Fans and Pumps: Blade Pass, Vane Pass, Cavitation and Flow-Related Vibration

From Mechanical Maintenance to Vibration Analysis - Part 9

In Part 8 - Resonance Diagnosis, we learned that a normal forcing frequency can become severe when it excites a natural frequency. Fans and pumps create important forcing frequencies of their own, especially blade-pass and vane-pass frequencies.

These machines also interact continuously with air, gas or liquid. A spectrum therefore reflects more than the rotor and bearings. It can contain evidence of inlet restrictions, poor operating point, recirculation, turbulence, cavitation, impeller or blade condition, and structural response.

Blade pass and vane pass are forcing frequencies, not automatic fault diagnoses. Their meaning comes from amplitude, harmonics, sidebands, waveform, operating point and process condition.

Begin with speed and component geometry

Before interpreting a peak, record the actual shaft speed and count the blades or vanes. Convert speed from revolutions per minute to hertz:

Running frequency (Hz) = rpm / 60

Then calculate the relevant pass frequency:

Blade-pass frequency (BPF) = number of blades x running frequency
Vane-pass frequency (VPF) = number of impeller vanes x running frequency

A fan with 8 blades operating at 1,200 rpm has a running frequency of 20 Hz and a blade-pass frequency of 160 Hz. A pump with 6 vanes operating at 1,480 rpm has a running frequency of 24.67 Hz and a vane-pass frequency of approximately 148 Hz.

The pass frequency normally exists because each blade or vane repeatedly moves past a stationary part of the housing. Pressure and flow vary during every pass. A visible peak is therefore expected on many healthy machines. What matters is whether it has changed and what other evidence accompanies it.

What makes a pass-frequency peak important?

A blade- or vane-pass peak deserves investigation when one or more of the following occur:

• Its amplitude rises significantly from a comparable baseline.
• Harmonics of the pass frequency increase.
• Running-speed sidebands appear or grow around the pass frequency.
• The response becomes strongly directional or changes with flow, damper position or load.
• The time waveform becomes distorted or contains repeating bursts.
• Pressure, flow, sound, temperature or power changes at the same time.

Possible causes include dirty or damaged blades, worn vanes, rotor or housing eccentricity, a loose impeller, diffuser or inlet problems, non-uniform blade spacing, flow restrictions, operation away from the intended duty point, or resonance near the forcing frequency. The spectrum alone rarely separates all of these possibilities.

Sidebands and harmonics add diagnostic information

Sidebands indicate modulation. If peaks around BPF or VPF are spaced by 1X running speed, something that changes once per revolution may be modulating the pass event. Possibilities include eccentricity, uneven clearance, a loose impeller, one damaged area, or another once-per-revolution flow disturbance.

For example, a six-vane pump at 24.67 Hz has VPF near 148 Hz. Peaks near 123.3, 148 and 172.7 Hz form 1X-spaced sidebands. This is evidence of modulation; it does not identify the physical cause by itself. Inspect the impeller, clearances and casing, compare radial directions, review phase where useful, and check whether the pattern changes with operating point.

Harmonics of BPF or VPF can result from a non-sinusoidal, strongly distorted or impacting force. Their presence may be normal for some designs, especially if stable. Trend comparable conditions and compare similar machines before deciding that the amplitude is abnormal.

Fan vibration: combine aerodynamics with mechanical checks

Fan vibration can be influenced by rotor unbalance, alignment, bearings, belts and looseness, but it may also respond strongly to the air system. Useful checks include:

• Blade condition: inspect for dust buildup, corrosion, erosion, cracks, bent blades and missing balance weights.
• Inlet condition: check filters, screens, elbows, dampers and obstructions that can create uneven flow into the wheel.
• Outlet and duct condition: look for restrictions, abrupt transitions, flexible-connection problems and unstable damper operation.
• Operating point: record flow, pressure, damper position, motor load and speed. A changing process may change vibration without a new mechanical defect.
• Structure: compare BPF and its harmonics with natural frequencies. An aerodynamic force can become severe when resonance amplifies it.

On variable-speed fans, collect vibration and process data across a controlled speed range when the procedure permits. If BPF moves with speed but the response becomes large only near one fixed frequency, resonance becomes a strong competing hypothesis.

Pump vibration: start with the operating point

A centrifugal pump should be evaluated with its pump curve and system condition. The best efficiency point (BEP) is the flow at which a particular pump operates most efficiently for a given speed and impeller diameter. The manufacturer normally defines an allowable operating region around it.

Operating too far from the intended region can create unstable hydraulic forces, recirculation, pressure pulsation, higher radial load, noise and vibration. The exact acceptable region is pump-specific; do not turn a general percentage from a training chart into a universal limit.

Always record the operating state with the vibration reading:

• Suction and discharge pressure.
• Flow rate and valve positions.
• Liquid level and temperature.
• Speed, motor current or power, and pump configuration.
• Whether strainers, filters or parallel pumps have changed.

A route measurement taken at a different flow condition may not be directly comparable with the previous trend.

Cavitation: bubble formation and collapse

Cavitation begins when local liquid pressure falls low enough for vapour bubbles to form. As the bubbles move into a higher-pressure region, they collapse. Repeated collapse can generate noise, random impacts, vibration and material damage.

Common contributors include insufficient available net positive suction head, a restricted suction line or strainer, low tank level, excessive liquid temperature, poor inlet geometry, air ingress, excessive speed, or an operating point that demands more flow than the suction system can supply.

Typical evidence may include:

• A gravel-like or crackling sound.
• Random high-frequency bursts in the time waveform.
• A raised broadband noise floor or broad spectral humps.
• Changes at vane-pass frequency and its harmonics.
• Unstable suction pressure, flow or discharge pressure.
• Loss of performance and, with prolonged exposure, impeller pitting.

These symptoms are not unique to cavitation. Air entrainment, rubbing, a damaged bearing, process solids, resonance and sensor-mounting problems can produce similar evidence. Confirmation requires process checks and, where possible, inspection.

NPSH is a system check, not a vibration label

The pump manufacturer specifies net positive suction head required (NPSHr) for a defined test condition. The system provides net positive suction head available (NPSHa). Reliable operation requires sufficient margin between the available and required values under real operating conditions, according to the manufacturer's guidance and the applicable engineering standard.

A vibration analyst does not confirm adequate NPSH from a spectrum alone. Work with operations or engineering to verify suction pressure, vapour pressure at the actual liquid temperature, static head, suction-line losses, speed and flow. Never throttle a pump's suction valve as an improvised diagnostic test unless an approved procedure specifically permits it.

Recirculation and turbulence can resemble other faults

Internal recirculation can occur when flow separates and circulates within the impeller or casing, often during operation away from the intended region. It may produce low-frequency pulsation, broadband energy, pressure fluctuation and changes near VPF.

External turbulence can result from obstructions, sharp elbows close to the inlet, abrupt area changes, partially closed valves, dirty filters or disturbed inlet flow. In fans and pumps it may appear as broad, unstable low-frequency energy rather than a clean mechanical order.

A practical distinction is responsiveness to process change. If vibration follows flow, pressure, valve or damper position while shaft speed remains nearly constant, a flow-related mechanism becomes more likely. Make only approved operational changes and remain inside the manufacturer's limits.

Do not confuse cavitation with a bearing defect

Evidence	Cavitation or flow issue	Rolling-element bearing defect
Relationship to process	Often changes with flow, suction condition or liquid temperature	May change with load, but normally follows bearing geometry and speed
Waveform	Random or irregular high-frequency bursts	More regularly repeating impacts may be present
Spectrum	Broadband rise, humps and possible VPF changes	Calculated defect families and harmonics may appear, especially in enveloped data
Supporting checks	Pressure, flow, NPSH review, sound and impeller inspection	Envelope spectrum, lubrication condition, ultrasound and bearing inspection

The strongest diagnosis explains both vibration and process behaviour. If the evidence does not separate the alternatives, state the uncertainty and recommend the next discriminating test.

Worked diagnosis: six-vane process pump

A six-vane centrifugal pump operates at 1,480 rpm, or 24.67 Hz. The calculated vane-pass frequency is approximately 148 Hz. The latest measurement shows a higher VPF peak, a raised high-frequency noise floor and irregular bursts in the acceleration waveform. Operators also report a gravel-like sound and unstable discharge flow.

The analyst compares the data with the previous baseline and checks the operating condition:

• Speed is unchanged.
• Suction pressure is lower than during the baseline measurement.
• Liquid temperature is higher.
• Flow has increased after a process change.
• The suction strainer differential pressure is above its normal range.

Interpretation: the vibration and process evidence support a suction-side flow problem with cavitation as the leading hypothesis. The VPF increase alone would not be enough to reach that conclusion.

Action: operations returns the pump to an approved stable condition and the responsible team inspects the suction path and strainer. Engineering verifies the system's NPSH margin. After the confirmed restriction is corrected, suction pressure, flow, sound and vibration are remeasured under the same operating state. The broadband energy and VPF amplitude return near baseline.

How System 1 and other software help

Condition-monitoring software can calculate and trend BPF or VPF, display spectra and waveforms, create narrow-band alarms, trend broadband high-frequency energy, compare multiple measurement locations, and correlate vibration with speed, flow, pressure, temperature and load.

Online systems are especially useful when a flow problem is intermittent. Time-synchronised process and vibration trends can show whether vibration changes before, after or at the same time as the process condition.

Software still cannot guarantee an exact diagnosis. Blade count, vane count, actual speed, sensor position, frequency range, sampling, mounting and process tags must be correct. The analyst must test competing explanations and close the loop after action.

A practical fan-and-pump workflow

1. Verify the measurement. Confirm sensor position, direction, mounting, units, Fmax and actual speed.
2. Calculate forcing frequencies. Mark 1X, harmonics, BPF or VPF, bearing frequencies, belt frequencies and electrical components where relevant.
3. Record the operating condition. Include flow, pressure, valve or damper position, temperature, level, load and configuration.
4. Compare with a valid baseline. Use the same speed, load and process state whenever possible.
5. Read spectrum and waveform together. Look for harmonics, sidebands, broadband energy, modulation, impacts and instability.
6. Inspect the machine and flow path. Check blades, impeller, clearances, filters, strainers, ducts, piping, supports and visible damage.
7. Rank competing causes. Separate mechanical, hydraulic or aerodynamic, structural and measurement explanations.
8. Choose a discriminating test. Correlate process tags, use an approved operating change, review phase or resonance data, and apply other condition-monitoring methods.
9. Verify after correction. Repeat vibration and process measurements under the same condition.

Final takeaway

• BPF and VPF are calculated forcing frequencies, not automatic fault names.
• Amplitude change, harmonics, sidebands and operating condition give the peaks meaning.
• Cavitation commonly produces noise, random impacts and broadband high-frequency energy, but it must be confirmed with process evidence.
• Fans and pumps should be diagnosed as complete machine-and-process systems.
• A good report states the evidence, uncertainty, recommended check and verification result.

Coming in Part 10

Part 10: Electric Motor Vibration - Line Frequency, Pole Pass, Rotor Bars and Electrical/Mechanical Separation. We will connect spectral patterns with motor load, current data, speed and mechanical checks.

Discussion question: Have you seen a pump or fan repaired mechanically when the main cause was actually the operating condition or flow path?

References and further learning

• Mobius Institute, Vibration Analysis Category II Course Manual, Chapter 16: Pumps, Fans and Compressors.
• Emerson Process Management, Basic Vibration Analysis - Course 2031, Chapter 1: Introduction to Vibration, including pump-pass frequency and the fault guide.

Educational note: The patterns and examples in this article are learning guidance, not universal alarm limits, NPSH calculations, operating procedures or acceptance criteria. Follow approved site safety procedures, pump and fan manufacturer requirements, process limits and qualified engineering judgement.

Resonance Diagnosis: Natural Frequencies, Bump Tests and Run-Up/Coast-Down Analysis

From Mechanical Maintenance to Vibration Analysis - Part 8

In Part 7 - Gearbox Faults, we saw that gear-mesh vibration can be amplified when a forcing frequency approaches a structural natural frequency. This is resonance: a condition that can make a modest forcing force produce severe vibration.

Resonance is easily misdiagnosed. A large 1X peak may be blamed on extreme unbalance, a blade-pass peak on a fan defect, or gear-mesh vibration on damaged teeth. The forcing frequency is real, but the structure may be multiplying its response.

A natural frequency belongs to the structure. Resonance occurs only when a forcing frequency excites that natural frequency.

Natural frequency and resonance are not the same

Every shaft, bearing housing, baseplate, foundation, pipe and support has natural frequencies. They are properties of the system's mass, stiffness and damping. A structure can have many natural frequencies, each associated with a particular pattern of movement called a mode shape.

A natural frequency may remain quiet for years. Resonance begins when a periodic force approaches it closely enough to excite the mode. Common forcing frequencies include:

• Shaft running speed and its harmonics.
• Fan blade-pass and pump vane-pass frequencies.
• Gear-mesh frequency and its harmonics.
• Reciprocating forces, electrical frequencies and flow pulsation.
• Impacts, looseness and forces transmitted from nearby equipment.

The response does not need an exact frequency match. The width of the resonant region depends strongly on damping. A lightly damped structure has a narrow, sharp response with high amplification. Greater damping normally lowers the peak and spreads the response over a wider frequency band.

Mass, stiffness and damping control the response

For a simple mass-spring system, natural frequency increases with stiffness and decreases with mass. The practical relationships are:

• More mass: generally lowers natural frequency.
• Less mass: generally raises natural frequency.
• More stiffness: generally raises natural frequency.
• Less stiffness: generally lowers natural frequency.
• More damping: generally reduces resonant amplification.

These relationships guide corrections, but real machines have multiple coupled modes. A brace, support or added mass can solve one resonance and move another mode into a forcing-frequency range. Structural changes therefore require engineering review and post-modification testing.

Clues that should make you suspect resonance

Observation	Why resonance is possible	Next test
One unusually large spectral peak	A normal forcing frequency may be amplified	Identify the forcing frequency, then perform a resonance test
High vibration in one direction but much lower in another	Structural stiffness and mode shape are directional	Map amplitude and phase across the structure
Amplitude rises sharply only in a narrow speed range	A speed-related order may be crossing a natural frequency	Run-up or coast-down with a tachometer
A broad hump or raised noise floor surrounds peaks	Several components may be amplified within a resonant band	Bump test or frequency-response measurement
Repeated cracked welds, pipes or supports without another clear cause	Amplified cyclic stress may be driving fatigue	Inspect, map motion and test the suspected structure

These observations justify a test; they do not prove resonance. Unbalance, looseness, misalignment, soft foot, hydraulic excitation and poor measurement technique can produce similar clues.

Amplitude and phase through resonance

As a speed-related forcing frequency approaches a natural frequency, amplitude rises. At the resonant region it reaches a maximum, then falls as the forcing frequency moves above the mode.

Phase provides the stronger confirmation. In a simple single-mode response, phase changes progressively by approximately 180 degrees while passing through resonance, with approximately 90 degrees of lag near the natural frequency. Actual plant data can be distorted by other modes, measurement location, phase wrapping, speed changes and poor tachometer signals, so interpret the complete amplitude-and-phase trend rather than one phase reading.

A Bode plot displays amplitude and phase against speed or frequency. A resonant peak combined with the expected phase transition is much stronger evidence than amplitude alone.

Test 1: the bump or impact test

A bump test introduces a short impact into a stationary structure and measures the frequencies at which it rings. The impact contains energy over a range of frequencies; the structure responds most strongly near its natural frequencies.

Safety comes first. Perform the test only under an approved site procedure. Isolate equipment where required, confirm that stored energy and process hazards are controlled, and never strike rotating, hot, pressurized, fragile or safety-critical components. Select a safe impact point and a suitable hammer or soft mallet that will not damage the surface.

Practical collection sequence

1. Define the forcing frequency and the suspected direction of movement.
2. Mount an accelerometer firmly on the structure in that direction.
3. Select an Fmax high enough to include the suspected mode and use a rectangular/uniform window where the instrument procedure requires it.
4. Use peak-hold averaging or a triggered impact setup. Low line resolution can help capture a short event quickly; refine the test later if nearby modes must be separated.
5. Make practice impacts to set the gain without clipping, then collect several consistent single impacts.
6. Repeat in other directions and at other positions. Avoid judging the structure from a nodal point, where the mode may show little movement.
7. Compare the response peaks with actual forcing frequencies and with historical tests.

The Mobius Category II manual offers example starting settings such as peak-hold averaging, about 400 lines or fewer, multiple averages and pre-triggering where available. These are instrument-dependent setup guides, not universal requirements. A calibrated impact hammer and frequency-response function provide better control because both input force and structural response are measured.

Test 2: run-up and coast-down analysis

During a controlled run-up or coast-down, shaft speed changes and the machine's orders sweep through a range of frequencies. If an order crosses a natural frequency, the response increases and then decreases. A waterfall plot shows the moving order as a diagonal ridge and the resonant region as a high-amplitude zone near a fixed frequency.

Use a reliable tachometer and collect spectra quickly enough to capture the transition. Order tracking can extract 1X or another order while speed changes and display amplitude and phase on a Bode or polar plot. This is especially useful when the machine starts or stops slowly enough for the mode to respond.

Run-up and coast-down tests must follow the machine manufacturer's limits and site operating procedure. Do not hold a machine near a suspected critical speed merely to improve the plot. Some flexible-rotor machines are designed to pass through critical speeds rapidly.

ODS and modal analysis answer different questions

An operating deflection shape (ODS) uses amplitude and phase measured while the machine operates to animate its motion at a selected frequency. It shows how the machine is moving under the present forces. It does not automatically identify every natural mode.

Modal analysis uses a measured input from an instrumented hammer or shaker and measures the structural response, normally with the machine stopped. It identifies natural frequencies, damping and mode shapes more directly. For complex structures or high-consequence modifications, specialist modal testing or finite-element analysis may be required.

Worked diagnosis: fan vibration near running speed

A belt-driven fan operates at 1,490 rpm, or 24.8 Hz. The fan outboard bearing measures 9.2 mm/s horizontally but only 1.8 mm/s vertically. The spectrum is dominated by 1X. Balancing reduces the calculated unbalance force but the vibration remains high.

The analyst records these findings:

• A stationary bump test shows a strong horizontal response at 25.4 Hz.
• A controlled coast-down shows the 1X amplitude rising sharply near 25 Hz and falling below it.
• The 1X phase changes progressively through the high-amplitude region.
• Movement mapping shows the fan base swaying horizontally, with the largest response near the unsupported side.

Conclusion: fan 1X is exciting a horizontal structural natural frequency. Residual unbalance supplies the forcing force, but structural flexibility supplies the amplification.

Action: an engineering review identifies a suitable brace and verifies loads, clearances and foundation condition. After installation, the natural frequency moves away from 1X. The bump test, coast-down and steady-state measurements are repeated under comparable conditions to confirm lower vibration and ensure that no new forcing frequency has been approached.

Correcting resonance without creating another problem

There are four broad strategies:

1. Change the forcing frequency. Adjust operating speed or process pulsation where the machine and process design allow it.
2. Move the natural frequency. Change stiffness or mass through an engineered structural modification.
3. Reduce transmission. Use correctly designed isolation where appropriate.
4. Add damping. Dissipate energy and reduce amplification.

A separation of roughly 15 to 20 percent between a forcing frequency and a natural frequency is commonly used as a screening guide in the reviewed training materials. It is not a universal acceptance limit. Follow the equipment manufacturer's criteria, applicable standards and qualified engineering analysis.

Do not add a brace, mass or isolator simply because it appears convenient. Confirm the mode shape, check structural loads and piping strain, preserve alignment, and test across all operating speeds and important harmonics after the change.

How System 1 and other software help

Condition-monitoring platforms can correlate vibration with speed and load, store run-up and coast-down data, display waterfall and Bode plots, track orders, compare phase, and trend narrow frequency bands. Modal and ODS packages can animate structural movement and calculate frequency-response functions.

Software organizes evidence; it does not make an exact diagnosis automatically. The analyst must verify the tachometer, sensor direction, mounting, operating condition, test repeatability and physical meaning of every peak and phase change.

An eight-step resonance diagnosis workflow

1. Identify the forcing frequency. Calculate 1X, harmonics, blade/vane pass, gear mesh, electrical and process frequencies.
2. Confirm the symptom. Compare directions, locations, operating states and historical trends.
3. Check measurement quality. Verify sensor mounting, Fmax, resolution, phase reference and tachometer signal.
4. Form competing hypotheses. Include unbalance, looseness, misalignment, soft foot, hydraulic forces and transmitted vibration.
5. Select a safe test. Use a bump test, speed variation, run-up/coast-down, ODS or modal analysis according to risk and machine availability.
6. Combine amplitude and phase. Look for an amplitude maximum and a progressive phase transition through the suspected mode.
7. Design the correction. Change force, stiffness, mass, isolation or damping only after engineering review.
8. Close the loop. Repeat the special test and normal route measurements across the operating range.

Final takeaway

• Natural frequencies exist in every machine and structure.
• Resonance is the amplified response created when a forcing frequency excites a natural frequency.
• A large spectral peak alone does not prove a severe mechanical fault.
• Directionality, speed sensitivity, bump tests, waterfall plots and phase changes build stronger evidence.
• Structural modifications must be engineered and verified across the complete operating range.

Coming in Part 9

Part 9: Fans and Pumps - Blade Pass, Vane Pass, Cavitation and Flow-Related Vibration. We will connect spectra and waveforms with operating point, pressure, flow, recirculation and mechanical condition.

Discussion question: Have you encountered a machine that was repeatedly balanced or aligned before resonance was identified as the real amplifier?

References and further learning

• Mobius Institute, Vibration Analysis Category II Course Manual, Chapter 17: Natural Frequencies and Resonance.
• Emerson Process Management, Basic Vibration Analysis - Course 2031, Chapter 10: Resonance.

Educational note: The diagnostic patterns and setup examples are learning guidance, not universal alarm limits, test procedures or structural-acceptance criteria. Apply approved site safety procedures, manufacturer requirements and qualified engineering judgement.

Gearbox Faults: Gear Mesh Frequency, Sidebands and Evidence

From Mechanical Maintenance to Vibration Analysis - Part 7

In Part 6 - Rolling-Element Bearing Faults, we learned that a calculated fault frequency is evidence, not an automatic replacement decision.

The same discipline is essential for gearboxes. Gear-mesh vibration exists even when the gears are healthy, its amplitude changes with load, and several shafts may modulate the same mesh frequency. The analyst's job is not simply to find gear mesh frequency. It is to explain what is changing around it.

Gear mesh frequency tells you where tooth contact occurs. Sideband spacing often tells you which shaft is modulating that contact.

Start with a gearbox map, not the spectrum

Before collecting data, sketch the drive train. Record the input, intermediate and output shaft speeds; the number of teeth on every mating gear; the gear type; bearing locations; measurement points; normal load range; lubrication system; and direction of rotation.

This map allows you to calculate each shaft speed and each gear-mesh frequency. Without it, a high-frequency peak may be mistaken for a gear mesh, bearing frequency, motor-bar frequency, blade-pass frequency or structural resonance.

Calculate gear mesh frequency correctly

Gear mesh frequency (GMF) is the rate at which teeth enter mesh:

GMF = number of teeth x rotational frequency of that gear

The same GMF must be obtained from either member of a mating pair. If one result differs, the tooth count, shaft speed or gear pairing is wrong.

Worked calculation

A 24-tooth input pinion rotates at 2,400 rpm, or 40 Hz, and drives a 72-tooth gear.

• Input GMF = 24 x 40 = 960 Hz.
• Output shaft speed = 960 / 72 = 13.33 Hz, or approximately 800 rpm.
• Output GMF check = 72 x 13.33 = approximately 960 Hz.

A multi-stage gearbox has a separate GMF for every mating pair. Work through the train one stage at a time and keep the shaft names consistent.

Why GMF alone is not a defect verdict

Every tooth pair generates a small force variation as contact moves through engagement, rolling and sliding. GMF may therefore appear in a healthy gearbox. Its amplitude is also strongly influenced by transmitted torque, gear design, tooth profile, stiffness, backlash, lubrication, resonance and the sensor transmission path.

A higher GMF amplitude at a higher load does not automatically mean deterioration. Compare measurements at similar speed, load, temperature and process condition. Trend the same point, direction, sensor mounting and acquisition setup.

Observation: GMF increased from 2.0 to 3.5 mm/s.

Question: Did gear condition change, or did torque, speed, alignment, lubrication, resonance or measurement setup change?

Better evidence: comparable operating data plus GMF harmonics, sidebands, waveform impacts, trends and corroborating inspection findings.

Sidebands are modulation evidence

When the amplitude or frequency of a gear-mesh signal changes periodically, the FFT produces peaks on both sides of GMF. If the modulating frequency is f_m, sidebands may appear at:

GMF - f_m, GMF + f_m, GMF - 2f_m, GMF + 2f_m ...

A damaged or eccentric gear rotates once per shaft revolution. Its contact stiffness or tooth load may therefore vary at that shaft's 1X frequency, producing GMF sidebands spaced by that shaft speed.

Measure the spacing; do not judge the cluster by appearance alone. In a gearbox with 40 Hz input speed and 13.33 Hz output speed:

• Sidebands spaced by 40 Hz point toward modulation associated with the input shaft or pinion.
• Sidebands spaced by 13.33 Hz point toward the output shaft or gear.
• Both spacings may indicate that both gears, their alignment, or a shared load path is involved.

The number and amplitude of sidebands often become more useful than the central GMF amplitude. They still do not identify the physical failure mode by themselves; they identify a repeating modulation that must be connected to the machine.

Read the complete pattern

Observed pattern	Possible explanation	Useful next check
Stable GMF with few small sidebands	Normal tooth contact or stable load-related response	Compare with baseline at the same load
GMF sidebands spaced at one shaft speed	Eccentricity, runout, localized tooth damage or load modulation on that shaft	Inspect waveform, phase, gear contact and shaft runout
Higher GMF harmonics with sideband families	Increasing nonlinearity, misalignment, wear, looseness or severe contact disturbance	Check alignment, backlash, mounting, load and oil debris
Once-per-revolution impact in acceleration waveform	Cracked, chipped or broken tooth; localized contact defect	Relate impact period to the responsible shaft and inspect teeth
Broadband high-frequency energy	Impacts, poor lubrication, wear debris, looseness, bearing activity or resonance	Use waveform, oil analysis, envelope data and local comparisons

These are hypothesis patterns, not universal fault rules. Gear geometry, load, transmission path and structural resonance can change the appearance significantly.

Use the acceleration time waveform

Gearbox waveforms are naturally busy because many teeth are engaging. A localized damaged tooth can add a stronger pulse once per revolution of the shaft carrying that tooth. Acceleration usually reveals these short impacts more clearly than velocity.

Set the waveform duration long enough to include several revolutions of the slow shaft. A very short record may show tooth-mesh impacts but hide the slow once-per-revolution modulation. Look for:

• Repeating impacts at the input, intermediate or output shaft period.
• Amplitude beating that agrees with the measured sideband spacing.
• Random bursts that may indicate looseness, debris or intermittent contact.
• Peak-to-peak growth even when the velocity RMS changes little.

Measurement setup can make or break the diagnosis

GMF and its harmonics can be far above the frequency range used for routine motor data. The Emerson course recommends an Fmax of approximately 3.5 x GMF where practical so higher harmonics and adjacent sidebands remain visible. SKF gives a similar practical starting point of about 3.25 x GMF. Treat these as setup guides, not severity limits.

Also consider:

• Resolution: the frequency spacing between lines must be much smaller than the slowest shaft speed you need to separate.
• Sensor: use an accelerometer with adequate high-frequency response.
• Mounting: stud mounting normally preserves high-frequency content better than a hand-held probe or loose magnet.
• Location: measure near each bearing that supports a gear shaft, in relevant radial directions and axial direction for helical gears where appropriate.
• Sampling: avoid aliasing and retain enough waveform samples to capture impacts.
• Operating state: record speed, load, direction, oil temperature and transient events.

A single spectrum may require both a wide frequency view and a high-resolution zoom around GMF. The wide view finds harmonics and resonances; the zoom separates closely spaced sidebands.

Variable speed requires order-based thinking

When speed changes, GMF and shaft-related sidebands move. A fixed-frequency trend can miss the peak or combine different operating states. Use tachometer-referenced orders, speed-synchronous sampling, waterfall plots or narrow speed/load bands where available.

During run-up or coast-down, a gear-mesh harmonic may cross a structural natural frequency and grow dramatically. That amplitude increase may be resonance amplification rather than sudden tooth deterioration. A waterfall plot helps separate a speed-following order from a fixed natural frequency.

Do not confuse gear, bearing and process activity

Several sources can occupy the same high-frequency region:

• Rolling-element bearing frequencies and their harmonics.
• Motor rotor-bar or stator-slot frequencies.
• Fan blade-pass, pump vane-pass or compressor lobe frequencies.
• Variable-frequency-drive switching activity.
• Structural resonance excited by normal gear mesh.
• Impacts from looseness, coupling problems or a nearby machine.

Gear mesh is synchronous with shaft speed and tooth count. Bearing defect frequencies are normally non-integer orders and may include cage- or shaft-related sidebands. Calculate all credible sources before assigning a label.

Worked diagnosis: two-stage conveyor gearbox

A conveyor gearbox operates at steady production load. The input shaft runs at 29.5 Hz, the intermediate shaft at 8.2 Hz and the output shaft at 1.9 Hz. The first-stage GMF is 590 Hz. The analyst observes:

• GMF remains similar to the historical baseline.
• Sidebands around GMF have increased and are spaced at 8.2 Hz.
• The same spacing appears around 2xGMF.
• The acceleration waveform shows amplitude modulation every 0.122 seconds, approximately one intermediate-shaft revolution.
• Oil debris has increased slightly, while bearing envelope trends remain stable.

Observation: a growing first-stage mesh sideband family is modulated at intermediate-shaft speed.

Leading hypothesis: a developing tooth-contact problem associated with the intermediate-shaft gear, such as localized wear, eccentricity or alignment-related load variation.

Competing explanations: load fluctuation at 8.2 Hz, gear resonance, shaft runout, support-bearing clearance, loose mounting or an incorrect shaft-speed calculation.

Recommended actions: repeat data at comparable load; verify shaft speeds and tooth counts; collect high-resolution spectra and longer acceleration waveforms; check phase and runout where practical; review alignment, backlash and lubrication; inspect oil debris; and schedule a borescope or tooth-contact inspection according to risk.

An eight-step gearbox diagnosis workflow

1. Map the train. Record every shaft speed, tooth count, gear pair, bearing and measurement point.
2. Record operating condition. Capture speed, torque or load, direction, temperature and lubrication state.
3. Calculate all frequencies. Include shaft orders, each GMF, GMF harmonics, bearing frequencies, blade/vane frequencies and relevant electrical components.
4. Verify measurement quality. Confirm sensor, mounting, Fmax, resolution, waveform length and tachometer signal.
5. Read the pattern. Compare GMF, harmonics, sidebands, broadband energy and the acceleration waveform.
6. Measure sideband spacing. Connect the spacing to the input, intermediate or output shaft instead of guessing from peak height.
7. Test competing causes. Review load, alignment, backlash, bearings, resonance, lubrication, looseness, torsional effects and transmitted vibration.
8. Close the loop. Inspect gears and oil, document the actual failure mode, correct the root cause and repeat measurements under comparable conditions.

The damaged gear may not be the root cause

Common contributors to gear distress include incorrect or contaminated lubricant, inadequate oil delivery, water ingress, excessive or cyclic load, shaft misalignment, soft foot, incorrect backlash, bearing clearance or failure, housing distortion, poor installation, overheating and resonance.

Replacing one damaged gear without checking its mating gear and the cause can create a poor contact pattern and repeat failure. Gear-set, bearing and alignment decisions should follow the gearbox manufacturer's guidance and an inspection of the complete load path.

How System 1 and other software help

Condition-monitoring platforms can store gearbox kinematics, calculate shaft and mesh frequencies, place sideband cursors, trend selected bands, create waterfall plots, correlate vibration with speed and load, and alarm on changing patterns.

Software still depends on correct tooth counts, shaft speeds, sensor locations and operating context. It can display a sideband family instantly; the analyst must decide whether the spacing is physically credible and what test will distinguish the leading hypothesis from its competitors.

Final takeaway

• GMF is tooth count multiplied by the rotational frequency of the gear.
• GMF can be present in a healthy gearbox and is strongly affected by load.
• Sideband spacing often identifies the shaft modulating the mesh.
• Harmonics, waveform impacts, trends and oil evidence strengthen the diagnosis.
• Correct Fmax, resolution, waveform duration and sensor mounting are essential.
• A damaged gear is evidence of a failure mechanism, not necessarily its root cause.

Coming in Part 8

Part 8: Resonance and Natural Frequency Testing. We will examine resonance symptoms, impact testing, run-up and coast-down data, phase changes and practical ways to separate a forcing frequency from a structural response.

Discussion question: When you diagnose a gearbox, which evidence has been most useful - GMF trend, sideband spacing, acceleration waveform, oil analysis or visual inspection?

References and further learning

• Emerson Process Management, Basic Vibration Analysis - Course 2031, Section 6: Gear Defects.
• SKF, Spectrum Analysis, Section 10: Gears.
• Fluke Reliability, Condition Monitoring with VibGuard IIoT Helped Two Customers Avoid Over $1.7M in Damage and Downtime.

Educational note: The patterns are simplified learning guidance, not universal fault rules, alarm limits or remaining-life predictions. Apply approved site procedures, gearbox-manufacturer guidance and qualified engineering judgement to real machinery.

Rolling-Element Bearing Faults: Frequencies, Enveloping and Evidence

From Mechanical Maintenance to Vibration Analysis - Part 6

In Part 5 - From Spectral Peaks to Fault Hypotheses, we learned to separate an observation from a diagnosis and test competing explanations.

Now we apply that discipline to one of the most important and frequently misunderstood subjects in vibration analysis: rolling-element bearing faults.

A peak near a calculated bearing frequency is evidence. It is not, by itself, permission to replace the bearing.

Bearing signals may be weak, high-frequency and affected by load, lubrication, mounting, sensor position, structural resonance and speed variation. A reliable conclusion therefore combines the correct bearing geometry, good measurements, trending and physical evidence.

Why a local bearing defect creates vibration

When a rolling element repeatedly passes over a pit, crack or spall, it produces a short impact. That impact excites high-frequency resonances in the bearing, housing and sensor mounting path. The impacts repeat according to the geometry and speed of the bearing component involved.

The raw time waveform may show a train of impacts, while the FFT and envelope spectrum help reveal the repetition rate. Because bearing geometry is not normally synchronized to an exact integer multiple of shaft speed, many bearing frequencies appear at non-integer orders such as 3.58X or 5.42X.

The four calculated bearing frequencies

Frequency	Component represented	Typical supporting clues
BPFO Ball Pass Frequency Outer race	Rolling elements passing a fixed outer-race location	BPFO harmonics; amplitude may be strongest close to the loaded outer-race zone
BPFI Ball Pass Frequency Inner race	Rolling elements passing a defect rotating with the inner race	BPFI harmonics with possible 1X running-speed sidebands
BSF Ball Spin Frequency	Rotation of a ball or roller	BSF or its harmonics with possible cage-frequency modulation
FTF Fundamental Train Frequency	Cage rotational frequency	A low, sub-synchronous component; possible cage, lubrication or load-zone involvement

Use the manufacturer and exact bearing model whenever possible. Calculated frequencies depend on the number and size of rolling elements, pitch diameter and contact angle. Actual frequencies may shift slightly because of slip, load and operating condition, so software cursors should allow a sensible tolerance rather than demanding perfect alignment.

A practical frequency example

Consider a motor running at 1,800 rpm:

• Shaft speed = 1,800 / 60 = 30 Hz.
• Suppose the bearing database gives BPFO = 3.58X, BPFI = 5.42X, BSF = 2.35X and FTF = 0.40X.
• BPFO = 3.58 x 30 = 107.4 Hz.
• BPFI = 5.42 x 30 = 162.6 Hz.
• BSF = 2.35 x 30 = 70.5 Hz.
• FTF = 0.40 x 30 = 12 Hz.

If the envelope spectrum contains peaks near 107.4, 214.8 and 322.2 Hz, BPFO and its first two harmonics become a reasonable outer-race fault hypothesis. The analyst must still verify the bearing identity, actual speed, trend, sensor position and competing impact sources.

Why enveloping helps detect early damage

Early bearing impacts may contain little energy compared with normal shaft vibration. In a conventional velocity spectrum, strong 1X and 2X components can dominate the display while the bearing signal remains hidden in the high-frequency noise floor.

Envelope analysis, also called demodulation, typically:

1. Measures acceleration at a suitable sample rate.
2. Uses a high-pass or band-pass filter around a high-frequency resonance excited by the impacts.
3. Rectifies the filtered signal so the ringing transients can be followed.
4. Applies a low-pass stage and calculates the envelope spectrum to expose the lower-frequency impact repetition rate.

The result may reveal BPFO, BPFI, BSF or FTF before those components become obvious in a normal velocity spectrum. Enveloping does not replace the waveform or conventional spectrum; it adds another view of the same machine behaviour.

Envelope setup matters

The filter band and sampling rate determine what the instrument can reveal. The high-pass or band-pass filter should reject strong lower-frequency machine vibration while retaining a resonance band excited by short bearing impacts. The envelope-spectrum Fmax must then be high enough to display the bearing frequencies and several harmonics.

As a practical starting point, the Mobius Category II manual recommends an envelope-spectrum Fmax of roughly 3.5 to 5 times the calculated BPFI. If the bearing is unknown and has approximately 8 to 12 rolling elements, it suggests starting near 15X to 20X running speed. These are setup guides, not alarm limits; adjust them for the bearing, machine and instrument.

Choose the resonance band carefully. Motor-bar and variable-frequency-drive switching activity, gearmesh, reciprocating-machine impacts, rotating looseness and cavitation can also generate high-frequency energy. A strong envelope reading therefore proves that repetitive impacts or modulation are present, not automatically that the bearing is damaged.

Conventional velocity: useful for overall machine condition and lower-to-mid-frequency faults such as unbalance, misalignment and looseness.

Acceleration: sensitive to higher-frequency energy and impacts.

Envelope spectrum: useful for identifying the repetition rate hidden inside high-frequency impact energy.

Read harmonics and sidebands as modulation clues

A single peak close to a calculated frequency is weak evidence. Confidence improves when a physically meaningful family appears.

• Harmonics: repeated impacts can generate BPFO, 2xBPFO, 3xBPFO and higher multiples.
• 1X sidebands around BPFI: an inner-race defect rotates through the bearing load zone, so impact amplitude may be modulated once per shaft revolution.
• FTF sidebands around BSF: rolling-element damage may change as the element moves around the bearing and contacts the inner and outer raceways.
• Rising noise floor: more distributed surface distress, contamination or poor lubrication can create broadband high-frequency energy.

Sideband spacing matters. Do not call every cluster a bearing fault; measure the spacing and relate it to shaft speed, FTF or another credible modulating frequency.

High-frequency vibration normally attenuates more rapidly through a structure than low-frequency vibration. Compare equivalent high-frequency readings at nearby bearings: a signal concentrated at one housing provides useful location evidence, while the same low-frequency pattern at several points may be transmitted from another source.

A simplified progression of bearing deterioration

Bearing damage does not always follow a neat universal sequence, but analysts often see a progression similar to this:

1. Earliest indication: high-frequency energy or the envelope trend rises while conventional velocity changes little.
2. Localized race defect develops: a bearing-frequency family and harmonics become visible, often first for one race.
3. Damage spreads: more harmonics and sidebands appear; rolling-element or cage-related activity may join the race frequencies, and impacts become clearer in acceleration and the waveform.
4. Advanced deterioration: broadband energy and the noise floor rise, discrete peaks may become less distinct, clearances and internal geometry may change, and conventional velocity can become significant.

Do not misinterpret falling discrete peaks as recovery. Severe loss of internal geometry can reduce the clear transmission of individual frequencies while broadband energy and random impacts continue to increase.

Do not use this sequence as a countdown clock. Remaining life depends on the size and number of defects, the components involved, loss of internal geometry, rate of progression, load, speed, lubrication, service time and experience with genuinely comparable machines. No two cases are identical.

Do not confuse the damaged component with the root cause

A vibration pattern may identify where damage is occurring without explaining why it occurred. Possible contributors include:

• Insufficient, excessive, incorrect or contaminated lubricant.
• Water or solid-particle contamination.
• Misalignment, unbalance, belt forces or excessive external load.
• Incorrect fits, loss of internal clearance or installation damage.
• Electrical discharge or fluting in motors and variable-frequency-drive applications.
• Resonance, looseness or impacts transmitted from a nearby machine component.

Replacing the bearing without correcting the cause may simply restart the failure cycle.

Worked example: motor drive-end bearing

A motor runs at 1,780 rpm, or approximately 29.67 Hz. The correct bearing model gives BPFI = 5.45X. The analyst observes:

• Envelope peaks near BPFI and 2xBPFI.
• Sidebands around BPFI spaced at approximately 1X running speed.
• The envelope trend has doubled over six weeks at comparable load.
• Conventional velocity has increased only slightly.
• The drive-end bearing temperature is stable.
• Lubrication history shows a recent change in grease quantity.

Observation: a growing, speed-related impact family aligns with BPFI and includes 1X sidebands.

Leading hypothesis: developing inner-race-related distress.

Competing explanations: an incorrect bearing number, transmitted impacts, electrical activity, lubrication-related friction or a mounting problem.

Recommended actions: confirm actual speed and bearing identification; review the grease type, quantity and procedure; inspect motor current and grounding evidence where relevant; increase measurement frequency; and plan inspection or replacement according to risk and trend rate. After maintenance, inspect the removed bearing and document the failure mode rather than recording only “bearing replaced.”

A seven-step bearing diagnosis workflow

1. Verify the bearing and operating condition. Record model, speed, load, temperature and lubrication state.
2. Verify the measurement. Use a repeatable point, firm sensor mounting, suitable frequency range and adequate sampling.
3. Review multiple displays. Compare velocity, acceleration, envelope spectrum, waveform and trends.
4. Overlay the correct frequencies. Look for harmonics and meaningful sideband spacing, allowing for reasonable slip.
5. Compare locations and history. Check nearby bearings, directions, baselines and comparable machines.
6. Test the root-cause and false-positive hypotheses. Review lubrication, contamination, load, alignment, fits, electrical switching, gearmesh, cavitation and other impact sources.
7. Verify the intervention. Inspect the removed bearing and repeat measurements under a comparable condition.

High-frequency methods are deliberately sensitive. Unless risk, trend rate or a low-speed application justifies earlier action, avoid overhauling a machine from one envelope spectrum alone. Seek confirmation in repeatable trends, the conventional spectrum, waveform, lubrication condition or another independent technique.

How software helps - and where judgement remains essential

System 1 and other condition-monitoring platforms can store bearing data, calculate or import defect frequencies, apply frequency markers, trend amplitudes, display waveforms and spectra, and generate alarms. These features improve consistency and make developing patterns easier to see.

However, the software cannot guarantee that the installed bearing matches the database, that the speed is correct, that the sensor is well mounted, or that the peak comes from the bearing. The analyst still has to connect the signal to the machine and select the next discriminating test.

Final takeaway

• BPFO, BPFI, BSF and FTF are geometry-based diagnostic frequencies, not automatic failure verdicts.
• Early bearing damage is often easier to see in high-frequency acceleration and envelope data than in overall velocity.
• Harmonics, sidebands, waveforms and trends provide stronger evidence than a single peak.
• A damaged bearing is not necessarily the root cause of the failure.
• The best diagnosis combines vibration, operating condition, lubrication history and physical inspection.

Coming in Part 7

Part 7: Gearbox Faults and Sideband Analysis. We will examine gear mesh frequency, harmonics, sidebands, modulation and how to separate gear damage from shaft-speed and bearing-related activity.

Discussion question: Which bearing evidence do you trust most in your plant - envelope trends, defect-frequency patterns, temperature, lubrication findings or inspection results?

References and further learning

• Emerson Process Management, Basic Vibration Analysis - Course 2031, Section 5: Rolling Element Bearings.
• Mobius Institute, Category II Vibration Analysis Manual, Chapter 13: Rolling Element Bearing Analysis.
• SKF, Spectrum Analysis.
• SKF Evolution, Vibrations Help Find Faulty Components.
• Fluke, How Demodulation Helps You Detect Bearing Faults Early.
• Fluke, Smarter Bearing Monitoring.

Educational note: The patterns are simplified learning guidance, not universal fault rules, alarm limits or remaining-life predictions. Apply approved site procedures, bearing-manufacturer guidance and qualified engineering judgement to real machinery.

A Horrible Noise That Disappeared: Diagnosing a Loose Motor Cooling-Fan Part

A strange mechanical noise does not have to remain present for the fault to be real.

In a Bently Nevada success story from an offshore oil and gas platform, a technician heard a “horrible noise” from a dissolved-salts pump motor during routine vibration data collection. The noise disappeared shortly afterward, but the measurements taken during the event preserved the evidence. What followed is a valuable lesson in combining human observation, spectral analysis, waveform interpretation and focused inspection.

A transient sound may disappear before an inspection begins, but correctly captured vibration data can preserve the mechanical signature of the event.

The operating context

The machine was considered moderately critical and was monitored periodically using a portable Scout 220 data collector. Offshore technicians collected the readings, uploaded them to a System 1 server and requested remote diagnostic support from Bently Nevada Machinery Diagnostic Services engineers.

This arrangement matters. It shows how a condition-monitoring program can connect three important capabilities:

• People near the machine who notice abnormal sound, smell, heat or movement.
• Portable measurements that preserve the spectrum and time waveform.
• Diagnostic expertise that can interpret the data and guide a targeted inspection.

What the vibration data showed

The measurement taken while the noise was present contained a single prominent peak at approximately 1210 Hz, accompanied by 1X and 2X running-speed sidebands. The unusual vibration appeared only at the motor non-drive end and was absent from the later measurement taken after the noise stopped.

The 1210 Hz component did not match an expected forcing frequency for the machine. This prevented the analyst from simply assigning it to a normal rotating or electrical source. Instead, the spectrum and waveform suggested that repeated impacts were exciting a local resonance near 1210 Hz. The 1X and 2X sideband spacing showed that the high-frequency response was being modulated at running-speed-related intervals.

Measured observation: A 1210 Hz peak with 1X and 2X sidebands appeared at the motor non-drive end during the audible event.

Interpretation: Periodic impact or rubbing was likely exciting a structural resonance.

Location hypothesis: A loose rotating part or contact between rotating and stationary parts near the overhung cooling fan.

Discriminating action: Open the fan cover and inspect the cooling-fan assembly.

Why sidebands were important

A sideband is a spectral component that appears on either side of a carrier frequency. In this case, the carrier was the resonance near 1210 Hz. Regular variation in the amplitude of that vibration produced sidebands separated by the modulating frequencies.

The key point is not merely that sidebands existed. Their spacing connected the high-frequency resonance to a once-per-revolution and twice-per-revolution mechanical event. That relationship supported a hypothesis involving a rotating component repeatedly contacting, striking or changing load as the shaft turned.

Sidebands should always be interpreted with the waveform, machine speed, measurement location and equipment geometry. They describe modulation; they do not identify the damaged component by themselves.

Why the noise was so noticeable

The abnormal frequency was high enough to be heard clearly by the technician. Baker Hughes noted that it was near the frequency range where human hearing is particularly sensitive. This helps explain why the event sounded severe even though it was temporary.

Human senses remain useful screening tools in maintenance. An experienced technician may recognize a change before an alarm is triggered. However, the safest workflow is to treat sound as an observation, capture objective data and avoid approaching or opening moving equipment until it is isolated under the approved procedure.

The inspection confirmed the diagnosis

Because the abnormal response was localized at the non-drive end, the diagnostic team suspected the overhung cooling fan. They recommended removing the fan cover and looking for abnormalities.

The inspection found part of a broken retaining ring loose inside the cover. The ring belonged to the fan assembly and had separated. The technician replaced it, and the machine returned to service less than 48 hours after the abnormal measurement.

According to the source case study, failure to detect the problem could have allowed the fan to separate from the rotor and destroy the motor. The estimated replacement cost of the motor was approximately €40,000. The larger value, however, also included avoided secondary damage, unplanned downtime and operational risk.

A practical diagnostic workflow

1. Record the human observation. Note what was heard, where it was strongest, when it began and whether operating conditions changed.
2. Preserve event data. Save the spectrum, time waveform, speed, load, measurement direction and timestamp. Do not overwrite an abnormal reading with a later normal one.
3. Compare locations. A response isolated to one end or one direction can greatly reduce the search area.
4. Identify measured facts. List the dominant frequency, sideband spacing, waveform features and differences from the baseline.
5. Develop more than one hypothesis. Consider loose parts, rubbing, impacts, bearing faults, aerodynamic effects, electrical sources and structural resonance as appropriate.
6. Use machine geometry. Ask which component near the measurement point could physically produce the observed periodic event.
7. Choose a focused inspection. Inspect the suspected area under proper isolation instead of dismantling the entire machine.
8. Verify after repair. Repeat comparable measurements and confirm that the abnormal sound and vibration signature are gone.

Lessons for a condition-monitoring program

• Intermittent faults deserve immediate attention. Disappearance of the symptom is not proof that the defect corrected itself.
• Keep the abnormal dataset. Event measurements may contain evidence that routine follow-up readings no longer show.
• Use both spectrum and waveform. Frequency-domain sidebands reveal modulation, while the time waveform helps show the underlying impact pattern.
• Measurement location matters. Localization to the motor non-drive end directed attention toward the cooling fan.
• Combine technology with technician experience. The technician’s report of abnormal noise gave essential context to the data.
• Convert diagnosis into a specific action. The recommendation was not simply “monitor closely”; it identified the fan cover as the next safe inspection point.
• Moderately critical assets can still create major losses. Periodic portable monitoring can prevent expensive failures outside the permanently monitored machine population.

Final takeaway

This case is a strong example of evidence-based vibration analysis. A temporary noise was captured as a localized high-frequency resonance with running-speed sidebands. The pattern suggested impact or rubbing near the motor cooling fan, and a focused inspection revealed a broken retaining ring.

The successful diagnosis did not come from one spectral rule. It came from linking sound, timing, location, spectrum, waveform, machine geometry and physical inspection. That is the habit that turns condition-monitoring data into reliable maintenance decisions.

Source and further reading

This educational analysis is based on the Baker Hughes/Bently Nevada success story Loose Part on Motor Cooling Fan, authored by Håkon Myklestad of Norway MDS. Refer to the original case study for its spectrum, waveform and damaged-component images.

Educational note: This article summarizes a published case and expands on its diagnostic lessons. Actual machinery decisions must follow approved isolation procedures, manufacturer guidance, applicable standards and qualified engineering judgement.

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From Spectral Peaks to Fault Hypotheses: Unbalance, Misalignment and Looseness

From Mechanical Maintenance to Vibration Analysis - Part 5

In Part 4 - Understanding the Time Waveform and FFT Spectrum, we learned how running speed, harmonics, sidebands and acquisition settings help us read vibration data.

Now we take the next step: turning observed patterns into fault hypotheses.

A spectral peak is a measured fact. A fault name is an interpretation. Evidence must connect the two.

This distinction is essential. A strong 1X peak may support an unbalance hypothesis, but it may also be influenced by resonance, eccentricity, a bent shaft, looseness or transmitted vibration. Good analysts do not stop at pattern recognition; they test competing explanations.

Separate observation, interpretation and confirmation

Use three levels when communicating a diagnosis:

1. Observation: What does the data actually show?
2. Interpretation: Which mechanisms could reasonably produce it?
3. Confirmation: What additional evidence distinguishes the leading hypothesis?

For example:

Observation: Pump outboard radial velocity has a dominant, stable 25 Hz peak. The machine runs at 1,500 rpm.

Interpretation: The peak is 1X running speed; unbalance is one plausible cause.

Confirmation: Check radial direction, phase stability, response at both bearings, operating-speed behaviour, rotor cleanliness and evidence of resonance before recommending balancing.

Build the fault hypothesis from multiple clues

A useful hypothesis combines more than frequency. Review:

• Frequency: Is the component at 1X, 2X, a harmonic, subharmonic or another calculated frequency?
• Amplitude: Is it significant relative to the baseline, alarm criteria and nearby locations?
• Direction: Is the response mainly horizontal, vertical or axial?
• Phase: Is phase stable, and how does it compare across bearings, directions and the coupling?
• Waveform: Is the motion sinusoidal, impacted, clipped, modulated or irregular?
• Operating condition: Does the pattern change with speed, load, temperature, flow or pressure?
• Machine geometry: Where are the bearings, coupling, overhung components, supports and potential clearances?
• History: What changed after cleaning, overhaul, alignment, pipe work or process adjustment?

Hypothesis 1: Rotor unbalance

Unbalance exists when the mass centre of a rotating component does not coincide with its rotational axis. The resulting centrifugal force rotates once per revolution and increases strongly as speed increases.

Patterns that may support unbalance

• A prominent 1X running-speed component.
• Vibration is commonly stronger in radial directions than axial direction.
• The time waveform may look relatively sinusoidal when 1X dominates.
• 1X phase is often reasonably stable when speed and load are steady.
• The response may increase markedly near a structural or rotor resonance.

Possible physical causes include product buildup, erosion, a missing balance weight, an incorrectly installed component, rotor damage, casting variation or eccentric mass distribution.

Why 1X alone is not enough

A shaft rotates once per revolution, so many mechanical conditions can produce 1X. A bent shaft, eccentric sheave, resonance, misalignment, looseness, rub or external vibration may all contribute. A large 1X peak identifies a synchronous response; it does not identify the root cause by itself.

Useful confirmation checks

• Compare horizontal, vertical and axial readings at both bearings.
• Measure 1X phase with a reliable tachometer and check repeatability.
• Inspect the rotor for deposits, missing material or loose components.
• Review startup or coast-down data for resonance amplification.
• Check whether the vibration changed after cleaning or mechanical work.
• Before adding correction weight, confirm that looseness, soft foot and alignment are acceptable.

Hypothesis 2: Shaft misalignment

Misalignment means the shaft centre-lines of coupled machines are not collinear under their normal operating condition. It may be angular, offset or a combination. Thermal growth, pipe strain, soft foot, foundation movement and assembly errors can all alter the running alignment.

Patterns that may support misalignment

• Elevated 1X and/or 2X components near the coupling.
• Significant axial vibration, particularly with angular misalignment.
• Radial response on both sides of the coupling, especially with offset misalignment.
• A repeatable phase relationship across the coupling that is inconsistent with simple unbalance.
• Coupling temperature, bearing temperature or seal problems may accompany the vibration evidence.

The exact spectrum depends on coupling type, machine stiffness, bearing arrangement, load and degree of misalignment. Some misaligned machines show a strong 2X component; others are dominated by 1X. Therefore, the absence of a large 2X peak does not rule misalignment out.

Useful confirmation checks

• Compare axial and radial readings on both sides of the coupling.
• Take phase readings at consistent locations and directions across the coupling.
• Check coupling condition and temperature.
• Verify soft foot, base condition, hold-down bolts and pipe strain.
• Review cold alignment targets and expected thermal growth.
• Perform precision alignment using an approved method, then compare vibration before and after correction.

Hypothesis 3: Mechanical looseness

Mechanical looseness is excessive movement between parts that should remain fixed or move within a controlled clearance. It can occur at a machine foot, baseplate, foundation, bearing housing, bearing fit, shaft fit, coupling or structural joint.

Patterns that may support looseness

• A family of running-speed harmonics: 1X, 2X, 3X and higher.
• Sometimes subharmonics such as 0.5X, depending on contact and clearance behaviour.
• An impacted, truncated or asymmetric time waveform.
• Amplitude and phase that may be unstable between repeated measurements.
• Large differences between nearby points or directions.
• A nonlinear response: relatively small changes in load or speed produce large vibration changes.

Harmonics develop because looseness can distort an otherwise sinusoidal motion. Contact, clearance and changing stiffness create a non-sinusoidal waveform, which the FFT represents as multiple harmonics.

Useful confirmation checks

• Inspect hold-down bolts, grout, baseplate, welds and structural joints.
• Check bearing and housing fits where permitted by the maintenance procedure.
• Compare casing points immediately above and below suspected joints.
• Look for fretting, polished contact surfaces, cracked paint or movement marks.
• Perform a controlled bump or impact test if resonance or structural flexibility is suspected.
• Check whether phase is repeatable; erratic phase may support intermittent movement.

Comparison table: clues, not rigid rules

Evidence	Unbalance hypothesis	Misalignment hypothesis	Looseness hypothesis
Spectrum	Often dominant 1X	Often 1X and/or 2X	Often multiple running-speed harmonics; possible subharmonics
Direction	Usually radial emphasis	Axial and/or radial near coupling	Any direction; may differ sharply across a joint
Waveform	May be near sinusoidal	Periodic but often more complex	Impacted, clipped, asymmetric or irregular
Phase	Often stable at constant condition	Cross-coupling relationships can be diagnostic	May be unstable or inconsistent
Physical checks	Deposits, erosion, missing weight, rotor damage	Alignment, thermal targets, coupling, soft foot, pipe strain	Bolts, fits, grout, cracks, fretting and structural movement

Important: These are tendencies, not universal acceptance rules. Faults can coexist, and resonance can amplify any forcing frequency.

Worked motor-pump example

A direct-coupled motor-pump runs at 1,500 rpm, so 1X equals 25 Hz. The analyst records:

• Motor drive-end axial: strong 25 Hz and 50 Hz.
• Pump drive-end axial: strong 25 Hz and 50 Hz.
• Radial readings: moderate 25 Hz.
• Phase readings across the coupling: repeatable but significantly different.
• Coupling temperature: higher than its established baseline.
• Inspection history: pump pipe work was modified during the last shutdown.

Observation: 1X and 2X are elevated, axial vibration is significant on both sides of the coupling, cross-coupling phase is repeatable, and temperature has increased.

Leading hypothesis: Misalignment or externally imposed strain affecting alignment.

Competing explanations: Coupling defect, bent shaft, looseness, soft foot or structural amplification.

Next actions: Check pipe strain, soft foot, hold-down condition, coupling condition and hot-versus-cold alignment requirements before moving the machine. Repeat vibration and phase readings after any correction.

This conclusion is stronger than saying, “The spectrum has 2X, therefore the machine is misaligned.” It connects the spectrum with direction, phase, temperature, maintenance history and physical checks.

A practical hypothesis-testing workflow

1. Verify the data. Confirm point, direction, units, mounting, speed, load and acquisition settings.
2. State the observation. Record frequencies, amplitudes, directions, waveform features and phase behaviour without naming a fault.
3. List plausible mechanisms. Include at least one competing explanation.
4. Rank the hypotheses. Use machine design, operating condition and history.
5. Choose a discriminating test. Ask which measurement or inspection will separate the leading possibilities.
6. Correct the verified cause. Do not balance, align or tighten components merely because a pattern looks familiar.
7. Verify the result. Repeat measurements under a comparable condition and document the change.

How to write a defensible recommendation

Avoid:

The pump is unbalanced because the spectrum has 1X.

Prefer:

Radial vibration at the pump outboard bearing is dominated by a stable 1X component that has increased from its comparable-load baseline. Rotor unbalance is a leading hypothesis. Inspect the impeller for buildup or damage, check hold-down integrity and resonance response, and collect repeatable 1X phase data before deciding whether field balancing is appropriate.

Final takeaway

• Unbalance often emphasizes stable radial 1X, but 1X is not unique to unbalance.
• Misalignment may produce axial and radial 1X/2X near a coupling, but the exact pattern varies.
• Looseness may generate harmonics, impacts and unstable behaviour, but harmonics alone do not prove it.
• Direction, phase, waveform, operating condition, history and inspection turn a pattern into a testable hypothesis.
• The repair result is part of the diagnosis. Always verify the post-maintenance condition.

Coming in Part 6

Part 6: Rolling-Element Bearing Faults. We will examine bearing defect frequencies, high-frequency acceleration, enveloping, harmonics and sidebands—and why lubrication, load and installation must be considered before condemning a bearing.

Discussion question: Which fault have you found hardest to distinguish in the field—unbalance, misalignment or looseness?

References and further learning

• Fluke, Diagnosing Imbalance, Misalignment, Looseness, and Bearing Wear.
• Fluke, Mechanical Looseness: What It Is and How to Detect It.
• Fluke Reliability, Phase in Vibration Analysis: Theory, Applications, and Examples.
• Bently Nevada, Vibration and Dynamic Measurements.

Educational note: The patterns are simplified learning guidance, not universal fault rules or alarm limits. Apply approved site procedures, applicable standards, manufacturer guidance and qualified engineering judgement to real machinery.

Understanding the Time Waveform and FFT Spectrum

From Mechanical Maintenance to Vibration Analysis - Part 4

In Part 3 - Displacement, Velocity and Acceleration, we learned that the measurement quantity changes which part of a vibration signal is emphasized.

Now we move to the two plots an analyst uses most often:

The time waveform shows what the vibration did over time. The FFT spectrum shows how that vibration is distributed across frequency.

They are not two unrelated measurements. The spectrum is calculated from the sampled time waveform. Each view organizes the same signal differently, and each can reveal evidence that is difficult to see in the other.

Start with the time waveform

A time waveform plots:

• Amplitude on the vertical axis - displacement, velocity or acceleration; and
• Time on the horizontal axis - normally seconds or milliseconds.

The waveform answers questions such as:

• Is the motion smooth and repeating?
• Are there impacts, clipping, beats or modulation?
• How far apart are repeated events?
• Is the signal symmetrical?
• Does the vibration change during the record?

A clean sinusoidal waveform suggests that one frequency dominates. A complex machine waveform usually contains several vibration sources at the same time: shaft rotation, coupling forces, gears, bearings, blades, hydraulic activity, structural response and background noise.

Period and frequency

If a feature repeats every T seconds, its frequency is:

Frequency (Hz) = 1 / period (seconds)

Running frequency (Hz) = speed (rpm) / 60

For a motor running at 1,500 rpm:

1,500 / 60 = 25 Hz

One shaft revolution therefore takes:

1 / 25 = 0.04 seconds, or 40 milliseconds

If a waveform contains a strong event every 40 ms, the repetition rate is synchronous with running speed. That is useful evidence, but it does not by itself prove unbalance or any other single fault.

What the FFT spectrum does

The Fast Fourier Transform, or FFT, is a mathematical method that separates a sampled waveform into frequency components. The resulting spectrum normally plots:

• Amplitude on the vertical axis; and
• Frequency on the horizontal axis, commonly in hertz, cycles per minute or orders.

Instead of asking when an event happened, the spectrum helps us ask:

• Which frequencies contain the most vibration?
• Do peaks correspond with shaft speed or component frequencies?
• Are harmonics or sidebands present?
• Which peaks are changing over time?

A spectrum makes repeating components easier to separate. However, it removes much of the timing shape that can make impacts, modulation and transient behaviour obvious in the waveform.

Time waveform versus FFT spectrum

Question	Time waveform	FFT spectrum
Horizontal axis	Time	Frequency or order
Especially useful for	Impacts, beats, modulation, clipping, non-stationary events and waveform shape	Separating periodic components, identifying orders, harmonics, sidebands and component-related frequencies
What may be hidden	Closely spaced frequency components can overlap visually	The timing and shape of individual events can be difficult to recognize
Best practice	Review both views with the same units, point, direction, speed, load and acquisition settings.

Understanding 1X, 2X and harmonics

Analysts often express frequency as a multiple of shaft-running speed:

• 1X means once per shaft revolution.
• 2X means twice per shaft revolution.
• 3X means three times per shaft revolution.

For the 1,500 rpm motor:

• 1X = 25 Hz
• 2X = 50 Hz
• 3X = 75 Hz
• 4X = 100 Hz

Integer multiples of a fundamental frequency are called harmonics. A series at 1X, 2X, 3X and higher orders tells us that the waveform contains repeating non-sinusoidal content related to shaft rotation.

A harmonic family is a pattern, not a diagnosis. Several conditions can generate harmonics, and the same fault can look different on different machines.

Before attaching a fault name, compare the pattern with measurement direction, phase, machine construction, clearances, operating condition, history and physical inspection.

Worked motor-pump example

Consider a direct-coupled motor and centrifugal pump running steadily at 1,500 rpm. The pump impeller has six vanes.

1. Running speed: 1,500 / 60 = 25 Hz.
2. Shaft period: 1 / 25 = 0.04 s.
3. Vane-pass frequency: 6 vanes × 25 Hz = 150 Hz, or 6X.

Suppose the spectrum contains peaks at 25, 50 and 150 Hz.

• The 25 Hz peak is synchronous with shaft rotation.
• The 50 Hz peak is 2X running speed.
• The 150 Hz peak matches the calculated vane-pass frequency.

Those identities are defensible because they are based on measured speed and machine geometry. The cause still requires testing.

For example, a 1X peak could be influenced by unbalance, bent shaft, eccentricity, resonance, transmitted vibration or other mechanisms. A vane-pass peak may be influenced by normal hydraulic excitation, operating away from the best efficiency point, recirculation, clearance problems or structural amplification. The frequency tells us where to investigate; it does not complete the diagnosis.

What the waveform adds

If the waveform is smooth and repeats every 40 ms, shaft-synchronous motion may dominate. If sharp impacts repeat at the same interval, looseness, contact or another once-per-revolution event may be exciting a resonance. If the amplitude rises and falls in a regular envelope, modulation or beating may be present.

This is why the analyst should move between waveform and spectrum instead of relying on one display.

Sidebands and modulation

Sidebands are peaks spaced equally around a central frequency. Their spacing is important because it can identify the modulating frequency.

For example, peaks around 150 Hz separated by 25 Hz would be described as 1X sidebands around the vane-pass frequency:

125 Hz, 150 Hz and 175 Hz

The spectrum shows the spacing clearly, while the waveform may show the related rise and fall of amplitude. Sidebands are useful evidence of modulation, but their mechanical source must still be confirmed.

FFT settings can change what you see

A spectrum is not independent of its acquisition settings. Poor settings can hide peaks, merge nearby frequencies or display misleading amplitudes.

1. Frequency span or maximum frequency

The selected span must include the frequencies relevant to the suspected condition. A low span may show running-speed components clearly but exclude bearing or gear activity. A very high span can provide inadequate detail at low frequency if the number of spectral lines is unchanged.

2. Spectral lines and resolution

A useful approximation is:

Frequency resolution Δf ≈ frequency span / number of lines

Longer time record → finer frequency resolution

If the span is 1,000 Hz with 800 lines, the line spacing is approximately 1.25 Hz. Two components only 0.5 Hz apart will not be cleanly separated by that setup. To improve frequency resolution, the analyzer normally needs a longer time record.

3. Sampling rate and alias protection

The signal must be sampled fast enough for the selected frequency range. Frequencies above the usable range can fold into the displayed spectrum as false lower-frequency components, a problem called aliasing. Modern analyzers normally use anti-alias filtering, but the analyst must still use a suitable acquisition range and instrument configuration.

4. Window function and leakage

A finite time record rarely begins and ends at perfectly matching points in the vibration cycle. The FFT can then spread energy from a true component into adjacent frequency bins. This is called spectral leakage.

A window function reduces the discontinuity at the record ends. A Hanning window is common for general machinery spectra, while other windows may suit transient or amplitude-accuracy applications. Window choice involves trade-offs; it does not repair an unstable or incorrectly collected signal.

5. Averaging

Averaging several records can stabilize random variation and make repeatable components easier to see. Too much averaging can hide short-lived events. Select the averaging method and number of averages to match the machine behaviour and diagnostic question.

Orders versus hertz

Hertz is absolute frequency. Order is frequency divided by a selected reference speed.

At 1,500 rpm, 25 Hz is 1X. If speed changes to 1,800 rpm, 1X becomes 30 Hz. The physical shaft-related event remains once per revolution even though its frequency in hertz changes.

Order-based analysis is especially useful when speed varies. It helps distinguish components tied to rotational speed from frequencies that remain fixed. Accurate speed information from a tachometer, keyphasor or reliable speed measurement becomes essential.

A practical reading sequence

1. Confirm data quality. Check the point, direction, sensor mounting, units, range, overload status, speed and load.
2. Read the waveform first. Look for periodicity, impacts, modulation, clipping, beats and changes during the record.
3. Calculate known frequencies. Include shaft speeds, gear mesh, blade or vane pass and available bearing frequencies.
4. Read the spectrum. Identify dominant peaks, harmonics, subharmonics, sidebands and broadband regions.
5. Match frequencies to the machine. Use measured speed and actual component geometry, not guesswork.
6. Compare locations and directions. Horizontal, vertical and axial responses help test a hypothesis.
7. Compare with history. Trend amplitudes and patterns under similar operating conditions.
8. Seek confirmation. Use phase, high-resolution data, envelope analysis, temperature, oil analysis, process data or inspection as appropriate.
9. State uncertainty. Separate what the data proves from what it merely suggests.

Five common mistakes

Mistake 1: Diagnosing from the tallest peak

The tallest peak may be important, but amplitude can be influenced by structural response, measurement location, direction and operating condition. Identify the frequency and test the mechanism.

Mistake 2: Assuming every 1X peak means unbalance

Unbalance often produces running-speed vibration, but 1X is not unique to unbalance. Phase, direction, machine geometry and inspection evidence are needed.

Mistake 3: Ignoring the time waveform

A spectrum can make frequencies clear while hiding impact shape and timing. Always inspect the waveform when impacts, looseness, rubs or modulation are possible.

Mistake 4: Comparing spectra with different settings

Changes in span, lines, window, averaging, units or operating condition can change the display. Trend like with like.

Mistake 5: Trusting software labels without verification

Software can calculate peaks, orders and alarms quickly. It does not know every change in machine configuration, process condition, sensor installation or maintenance history. The analyst remains responsible for validation.

Final takeaway

The waveform and spectrum are two views of the same vibration signal.

• The time waveform preserves timing, shape and transient behaviour.
• The FFT spectrum separates repeating components by frequency.
• Running speed and machine geometry give peaks physical meaning.
• Acquisition settings determine what can be seen and resolved.
• A familiar pattern is evidence, not proof.

A good analyst does not ask, "Which plot gives the answer?" The better question is, "What does each view reveal, and what additional evidence will confirm the hypothesis?"

Coming in Part 5

Part 5: From Spectral Peaks to Fault Hypotheses. We will examine how unbalance, misalignment and mechanical looseness can influence 1X, 2X, harmonics, direction and phase - and how to distinguish a plausible pattern from a confirmed diagnosis.

Discussion question: When diagnosing a difficult machine problem, which view has helped you more - the time waveform or the FFT spectrum - and why?

References and further learning

• SKF, Spectrum Analysis, guidance on identifying and trending component frequencies in machinery FFT spectra.
• Bently Nevada, Vibration and Dynamic Measurements, examples of waveforms, spectra, 1X components and phase references.
• Fluke, What Is Vibration Analysis? A Complete Guide, overview of time-waveform and FFT analysis.
• Fluke, Vibration Spectrum Analysis versus Overall Vibration Analysis, explanation of time-domain collection and FFT conversion.

Educational note: The examples are simplified for learning and d

From Mechanical Maintenance to Vibration Analysis - Part 4

In Part 3 - Displacement, Velocity and Acceleration, we learned that the measurement quantity changes which part of a vibration signal is emphasized.

Now we move to the two plots an analyst uses most often:

The time waveform shows what the vibration did over time. The FFT spectrum shows how that vibration is distributed across frequency.

They are not two unrelated measurements. The spectrum is calculated from the sampled time waveform. Each view organizes the same signal differently, and each can reveal evidence that is difficult to see in the other.

Start with the time waveform

A time waveform plots:

• Amplitude on the vertical axis - displacement, velocity or acceleration; and
• Time on the horizontal axis - normally seconds or milliseconds.

The waveform answers questions such as:

• Is the motion smooth and repeating?
• Are there impacts, clipping, beats or modulation?
• How far apart are repeated events?
• Is the signal symmetrical?
• Does the vibration change during the record?

A clean sinusoidal waveform suggests that one frequency dominates. A complex machine waveform usually contains several vibration sources at the same time: shaft rotation, coupling forces, gears, bearings, blades, hydraulic activity, structural response and background noise.

Period and frequency

If a feature repeats every T seconds, its frequency is:

Frequency (Hz) = 1 / period (seconds)

Running frequency (Hz) = speed (rpm) / 60

For a motor running at 1,500 rpm:

1,500 / 60 = 25 Hz

One shaft revolution therefore takes:

1 / 25 = 0.04 seconds, or 40 milliseconds

If a waveform contains a strong event every 40 ms, the repetition rate is synchronous with running speed. That is useful evidence, but it does not by itself prove unbalance or any other single fault.

What the FFT spectrum does

The Fast Fourier Transform, or FFT, is a mathematical method that separates a sampled waveform into frequency components. The resulting spectrum normally plots:

• Amplitude on the vertical axis; and
• Frequency on the horizontal axis, commonly in hertz, cycles per minute or orders.

Instead of asking when an event happened, the spectrum helps us ask:

• Which frequencies contain the most vibration?
• Do peaks correspond with shaft speed or component frequencies?
• Are harmonics or sidebands present?
• Which peaks are changing over time?

A spectrum makes repeating components easier to separate. However, it removes much of the timing shape that can make impacts, modulation and transient behaviour obvious in the waveform.

Time waveform versus FFT spectrum

Question	Time waveform	FFT spectrum
Horizontal axis	Time	Frequency or order
Especially useful for	Impacts, beats, modulation, clipping, non-stationary events and waveform shape	Separating periodic components, identifying orders, harmonics, sidebands and component-related frequencies
What may be hidden	Closely spaced frequency components can overlap visually	The timing and shape of individual events can be difficult to recognize
Best practice	Review both views with the same units, point, direction, speed, load and acquisition settings.

Understanding 1X, 2X and harmonics

Analysts often express frequency as a multiple of shaft-running speed:

• 1X means once per shaft revolution.
• 2X means twice per shaft revolution.
• 3X means three times per shaft revolution.

For the 1,500 rpm motor:

• 1X = 25 Hz
• 2X = 50 Hz
• 3X = 75 Hz
• 4X = 100 Hz

Integer multiples of a fundamental frequency are called harmonics. A series at 1X, 2X, 3X and higher orders tells us that the waveform contains repeating non-sinusoidal content related to shaft rotation.

A harmonic family is a pattern, not a diagnosis. Several conditions can generate harmonics, and the same fault can look different on different machines.

Before attaching a fault name, compare the pattern with measurement direction, phase, machine construction, clearances, operating condition, history and physical inspection.

Worked motor-pump example

Consider a direct-coupled motor and centrifugal pump running steadily at 1,500 rpm. The pump impeller has six vanes.

1. Running speed: 1,500 / 60 = 25 Hz.
2. Shaft period: 1 / 25 = 0.04 s.
3. Vane-pass frequency: 6 vanes × 25 Hz = 150 Hz, or 6X.

Suppose the spectrum contains peaks at 25, 50 and 150 Hz.

• The 25 Hz peak is synchronous with shaft rotation.
• The 50 Hz peak is 2X running speed.
• The 150 Hz peak matches the calculated vane-pass frequency.

Those identities are defensible because they are based on measured speed and machine geometry. The cause still requires testing.

For example, a 1X peak could be influenced by unbalance, bent shaft, eccentricity, resonance, transmitted vibration or other mechanisms. A vane-pass peak may be influenced by normal hydraulic excitation, operating away from the best efficiency point, recirculation, clearance problems or structural amplification. The frequency tells us where to investigate; it does not complete the diagnosis.

What the waveform adds

If the waveform is smooth and repeats every 40 ms, shaft-synchronous motion may dominate. If sharp impacts repeat at the same interval, looseness, contact or another once-per-revolution event may be exciting a resonance. If the amplitude rises and falls in a regular envelope, modulation or beating may be present.

This is why the analyst should move between waveform and spectrum instead of relying on one display.

Sidebands and modulation

Sidebands are peaks spaced equally around a central frequency. Their spacing is important because it can identify the modulating frequency.

For example, peaks around 150 Hz separated by 25 Hz would be described as 1X sidebands around the vane-pass frequency:

125 Hz, 150 Hz and 175 Hz

The spectrum shows the spacing clearly, while the waveform may show the related rise and fall of amplitude. Sidebands are useful evidence of modulation, but their mechanical source must still be confirmed.

FFT settings can change what you see

A spectrum is not independent of its acquisition settings. Poor settings can hide peaks, merge nearby frequencies or display misleading amplitudes.

1. Frequency span or maximum frequency

The selected span must include the frequencies relevant to the suspected condition. A low span may show running-speed components clearly but exclude bearing or gear activity. A very high span can provide inadequate detail at low frequency if the number of spectral lines is unchanged.

2. Spectral lines and resolution

A useful approximation is:

Frequency resolution Δf ≈ frequency span / number of lines

Longer time record → finer frequency resolution

If the span is 1,000 Hz with 800 lines, the line spacing is approximately 1.25 Hz. Two components only 0.5 Hz apart will not be cleanly separated by that setup. To improve frequency resolution, the analyzer normally needs a longer time record.

3. Sampling rate and alias protection

The signal must be sampled fast enough for the selected frequency range. Frequencies above the usable range can fold into the displayed spectrum as false lower-frequency components, a problem called aliasing. Modern analyzers normally use anti-alias filtering, but the analyst must still use a suitable acquisition range and instrument configuration.

4. Window function and leakage

A finite time record rarely begins and ends at perfectly matching points in the vibration cycle. The FFT can then spread energy from a true component into adjacent frequency bins. This is called spectral leakage.

A window function reduces the discontinuity at the record ends. A Hanning window is common for general machinery spectra, while other windows may suit transient or amplitude-accuracy applications. Window choice involves trade-offs; it does not repair an unstable or incorrectly collected signal.

5. Averaging

Averaging several records can stabilize random variation and make repeatable components easier to see. Too much averaging can hide short-lived events. Select the averaging method and number of averages to match the machine behaviour and diagnostic question.

Orders versus hertz

Hertz is absolute frequency. Order is frequency divided by a selected reference speed.

At 1,500 rpm, 25 Hz is 1X. If speed changes to 1,800 rpm, 1X becomes 30 Hz. The physical shaft-related event remains once per revolution even though its frequency in hertz changes.

Order-based analysis is especially useful when speed varies. It helps distinguish components tied to rotational speed from frequencies that remain fixed. Accurate speed information from a tachometer, keyphasor or reliable speed measurement becomes essential.

A practical reading sequence

1. Confirm data quality. Check the point, direction, sensor mounting, units, range, overload status, speed and load.
2. Read the waveform first. Look for periodicity, impacts, modulation, clipping, beats and changes during the record.
3. Calculate known frequencies. Include shaft speeds, gear mesh, blade or vane pass and available bearing frequencies.
4. Read the spectrum. Identify dominant peaks, harmonics, subharmonics, sidebands and broadband regions.
5. Match frequencies to the machine. Use measured speed and actual component geometry, not guesswork.
6. Compare locations and directions. Horizontal, vertical and axial responses help test a hypothesis.
7. Compare with history. Trend amplitudes and patterns under similar operating conditions.
8. Seek confirmation. Use phase, high-resolution data, envelope analysis, temperature, oil analysis, process data or inspection as appropriate.
9. State uncertainty. Separate what the data proves from what it merely suggests.

Five common mistakes

Mistake 1: Diagnosing from the tallest peak

The tallest peak may be important, but amplitude can be influenced by structural response, measurement location, direction and operating condition. Identify the frequency and test the mechanism.

Mistake 2: Assuming every 1X peak means unbalance

Unbalance often produces running-speed vibration, but 1X is not unique to unbalance. Phase, direction, machine geometry and inspection evidence are needed.

Mistake 3: Ignoring the time waveform

A spectrum can make frequencies clear while hiding impact shape and timing. Always inspect the waveform when impacts, looseness, rubs or modulation are possible.

Mistake 4: Comparing spectra with different settings

Changes in span, lines, window, averaging, units or operating condition can change the display. Trend like with like.

Mistake 5: Trusting software labels without verification

Software can calculate peaks, orders and alarms quickly. It does not know every change in machine configuration, process condition, sensor installation or maintenance history. The analyst remains responsible for validation.

Final takeaway

The waveform and spectrum are two views of the same vibration signal.

• The time waveform preserves timing, shape and transient behaviour.
• The FFT spectrum separates repeating components by frequency.
• Running speed and machine geometry give peaks physical meaning.
• Acquisition settings determine what can be seen and resolved.
• A familiar pattern is evidence, not proof.

A good analyst does not ask, "Which plot gives the answer?" The better question is, "What does each view reveal, and what additional evidence will confirm the hypothesis?"

Coming in Part 5

Part 5: From Spectral Peaks to Fault Hypotheses. We will examine how unbalance, misalignment and mechanical looseness can influence 1X, 2X, harmonics, direction and phase - and how to distinguish a plausible pattern from a confirmed diagnosis.

Discussion question: When diagnosing a difficult machine problem, which view has helped you more - the time waveform or the FFT spectrum - and why?

References and further learning

• SKF, Spectrum Analysis, guidance on identifying and trending component frequencies in machinery FFT spectra.
• Bently Nevada, Vibration and Dynamic Measurements, examples of waveforms, spectra, 1X components and phase references.
• Fluke, What Is Vibration Analysis? A Complete Guide, overview of time-waveform and FFT analysis.
• Fluke, Vibration Spectrum Analysis versus Overall Vibration Analysis, explanation of time-domain collection and FFT conversion.

Educational note: The examples are simplified for learning and do not establish universal alarm limits or fault rules. Apply approved site criteria, applicable standards, manufacturer guidance and qualified engineering judgement to real machinery.

o not establish universal alarm limits or fault rules. Apply approved site criteria, applicable standards, manufacturer guidance and qualified engineering judgement to real machinery.