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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.

Displacement, Velocity and Acceleration: What Each Vibration Measurement Tells You

From Mechanical Maintenance to Vibration Analysis - Part 3

In Part 2 - From a Measurement to a Maintenance Decision, we followed the complete vibration-analysis workflow: understand the machine, collect repeatable data, validate the measurement, analyse the evidence, recommend an action and verify the result.

Now we address a question every new analyst meets:

Should I measure displacement, velocity or acceleration?

All three describe the same vibrating motion, but they emphasize different parts of the frequency range. Selecting the right quantity can make a machine condition easier to see. Selecting the wrong one can reduce or hide useful evidence.

Begin with one simple motion

Imagine a point on a bearing housing moving back and forth around its normal position:

• Displacement tells us how far the point moves.
• Velocity tells us how fast it moves.
• Acceleration tells us how quickly its velocity changes.

For a simple sinusoidal vibration at frequency f:

Velocity peak = 2 π f × displacement peak

Acceleration peak = 2 π f × velocity peak

Therefore, acceleration peak = (2 π f)² × displacement peak

This relationship explains the main selection principle:

• Displacement emphasizes lower-frequency motion.
• Velocity provides a useful balance across a broad middle-frequency range.
• Acceleration emphasizes higher-frequency activity.

This is not a rule that one quantity is always better than another. The right choice depends on the machine, bearing type, sensor, expected fault, speed and frequency range of interest.

1. Displacement: how far the vibration moves

Displacement is the change in position of the vibrating surface or shaft. Common units include:

• micrometres, or µm;
• millimetres, or mm; and
• mils, where 1 mil equals 0.001 inch.

Displacement is often displayed as peak-to-peak because that value represents the total travel from one extreme of the waveform to the other. Always confirm the convention in the instrument or software; µm peak, µm peak-to-peak and µm RMS are not interchangeable.

Where displacement is especially useful

• Low-frequency vibration and slow movement
• Shaft-relative vibration on machines with fluid-film bearings
• Large turbo-machinery where non-contact proximity probes observe shaft motion relative to the bearing housing
• Clearance-related questions where actual movement matters

A proximity probe measures the changing gap between the probe tip and the shaft. This is a different physical measurement from an accelerometer mounted on the bearing housing. One represents shaft-relative motion; the other normally represents absolute casing vibration. They should not be treated as if they were the same measurement.

Important limitation

As frequency increases, the displacement produced by high-frequency impacts can become extremely small. A developing rolling-element bearing defect may therefore be difficult to recognize in a displacement plot even though it is clear in acceleration or an appropriate demodulated measurement.

2. Velocity: how fast the vibration moves

Velocity is the rate of change of displacement. Common units are:

• millimetres per second, or mm/s; and
• inches per second, or in/s.

Overall casing velocity is frequently displayed as RMS. RMS is useful because it represents the effective energy of a varying signal, but you must still confirm the instrument configuration and frequency band before comparing values.

Where velocity is especially useful

• General condition monitoring of many rotating machines
• Broad assessment of casing vibration over a middle-frequency range
• Common mechanical conditions such as unbalance, misalignment and looseness when their frequencies fall inside the configured measurement band
• Trending overall machine condition under comparable operating states

Velocity does not give every frequency equal importance in every real measurement. Sensor response, integration, filtering and the selected frequency band still matter. However, compared with displacement and acceleration, velocity often provides a practical balance for general machinery monitoring.

Important limitation

An overall velocity value can tell you that vibration energy changed, but it cannot identify the cause by itself. Two machines can have the same overall velocity and completely different spectra. The analyst must review frequency, direction, location, phase, waveform, process condition and machine history.

3. Acceleration: how quickly velocity changes

Acceleration is the rate of change of velocity. Common units include:

• metres per second squared, or m/s²; and
• g, where 1 g is approximately 9.81 m/s².

Industrial accelerometers commonly use piezoelectric sensing elements. They are versatile, robust and capable of measuring a wide frequency range when the sensor, mounting and acquisition settings are suitable.

Where acceleration is especially useful

• Higher-frequency vibration
• Rolling-element bearing impacts
• Gear-mesh activity
• Blade- or vane-related frequencies
• Impulsive events and resonance excited by impacts

Acceleration is also commonly the original signal collected by a portable data collector. The instrument or software may mathematically integrate that signal to display velocity and, in some applications, displacement.

Important limitation

High-frequency acceleration can be sensitive to mounting quality. A hand-held probe, magnet, adhesive pad and stud do not provide identical frequency response. A loose or inconsistent mounting method can distort the very high-frequency information the analyst wants to examine.

A practical comparison table

Quantity	What it describes	Common display units	Often useful for
Displacement	How far the vibration moves	µm peak-to-peak, mils peak-to-peak	Low-frequency motion and shaft-relative vibration
Velocity	How fast the vibration moves	mm/s RMS, in/s peak or RMS	General casing-vibration condition monitoring
Acceleration	How quickly velocity changes	g peak, g RMS, m/s2	High-frequency, bearing, gear and impact-related activity

The entries are starting points, not universal rules. A specific monitoring program must follow the machine design, sensor specifications, applicable standards, original-equipment-manufacturer guidance, site procedures and engineering judgement.

Worked example: the same 1X vibration in three quantities

Consider a motor running at 1,500 rpm:

Frequency = 1,500 / 60 = 25 Hz

Suppose the 1X displacement is 100 µm peak-to-peak. For a simple sinusoid:

1. Displacement peak is half of peak-to-peak: 50 µm, or 0.000050 m.
2. Velocity peak = 2 π × 25 × 0.000050 = 0.00785 m/s, or 7.85 mm/s peak.
3. Velocity RMS = 7.85 / √2 = approximately 5.55 mm/s RMS.
4. Acceleration peak = 2 π × 25 × 0.00785 = approximately 1.23 m/s², or 0.126 g peak.

The motion has not changed. Only the quantity and amplitude convention used to describe it have changed.

Never compare 100 µm peak-to-peak directly with 5.55 mm/s RMS or 0.126 g peak as if they were competing severity numbers. They are different descriptions of the same sinusoidal motion.

Why frequency changes what you see

For the same displacement amplitude, increasing frequency increases velocity in direct proportion to frequency and acceleration in proportion to frequency squared.

This explains why:

• a slow shaft movement may look large in displacement but modest in acceleration;
• a high-frequency bearing impact may look small in displacement but strong in acceleration; and
• velocity often serves as a useful middle ground for general rotating-machine casing vibration.

It also explains why a single overall value cannot cover every failure mode equally well. A monitoring program may need overall velocity, acceleration spectra, bearing-condition measurements and shaft-relative displacement, depending on the asset.

Peak, peak-to-peak and RMS: do not ignore the convention

For a pure sine wave:

• Peak-to-peak = 2 × peak
• RMS = peak / √2

These simple conversions apply exactly to a pure sinusoid. Real machine vibration is usually a combination of frequencies, impacts and noise. Do not convert a broadband overall RMS value to peak or peak-to-peak using the sine-wave factors and assume the result represents the real waveform.

Before comparing readings, confirm all of the following:

• same physical quantity;
• same unit;
• same amplitude convention;
• same frequency band and filtering;
• same sensor and mounting method;
• same measurement point and direction; and
• comparable speed and load.

The sensor and the displayed quantity are not always the same

An accelerometer measures acceleration, but software can integrate its signal once to display velocity and twice to display displacement. This does not mean every converted result is equally reliable.

• Integration can magnify low-frequency noise, drift and sensor-settling effects.
• High-pass filters may remove low-frequency content.
• Sensor mounting and frequency response limit the usable high-frequency range.
• The selected acquisition range and resolution determine what enters the calculation.

Always check the actual sensor, its mounting, the acquisition setup and the displayed engineering units. Software cannot reconstruct information that the sensor and acquisition system did not capture correctly.

A practical selection guide

1. Define the machine and bearing type. A rigid-bearing motor and a fluid-film-bearing turbine do not require identical measurements.
2. Identify the failure mode of interest. Are you looking for slow shaft movement, general mechanical vibration, or high-frequency impacts?
3. Estimate the relevant frequency range. Use running speed, bearing geometry, gear teeth, blade or vane count and known excitation frequencies.
4. Select a suitable sensor and mounting. Confirm its usable frequency and amplitude range.
5. Select the quantity and convention. Record whether the result is displacement, velocity or acceleration and whether it is RMS, peak or peak-to-peak.
6. Trend like with like. Keep the point, direction, operating condition, band and setup consistent.
7. Use more than one view when needed. Combine overall trends with spectra, waveforms and other diagnostic techniques.

Three mistakes new analysts should avoid

Mistake 1: Asking which quantity is best

There is no universal best quantity. Ask which one is most sensitive and meaningful for the machine condition and frequency range being investigated.

Mistake 2: Comparing values without reading the units

A value of 5 can mean 5 mm/s RMS, 5 µm peak-to-peak or 5 g peak. The number alone is meaningless.

Mistake 3: Treating an overall value as a diagnosis

Overall vibration is useful for screening and trending. Diagnosis requires the frequency content, location, direction, time behaviour, operating condition and machine context.

Final takeaway

Displacement, velocity and acceleration are not three unrelated measurements. They are three connected ways of describing vibration.

Displacement answers how far. Velocity answers how fast. Acceleration answers how quickly the velocity changes.

The analyst's job is not to select a familiar unit automatically. It is to match the measurement quantity, sensor, frequency range and amplitude convention to the machine and the suspected condition.

Coming in Part 4

Part 4: Understanding the Time Waveform and FFT Spectrum. We will explain what each plot shows, how frequency relates to machine speed, what 1X and harmonics mean, and why a spectrum pattern should be treated as evidence rather than proof.

Discussion question: Which quantity do you use most often in your plant - displacement, velocity or acceleration - and what type of machine are you monitoring?

References and further learning

• Emerson, Vibration Analysis for Machinery Health Diagnosis, especially the comparison of typical sensors, units and applications.
• SKF, Introduction Guide to Vibration Monitoring, sections on displacement, velocity and acceleration.
• NI, What Is Vibration Monitoring?, sensor and measurement overview.
• Emerson Process Management, Basic Vibration Analysis - Course 2031, measurement-parameter fundamentals.
• Vibration Analysis Guide, beginner sections on amplitude, frequency and measurement quantities.

Educational note: The worked example assumes a pure sinusoidal signal and is intended to demonstrate the mathematical relationship between quantities. It is not a universal alarm limit. Apply approved site criteria, applicable standards, manufacturer guidance and qualified engineering judgement to real machinery.

The Vibration Analysis Workflow: From a Measurement to a Maintenance Decision

From Mechanical Maintenance to Vibration Analysis - Part 2

In Part 1 - You Are Not Starting from Zero, we established that a mechanical maintenance professional is not starting from zero when moving into vibration analysis. Knowledge of machines, failure modes, operating conditions and maintenance history is already part of the diagnostic process.

Now we move to the central question: What should an analyst actually do when new vibration data arrives?

A reliable diagnosis does not begin with selecting a fault from a chart. It begins before the measurement is collected and continues after the maintenance work is completed.

The objective is not to find a pattern that looks familiar. The objective is to build enough reliable evidence to support the right maintenance decision.

The complete workflow at a glance

Stage	Main question	Expected output
1. Understand	What machine and operating state are we assessing?	Asset and operating context
2. Plan	What measurements can reveal the expected failure modes?	Measurement strategy
3. Collect	Was the data collected safely and repeatably?	Traceable measurements and field notes
4. Validate	Is the change real, or could it be bad data?	Accepted or repeated measurement
5. Analyse	What changed, where and at which frequencies?	Defined vibration symptoms
6. Diagnose	Which causes fit all the available evidence?	Ranked fault hypotheses
7. Decide	What action is justified, and how urgent is it?	Risk-based recommendation
8. Verify	Did the action correct the condition?	Confirmed result and updated history

Each stage protects the next one. Excellent analysis cannot rescue unreliable data, and a technically correct diagnosis has little value if the recommendation is unclear or arrives too late.

Stage 1: Understand the machine and its operating context

Before opening a spectrum, establish what you are looking at. Useful questions include:

• What is the asset ID, function and consequence of failure?
• Which driver and driven components form the machine train?
• What are the running speeds, gear ratios, blade or vane counts and bearing types?
• How are the components coupled and supported?
• Is the machine fixed-speed or variable-speed?
• What load, flow, pressure, temperature or production state is normal?
• What maintenance was recently performed?
• Which failure modes are credible for this design and service?

This information turns frequency peaks into mechanical possibilities. For example, a peak at 25 Hz has little meaning by itself. If the shaft is running at 1,500 rpm, 25 Hz is running speed, or 1X. If the machine is running at 750 rpm, that same peak is 2X. Context changes the interpretation.

Stage 2: Plan measurements around the machine

Do not collect every possible measurement without purpose. Select points, directions, transducers and acquisition settings that can reveal the expected behaviour of the asset.

A basic route on a horizontal motor-pump set often includes measurements near the bearings in horizontal, vertical and axial directions. However, the correct plan depends on the machine, bearing type, casing, speed, accessibility and suspected fault.

The plan should define:

• measurement-point names and exact physical locations;
• sensor type and mounting method;
• measurement direction;
• units and amplitude convention;
• frequency range, resolution and other acquisition settings;
• expected operating state; and
• required process values and field observations.

Route consistency matters because condition monitoring depends on comparing the present with the past. If the point, orientation, mounting or operating state changes, the vibration may change even when the machine condition has not.

Stage 3: Collect safe, repeatable data

Repeatability means reducing unnecessary differences between one measurement and the next. Use the same marked point, direction, sensor, mounting method and suitable operating condition whenever practical.

Before taking a reading:

1. Follow site safety requirements and confirm that the measurement can be taken without exposure to rotating, hot, pressurized or energized hazards.
2. Confirm the correct asset and measurement point.
3. Check that the machine is running in the intended operating state.
4. Inspect the sensor, cable, connector and mounting surface.
5. Mount the sensor firmly and in the correct direction.
6. Allow the signal to stabilize and check whether the reading appears reasonable.
7. Record useful observations before leaving the machine.

Field observations can be diagnostically valuable. Note leaking seals, loose guards, damaged bases, unusual noise, product buildup, oil on the floor, recent maintenance and comments from operators. The person collecting data is not merely carrying an instrument; that person is also gathering context.

Stage 4: Validate the measurement before diagnosing the machine

When a value changes sharply, first ask whether the machine changed or the measurement changed.

Possible data problem	Basic validation action
Loose, tilted or inconsistent sensor mounting	Remount at the marked point and repeat the reading.
Wrong point or direction	Check the route definition, point label and orientation.
Different speed or load	Record the state and compare with data from a similar condition.
Damaged cable or poor connector	Inspect the setup and compare with a known-good sensor or cable where permitted.
Incorrect acquisition setup	Confirm units, frequency range, resolution and sensor configuration.
Transient process event	Check process trends and repeat under a stable condition if appropriate.

A repeated high reading does not prove a specific fault, but it gives more confidence that the condition is real.

Stage 5: Analyse the evidence in a logical order

Many analysts begin with the alarm list or exception report, but an alarm is a screening device, not a diagnosis. Analyse the alerted point in context.

1. Review the trend

Determine when the change began, how quickly it developed and whether it correlates with maintenance or operating changes. A gradual rise over months suggests a different investigation from a step change immediately after overhaul.

2. Compare related points and directions

Identify where vibration is strongest and how it travels through the machine. Compare driver and driven components, inboard and outboard bearings, and radial and axial directions. Spatial distribution is part of the fault pattern.

3. Review the spectrum

Identify the dominant frequencies and relate them to running speed, harmonics and known machine components. Look for changes in amplitude, new peaks, sidebands, broadband energy and high-frequency content.

4. Review the time waveform where useful

The waveform can reveal impacts, modulation, clipping, looseness and non-steady behaviour that may not be obvious from the spectrum alone.

5. Use additional plots and techniques when justified

Phase, enveloping or demodulation, orbits, shaft centerline, run-up or coast-down data and other techniques can help answer specific questions. Use them because the investigation requires them, not simply because the software offers them.

Overall vibration tells you that energy changed. Frequency, time, phase, location and operating context help explain why.

Stage 6: Build and test fault hypotheses

A diagnosis is stronger when the analyst considers competing explanations. Instead of saying, "There is a 1X peak, therefore the rotor is unbalanced," write a short hypothesis table.

Possible cause	Evidence that would support it	Useful confirmation
Mass unbalance	Dominant 1X response, commonly strongest radially, with behaviour consistent with the rotor and support.	Phase and spatial pattern; inspect for buildup, damage or missing material.
Misalignment	Vibration pattern across the coupling, often with axial and harmonic content depending on the case.	Phase relationship, coupling inspection and alignment check.
Mechanical looseness	Harmonics, nonlinearity, impacts or localized response consistent with a loose interface.	Inspect hold-down bolts, base, bearing fits, guards and structural joints.
Hydraulic excitation	Vibration changes with flow or pressure and may include vane-related or broadband components.	Compare process state, listen for cavitation and review pump operation.

No single row is a universal rule. Machine construction and operating behaviour can alter the pattern. The purpose of the table is to make your reasoning visible and testable.

Stage 7: Convert analysis into a maintenance decision

A useful report answers five questions:

1. Where? Identify the asset and measurement location.
2. What changed? Describe the trend and relevant vibration symptoms.
3. What is the probable condition? State the diagnosis with an appropriate confidence level.
4. What should be done? Recommend inspection, further testing, monitoring or corrective work.
5. When? State urgency based on trend, severity, failure consequence and local criteria.

Avoid vague reports such as "high vibration - check machine." A stronger report might say:

Pump P-204 drive-end horizontal velocity increased from 2.1 to 5.8 mm/s RMS over three weekly measurements under comparable speed and load. The spectrum is dominated by 1X running speed, with the highest response on the pump. The pattern is consistent with probable impeller unbalance. Inspect the impeller for buildup or damage and check base tightness during the next planned opportunity. Continue weekly monitoring and escalate sooner if the trend accelerates or operating behaviour changes.

The severity and timing in a real report must follow the organization's approved alarm philosophy, applicable guidance, machine history, operating risk and engineering judgement. A numerical value should not be copied into a universal action rule without context.

Stage 8: Verify the result and preserve the lesson

After maintenance, collect data under a comparable operating condition. Compare before and after values, spectra, waveforms and process conditions. Record what the maintenance team found and what action was actually performed.

If the vibration falls and the suspected defect is physically confirmed, confidence in the diagnosis increases. If the vibration remains high, do not hide the result. Reassess the hypothesis, measurement and repair quality.

Verification converts an isolated diagnosis into organizational knowledge. It improves future alarm decisions, reports, fault recognition and maintenance planning.

Practical case: a pump with rising 1X vibration

Consider a simplified training example involving a motor-driven centrifugal pump operating at approximately 1,480 rpm, or 24.7 Hz.

1. Understand: The pump normally operates at stable speed and similar flow. The impeller handles a product that can accumulate deposits.
2. Collect: Weekly readings are taken at marked bearing locations using the same sensor and mounting method. Speed, flow and pressure are recorded.
3. Detect: Pump drive-end horizontal velocity rises from 2.1 to 5.8 mm/s RMS over three comparable measurements.
4. Validate: The analyst remounts the sensor, repeats the measurement and checks the nearby points. The increase remains.
5. Analyse: The spectrum is dominated by 24.7 Hz, matching running speed. The response is strongest radially on the pump. The time waveform is mainly periodic, and bearing-condition indicators have not changed significantly.
6. Hypothesize: Impeller unbalance is considered probable, but looseness, support problems and hydraulic effects are also reviewed.
7. Confirm: Hold-down bolts and the base show no obvious looseness. Process conditions are stable. The team plans an impeller inspection.
8. Act: Deposits are found and removed from the impeller. Its condition is checked before the pump is returned to service.
9. Verify: Under a comparable operating condition, vibration falls to 2.2 mm/s RMS and the 1X component reduces substantially.

The lesson is not that every 1X peak means impeller buildup. The lesson is that a diagnosis becomes credible when measurement quality, machine context, pattern, inspection and post-maintenance response agree.

A field checklist for new analysts

• Correct asset and point confirmed
• Safe access and site requirements satisfied
• Speed and operating state recorded
• Sensor, mounting and direction verified
• Measurement repeated if the result is unusual
• Field observations and recent work recorded
• Trend reviewed before isolated plots
• Related points and directions compared
• More than one possible cause considered
• Recommendation states action and urgency
• Post-maintenance verification requested

Final takeaway

Vibration analysis is not a contest to name a fault quickly. It is a disciplined process for reducing uncertainty.

Understand the machine. Plan the measurement. Collect repeatable data. Validate the result. Define the symptoms. Test competing explanations. Communicate the decision clearly. Then verify what happened.

When these steps become habitual, software changes from a collection of plots into a tool for making better maintenance decisions.

Coming in Part 3

Part 3: Displacement, Velocity and Acceleration - What Each Measurement Tells You. We will explain the three common vibration quantities, their units, where each is useful and why selecting the wrong measurement can hide an important machine condition.

Discussion question: Which step of the workflow is most often missed in your workplace - measurement validation, diagnosis confirmation, clear reporting or post-maintenance verification?

References and further learning

• Mobius Institute, Vibration Analysis Category I training material, especially Chapter 4 topics on data acquisition, repeatability, field observations, routes and the start of the analysis process.
• Emerson Process Management, Basic Vibration Analysis - Course 2031, especially the introduction to vibration, measurement parameters, spectra and monitoring fundamentals.
• Vibration Analysis Guide, especially the beginner sections on amplitude, frequency, waveforms and spectra.
• Mobius Institute, Vibration Analysis Faults booklet, used as a fault-pattern reference.

Educational note: The numerical values and pump case in this article are simplified examples, not universal alarm limits. Apply site procedures, approved alarm criteria, equipment-manufacturer guidance and qualified engineering judgement to real machinery.