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Vibration and thermal measurements improve predictive maintenance when they are tied to a specific machine, its operating conditions, a healthy baseline, and an action plan. Vibration is especially useful for rotating equipment; bearing-temperature monitoring and infrared thermography provide complementary evidence of developing problems. Neither a sensor nor a single alarm reading predicts failure by itself.
What vibration and thermal sensing can reveal
Predictive maintenance is the monitoring, trending, and analysis of equipment signatures that can show a declining ability to perform its intended function. That is the approach described in U.S. Department of Energy guidance, which identifies vibration analysis, bearing-temperature monitoring, and infrared surveys as examples of condition-monitoring methods.
Vibration: mechanical changes in rotating equipment
Vibration measurements are particularly relevant to rotating machinery, including generators, turbines, pumps, and electric motors. A change in a machine’s vibration signature can prompt investigation of a developing mechanical problem. The measurement is a symptom, not a diagnosis: interpretation depends on the machine, where and how the measurement was taken, and what the equipment was doing at the time.
Temperature: heat at a bearing or across a surface
Bearing-temperature monitoring provides thermal evidence at a specific component. Infrared thermography surveys surface temperatures without relying on a single contact point, and DOE guidance describes its use on motors, circuit breakers, batteries, load centers, and insulated areas to identify signs such as high resistance or insulation breakdown.
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These methods answer different questions. A vibration reading characterizes mechanical movement; a temperature reading or infrared image shows heat. A thermal anomaly may justify investigation, but temperature alone does not establish its cause. Likewise, a vibration deviation needs diagnosis before it can support a maintenance decision.
Vibration analysis or thermal imaging?
Choose based on the equipment, likely failure modes, and practical measurement conditions. ISO 17359:2018 includes both vibration and temperature among condition-monitoring parameters, and DOE guidance maps vibration monitoring, bearing temperatures, and infrared thermography to generators, turbines, pumps, motors, and electrical equipment.
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| Consideration | Vibration monitoring | Bearing-temperature monitoring | Infrared thermography |
|---|---|---|---|
| What it measures | Machine vibration signatures | Temperature at a bearing or other instrumented point | Surface-temperature patterns across an inspected area |
| Where it is most useful | Especially useful for rotating equipment | Bearings and other selected components where temperature is a relevant symptom | Motors, electrical equipment, batteries, load centers, and insulated areas, among other DOE examples |
| Placement or access | Requires repeatable measurement locations on the machine | Requires a sensor at the component or location being monitored | Requires a view of the surface being surveyed |
| Operating context | Readings need to be interpreted in relation to operating conditions | Readings need context, including the component and conditions during measurement | Surface patterns need context about the equipment and conditions during the survey |
| Monitoring approach | Use a suitable interval or acquisition rate for the asset and the monitoring plan | Use an interval suited to the asset and the monitoring plan | Use repeat surveys or an appropriate inspection plan; the interval depends on the asset and its risk |
| Alarm and diagnosis | Machine-specific criteria and trends are more useful than treating one vibration level as a universal failure limit | Interpret against the component’s baseline and conditions; one reading is not a universal failure limit | Interpret observed patterns against baseline and operating context; an image alone does not prove root cause |
| Installation and integration | Depends on measurement method, locations, acquisition needs, and how results reach maintenance staff | Depends on sensor placement and how readings are collected and reviewed | Can be used for surveys; integrating findings requires a repeatable record and maintenance follow-up |
The comparison is qualitative: the cited guidance does not establish a universal accuracy ranking, temperature or frequency range, cost, or failure-reduction percentage for these methods. A program should evaluate feasibility, measurement accuracy, acquisition needs, and cost for the machines it actually monitors.
What sensors do you need?
Do not start by buying a sensor for every asset. Start with criticality and likely failure modes, then select the measurement that can reveal a relevant symptom at a practical location and interval. ISO 17359:2018 treats measurement technique, accuracy, feasibility, operating conditions, monitoring interval, data-acquisition rate, locations, alarm criteria, and baseline data as program considerations.
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- Rotating equipment: consider vibration monitoring, with bearing-temperature monitoring or infrared surveys where heat is also a relevant symptom.
- Electrical equipment: consider infrared thermography for surface patterns that may indicate high resistance or insulation breakdown, as described in DOE guidance.
- Components with a specific thermal concern: use bearing-temperature or other point-temperature monitoring when the selected location and measurement method fit the suspected degradation.
- Lower-priority or hard-to-access assets: weigh the consequences of missed degradation against sensor installation, access, measurement frequency, and the ability to act on findings.
The sensor plan should specify the asset and component, measurement location, operating conditions, interval or acquisition rate, expected data quality, and who reviews the result. A platform can organize and trend measurements, but it cannot make poor placement, missing operating context, or an unclear maintenance response reliable.
How to build a condition-monitoring program
ISO 17359:2018 describes general procedures for setting up a condition-monitoring program for machines. The following sequence turns that guidance into an operational plan:
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- Rank assets by criticality. Consider the consequences of failure, including safety, production, equipment damage, and the available recovery options. Focus monitoring effort where timely warning could change a maintenance decision.
- Identify likely failure modes and measurable symptoms. Decide what degradation matters for each asset and whether vibration, temperature, or another condition parameter can provide relevant evidence.
- Select the method and measurement plan. Define the sensor or survey method, location, measurement accuracy needs, operating conditions, monitoring interval, and data-acquisition rate. Check that the method is feasible for the machine and site.
- Capture a healthy baseline. Record measurements when the machine’s condition is known to be acceptable, together with enough operating context to make later comparisons meaningful. A baseline helps distinguish change from normal variation.
- Set initial alert and alarm criteria. Use relevant history, data from comparable machines, applicable standards, and vendor recommendations. Set criteria for the specific machine and measurement—not a universal limit applied indiscriminately.
- Trend readings and check data quality. Review changes over time and confirm measurements are comparable. Check location, method, operating context, and whether missing or inconsistent data could distort the trend.
- Investigate deviations and define action. Use the condition data to trigger diagnosis and determine an appropriate response, such as inspection, further measurements, or planned maintenance. Document the finding and reasoning.
- Re-baseline after corrective work and review the program. Confirm the post-work condition, update the baseline where justified, and review whether locations, intervals, criteria, and actions remain useful.
NIST describes ISO 17359 as a starting point for prognostics and health management (PHM) systems. Its PHM work also emphasizes reference datasets, use cases, and test scenarios for sensing, diagnostics, prognostics, and control. That framing is useful when a plant is moving beyond isolated readings toward a broader system: sensing supplies data, diagnostics interprets it, and maintenance or operational decisions must follow.
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Alarm criteria should tell staff when a measurement warrants attention, not claim that a machine will fail at a universally fixed value. DOE’s 2001 guide states that vibration monitoring is not an exact science and recommends greater emphasis on observed trends than on a vibration level at one time. It advises using historical data from comparable equipment and relevant standards or vendor recommendations for machine-specific limits.
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- Keep alert and alarm criteria asset-specific. Define them for the equipment, component, location, measurement method, and operating context.
- Use a baseline and trend. Compare repeatable measurements with the machine’s known healthy condition and evaluate whether the change persists or develops over time.
- Make the criterion actionable. State who reviews an alert, what checks or diagnosis follow, and what findings justify maintenance. A threshold without an assigned response is not a complete control.
- Check the measurement before acting on it. Confirm the location, conditions, method, and data quality, especially when a reading differs sharply from the trend.
- Review criteria after experience or repair. Use verified findings and post-maintenance data to improve thresholds and reset a baseline only when the machine’s condition warrants it.
There is no single vibration or temperature value in the cited guidance that can serve as a universal failure limit for every machine. The criteria must fit the asset and be interpreted with trend, operating context, and diagnosis.
Turn a reading into a maintenance decision
A sensor provides evidence; it does not replace inspection, engineering judgment, or root-cause analysis. When a reading crosses a criterion or departs from its expected trend, verify the measurement and the machine’s operating state, then investigate the likely cause before selecting work. Record the diagnosis, action, and outcome so future readings can be assessed against actual machine history.
For a formal framework, the physical product phrase with the clearest evidence is the ISO 17359:2018 condition monitoring and diagnostics of machines standard. ISO’s record identifies the 2018 publication as its third edition and states that it was confirmed current in 2023; the record lists paper and PDF + ePub formats. That confirmation date should not be read as proof of a later status update.
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