Condition Monitoring Systems

What a Condition Monitoring System Is

A condition monitoring system (CMS) is an integrated set of sensors, data acquisition hardware, and analysis software that measures the physical state of operating machinery and reports whether that state is healthy, degrading, or close to failure. Per ISO 17359, the parameters typically tracked include vibration, temperature, lubricant and wear-debris condition, flow, contamination, electrical power, and rotational speed. The system does not merely log numbers: a complete CMS compares each measurement against expected values and acceptance limits, raises alarms, and where prognostics are implemented, estimates the time remaining before the machine can no longer perform its function.

The purpose of condition monitoring is to enable a specific maintenance strategy. Three broad strategies exist. Reactive or run-to-failure maintenance fixes equipment only after it breaks, which is acceptable only for low-criticality assets with short, cheap repairs. Preventive maintenance services equipment on a fixed time or running-hours schedule regardless of actual condition, which wastes life on healthy components and still misses random failures. Condition-based maintenance, the strategy a CMS enables, intervenes only when measured evidence shows a developing fault, capturing most of the remaining useful life while still avoiding unplanned breakdown.

The intellectual core of the field is the P-F curve, a model from Reliability-Centred Maintenance. As a fault develops, machine condition degrades along a curve. Point P is the potential failure: the earliest moment the developing fault becomes detectable by a chosen technique. Point F is the functional failure: the moment the machine can no longer do its job. The interval between them, the P-F interval, is the window in which condition monitoring must both detect the fault and trigger a response. Vibration and ultrasound usually reach point P weeks or months before heat or audible noise, which is exactly why those techniques sit at the front of a monitoring program.

The discipline matured alongside the instruments. Mechanical vibration severity charts, the ancestors of today's ISO 20816 zones, were codified from the 1960s. Eddy-current proximity probes for measuring shaft motion inside fluid-film bearings on turbomachinery were commercialised by Bently Nevada and shaped API 670, the petroleum industry protection standard. Piezoelectric accelerometers with integral electronics, the IEPE or ICP class, made wired vibration sensing cheap and robust. From the late 1990s the ISO 13374 and OSA-CBM work standardised the software architecture, and the 2010s added wireless triaxial sensors, edge analytics, and cloud reliability platforms that pushed condition monitoring down from critical turbomachinery to ordinary motors, pumps, and fans.

The scale of the problem explains the investment. Rotating machinery, motors, pumps, compressors, fans, gearboxes, and turbines, makes up the bulk of industrial mechanical assets, and unplanned downtime on a single critical train in oil and gas, power generation, or process chemicals can cost far more per day than an entire monitoring system. A CMS is therefore evaluated not on sensor price but on the avoided cost of the failures it catches inside the P-F interval, the same total-cost-of-ownership logic that governs every other instrument purchase.

Condition Monitoring Techniques

No single measurement detects every failure mode, so a mature program layers several complementary techniques. The five mainstream methods are vibration analysis, infrared thermography, oil and wear-debris analysis, acoustic emission and airborne ultrasound, and motor current signature analysis. Each has its own best-fit fault types, lead time, and cost profile. The table below compares the core engineering trade-offs.

Vibration analysis is the default technique for rotating machinery and detects the widest range of mechanical faults. An accelerometer mounted on the bearing housing senses the machine's oscillation, which is then analysed as an overall velocity value in mm/s RMS and as a frequency spectrum. The spectrum is diagnostic: imbalance shows at one times running speed, misalignment at one and two times, looseness as harmonics, and bearing defects at characteristic non-synchronous frequencies. Envelope or demodulation techniques, including Emerson's PeakVue, isolate the high-frequency impacts of early bearing damage from the larger low-frequency machine vibration.

Infrared thermography images surface temperature and is the fastest screening tool for electrical panels, where a loose or corroded connection runs hot before it fails, and for confirming mechanical friction, blocked cooling passages, or lubrication starvation. It is non-contact and covers large areas quickly, but it sees only the surface and gives less fault-specific diagnosis than vibration. Oil and debris analysis acts as a blood test for lubricated machinery: laboratory or inline testing reports viscosity, additive depletion, water and particle contamination, and microscopic wear metals that reveal which component is shedding material. Contamination is graded against the ISO 4406 cleanliness code, a three-number designation such as 18/16/13 counting particles at the 4, 6, and 14 micron thresholds per millilitre.

Acoustic emission and airborne ultrasound detect the high-frequency stress waves released by crack initiation, early bearing contact, and turbulent leaks, often catching a fault earlier than vibration on slow-speed assets. Airborne ultrasound also locates compressed-air and steam-trap leaks and partial-discharge activity in switchgear. Motor current signature analysis (MCSA) is a non-intrusive electrical method that diagnoses AC motor health from the supply current spectrum measured at the motor control centre, catching broken rotor bars, stator winding faults, and air-gap eccentricity that vibration can miss. Because the techniques fill each other's gaps, a critical asset is often instrumented with vibration plus temperature as a baseline, with oil analysis and MCSA added where the failure modes warrant it.

The techniques also differ in how much lead time, and therefore how long a P-F interval, they provide for the same fault. On a developing rolling-element bearing defect, ultrasound and high-frequency envelope vibration typically reach the detectable point P first, followed by spectral vibration, then a rise in lubricant wear metals, then bulk temperature, and finally audible noise just before functional failure. A program that relies only on temperature or audible inspection is therefore detecting late, near the end of the P-F interval, with little time to plan a repair. This ordering is why vibration and ultrasound anchor most rotating-machinery programs and why temperature is treated as a confirming rather than a leading indicator.

ISO 13374 Functional Architecture

A condition monitoring system is more than its sensors. The software stack that turns raw signals into a maintenance recommendation is standardised by ISO 13374, which defines an open, vendor-neutral functional architecture so that hardware and software from different makers can interoperate. ISO 13374 is implemented in practice by OSA-CBM, the Open System Architecture for Condition-Based Maintenance maintained by MIMOSA, which adds the concrete data structures and interface methods. The architecture is organised as six functional blocks that pass data upward from raw measurement to actionable advice.

Data acquisition is the entry point: it provides access to the installed transducers and collects time-domain and scalar data at the required sample rate and resolution. Data manipulation performs single and multi-channel signal transformations such as the Fast Fourier Transform, order tracking, and envelope demodulation, and extracts the features that later blocks judge. State detection conducts the actual condition monitoring by comparing those features against expected values or operational limits and returning condition indicators and alarms; this is the block most plant operators interact with daily.

The upper three blocks add intelligence. Health assessment rates the current state as an asset health grade and diagnoses the specific fault, distinguishing for example a bearing defect from misalignment. Prognostic assessment predicts the remaining lifetime until the next significant state change, the function that converts condition monitoring into true predictive maintenance and that increasingly uses trend extrapolation and machine learning. Advisory generation communicates the findings of the lower layers to operators, reliability engineers, and maintenance planners, with the goal of presenting the right information to the right person in the right format.

The practical value of this model for a buyer is comparison. Different products implement different subsets of the six blocks: a simple online protection rack may stop at state detection, while a full reliability platform reaches advisory generation. Asking a vendor exactly where their offering sits across the ISO 13374 blocks, and whether it exposes OSA-CBM compatible interfaces for integration with a wider asset performance management system, cuts through marketing language and exposes the real scope of what is being sold.

Vibration Standards and Acceptance Limits

Vibration is the most-used condition parameter, so the standards that fix its acceptance limits deserve their own chapter. The current limit standard is the ISO 20816 series, which superseded the older ISO 10816 series and also merged in the ISO 7919 shaft-vibration work into a single framework. ISO 20816-1 gives general principles; ISO 20816-3 covers industrial machines with a power rating above 15 kW and rotational speeds from 120 to 30,000 r/min, the bulk of plant pumps, fans, compressors, and motors. The companion ISO 13373 series specifies how the measurement itself is performed.

The acceptance criterion is broadband velocity, measured in mm/s RMS over a 10 Hz to 1000 Hz frequency band on a non-rotating part such as the bearing housing. ISO 20816-3 sorts machines by power and foundation type, then assigns four severity zones. Zone A is the level typical of newly commissioned machines; Zone B is acceptable for unrestricted long-term operation; Zone C is unsatisfactory for long-term continuous running, meaning the machine should run only until a convenient repair window; and Zone D is severe enough to cause damage and requires action. The table below lists the zone boundary velocities.

Two cautions apply when using this table. First, the boundaries are general acceptance guidance, not alarm setpoints. The standard expects each machine to develop its own baseline from commissioning data; a sudden change relative to that baseline is often more diagnostic than an absolute reading still inside Zone B. Second, velocity alone is insufficient on slow machines: at a fixed velocity the underlying displacement grows as speed falls, so for machines at or below 600 r/min the standard requires both velocity and displacement criteria. Above roughly 1000 Hz, gear-mesh and bearing-defect energy moves out of the velocity band and is better judged in acceleration.

Turbomachinery with fluid-film (sleeve) bearings is a separate case. Here the shaft moves within an oil film and the meaningful measurement is relative shaft displacement, sensed by non-contact eddy-current proximity probes rather than casing accelerometers. For petroleum, chemical, and gas-industry rotating equipment this protection instrumentation is governed by API 670, which fixes the proximity-probe mechanical configuration, linear sensing range, accuracy, temperature stability, and the protection-system trip logic. The standard proximity transducer sensitivity is 7.87 mV/um, equal to 200 mV/mil, over a typical 2 mm (80 mil) linear range.

Key Sensor and Acquisition Specifications

Once the technique and limit standard are fixed, selection comes down to reading the sensor and data-acquisition spec sheets. For vibration the dominant transducer is the IEPE accelerometer, also branded ICP, CCLD, IsoTron, or DeltaTron depending on maker, a piezoelectric element with integral charge-to-voltage electronics that drives ordinary coaxial cable over long runs. IEPE devices are estimated to serve over 90 percent of industrial accelerometer applications. The parameters below drive the choice.

Sensitivity for general machinery is 100 mV/g, the de-facto industrial standard, with higher 500 mV/g devices reserved for low-speed assets where vibration amplitude is small. Frequency range is the most failure-prone selection error: the sensor's flat band must enclose every fault frequency of interest, which for envelope detection of bearing defects can reach several kilohertz. Mounting truncates this band: a stud-mounted accelerometer preserves the full high-frequency response, while a magnetic base or handheld probe rolls off the high end and can hide early bearing damage. IEPE supply matters because it must match the data acquisition front end, which has to source the 2 to 20 mA constant current on an 18 to 30 VDC compliance voltage.

On the acquisition side, the system must digitise enough channels at enough bandwidth and resolution to support the analysis. SKF's Multilog On-Line System IMx-8, a representative online unit, provides eight analogue inputs configurable for constant-current accelerometers, current, or voltage signals, plus two digital channels for speed sensors and relay outputs for system, warning, and alarm status. It pairs with SKF CMSS-series accelerometers such as the CMSS 2100T and CMSS 797T. Wireless alternatives, including the Emerson AMS Wireless Vibration Monitor, capture triaxial vibration plus temperature and PeakVue and report through a smart wireless gateway into reliability software such as AMS Machine Works.

Channel count, sample rate, dynamic range, and synchronous multi-channel capability determine whether the system can perform advanced analysis such as order tracking, cross-channel phase for balancing, and transient capture during start-up coastdown. Protection-grade racks add deterministic alarm and trip logic with the response time and redundancy that API 670 demands. For periodic rather than continuous coverage, a portable route-based analyzer such as the Emerson AMS 2140 collects the same vibration features on a walk-around schedule and uploads them to the same database, trading installed cost for manual effort.

Lubricant condition has its own measurement chain. Inline oil sensors and laboratory analysis report the ISO 4406 cleanliness code, water content, viscosity, and wear-metal spectrometry. Because the ISO 4406 scale is logarithmic, each increment in a code number represents a doubling of the particle-count range, so a target such as 16/14/11 versus an actual 20/18/15 is a large, not marginal, contamination difference. Integrating oil-sensor data into the same ISO 13374 architecture lets one platform correlate a rising wear-metal trend with a rising vibration trend on the same gearbox.

A recurring spec-sheet trap is the speed reference. Vibration faults are diagnosed against running speed, so a tachometer or once-per-revolution trigger is needed for order tracking, phase measurement, and balancing, which is why online units such as the IMx-8 reserve digital channels for speed sensors. On variable-speed drives the spectrum smears unless the acquisition tracks order rather than fixed frequency, so confirm the system supports order tracking before specifying it for a machine on a variable-frequency drive. Equally, the analysis bandwidth must be set against the highest fault frequency, not the running speed: a 1500 r/min motor runs at 25 Hz, but its bearing-defect and gear-mesh energy can sit several kilohertz higher, so a front end limited to a few hundred hertz will miss the earliest evidence the accelerometer is perfectly capable of sensing.

Selection Decision Factors

To turn the preceding chapters into a specific system, follow the decision sequence below. Most program failures come not from a single wrong component but from skipping the criticality and failure-mode analysis at the top, then over- or under-instrumenting as a result. These eight steps work as a fixed RFQ template.

1. Asset criticality and failure modes: Rank assets by consequence of failure, then identify the dominant failure modes per ISO 17359. This determines which parameters are worth measuring and is the step that prevents both gold-plating and blind spots.
2. P-F interval and monitoring frequency: Estimate the P-F interval for each chosen technique, then set the monitoring or sampling interval at no more than half of it so a fault is caught with margin. A short P-F interval pushes toward continuous online monitoring; a long one allows portable routes.
3. Monitoring mode: Choose online (permanently installed), portable (route-based), or a hybrid. Critical, unmanned, hazardous, or fast-failing assets justify online; balance-of-plant assets suit portable routes. A typical plant runs online on the critical 10 to 20 percent and routes on the rest.
4. Technique mix: Select the complementary techniques from Chapter 2, vibration as the baseline plus thermography, oil analysis, or MCSA as the failure modes warrant. Confirm one platform can ingest all chosen data streams.
5. Sensor and acquisition specs: Fix accelerometer sensitivity, frequency range, and mounting, or proximity probes for sleeve-bearing machines, then size DAQ channel count, sample rate, and dynamic range to the analysis required (Chapter 5).
6. Standards and acceptance limits: Bind the program to ISO 20816-3 zones for casing vibration, API 670 for turbomachinery protection, ISO 4406 for oil cleanliness, and the relevant ISO 13373 measurement procedures, then document baseline-relative alarm setpoints.
7. Software architecture and integration: Map the offering against the six ISO 13374 blocks, confirm how far it reaches into health assessment and prognostics, and verify integration paths (OPC UA, OSA-CBM, API) into the wider maintenance or asset performance management system.
8. Certifications and environment: Specify hazardous-area rating (ATEX / IECEx Ex ia or Ex d), ingress protection, operating temperature, and functional-safety requirements for any protection and trip duty.

One last dimension is serviceability and analyst support: condition monitoring only delivers value if someone interprets the data. Weigh local sensor and cable spare-part inventory, calibration service, the depth of the diagnostic software's automated fault detection, and whether the vendor offers remote diagnostic services to supplement in-house analysts. SKF, Baker Hughes Bently Nevada, Emerson, Bruel & Kjaer Vibro (HBK), Acoem, PRUFTECHNIK (Fluke Reliability), Schaeffler, and ifm all maintain instrumented portfolios and support networks, making them defensible choices for large programs, while wireless and edge-analytics newcomers should be judged on sensor accuracy, ISO 13374 alignment, and proven diagnostic software rather than sensor unit price alone.