Complete List of Condition Monitoring Techniques

The future holds great promise for condition monitoring as more sensors are developed that can be mounted on equipment. Also, more equipment is being built to Internet of Things (IoT) standards.
Kelvin Bui, Marketing Associate at SMC, in the MSI Data blog said, “Industrial devices now have an unprecedented amount of sensing, processing and communications capabilities built into the product itself.”
Data analyzed for condition monitoring serves as the basis for predictive maintenance. Patterns emerge from the data showing a machine part may be deteriorating or beginning to fail. Based on the analysis, maintenance is then scheduled to prevent failure and avoid emergency downtime.
The following list of condition monitoring techniques, grouped by several category types, shows the extent technology has moved monitoring ahead. The various methods listed may or may not currently be linked within an IoT network, but most are suitable for automatic data collection and analysis.
Oil Analysis/Tribology
This technique involves collecting and testing machine oils, equipment lubricants or other fluid samples to ascertain the condition of either/both the fluids and the machines. As machines wear, overheat or trend toward failure, contaminants are deposited in lubricating oils and other operating fluids. Careful analysis of oil samples reveals these contaminants. Data from these studies can then be interpreted to indicate impending failures.
Techniques include:
• Ferrography
• Presence of water
• Viscosity/kinematic viscosity test
• ICP or atomic emissions spectroscopy to identify presence of contaminants
• Dielectric strength test
• Microbial analysis
• Particle quantification index (iron content)
• Fourier transform infrared spectroscopy
• Ultraviolet spectroscopy
• Potentiometric titration/total acid number and total base number
• Sediment test
Vibration Analysis/Dynamic Monitoring
Equipment and parts respond to vibrations in a variety of ways that can be used to identify defects due to misalignments, imbalances or design flaws. Wear on machine parts, bearings, rotors and shafts, causes these parts to vibrate with specific patterns that can be recorded and analyzed. Different parts vibrate in different ways, and worn or out-of-balance parts have unique vibration signatures that can be tracked and used to predict parts failures.
Techniques include:
• Shock pulse analysis
• Fast fourier transforms
• Broadband vibration analysis
• Ultrasonic analysis
• Power spectral density (PSD)
• Time waveform analysis
• Spectrogram/spectrum analysis
Motor Circuit Analysis
Motor circuit analysis (MCA) is a battery of computerized tests on an electric motor to ascertain the motor’s overall condition and possible sources of potential failures. Electrical imbalances and degradation of insulation are the chief causes of motor failure and are the focus of MCA testing.
Some tests are go/no-go tests, while test results for others must be tracked over time to identify failure development. These tests are generally grouped into voltage-based or current-based tests.
Inspection points include:
• Power circuit/current signature
• Online and offline testing (not tests but testing regimes)
• Rotor
• Stator
• Insulation
• Power quality
• Air gap
Thermography/Temperature Measurements/Infrared Thermography
Thermography is the study of heat patterns in machines and objects. Images capture thermal radiation patterns emitted from equipment. Data analysis is used to identify potential failures or degradation of equipment parts. Generally, equipment and parts will heat as parts failure is developing. Thermal anomalies and temperature differences can indicate misalignment, imbalances, improper lubrication, worn components, undesirable mechanical stresses and electrical overheating.
Thermographic inspection helps identify safety issues such as overheated electrical connections, pipe leaks and pressure vessel weaknesses. Many infrared techniques based on the principles of IR radiation have been developed to fit specific industrial applications.
Techniques include:
• Comparative thermography
• Testing of electrical, pipe-works and machinery
• Comparative quantitative thermography
• Comparative qualitative thermography
• Paint stickers (colour change with out of spec temperatures)
• Fluids that change colour at out-of-spec temperatures
• Lock-in thermometry
• Pulse phase thermometry
• Pulse thermometry
Ultrasonic Monitoring/Acoustic Analysis/Airborne Ultrasonics
Ultrasonic monitoring of equipment, bearings and rotating parts uses high-frequency sound waves to detect part defects such as leaks, parts seating and cavitations. In many cases, tiny changes in friction forces can be detected with ultrasonic monitoring. These small changes may be missed with IR or vibration analysis. Because of this, UM can be an excellent companion testing technique along with IR and vibration analysis.
Almost all areas of manufacturing processes can benefit from ultrasonic monitoring UM. It provides an early warning for machine parts deterioration that might otherwise be masked by ambient plant noises and temperatures.
Techniques include:
• Airborne ultrasonics
• Ultrasonic backscatter technique
• Backwall echo attenuation
• Ultrasonic thickness and gauging (pipe walls, etc.)
• Phased array testing
• Automatic and continuous ultrasonic inspection
• Internal rotating inspection systems
• Acoustic emissions testing
• Dry-coupled ultrasonic testing
• Long-range ultrasonic testing
• Acoustic ranging
• Time-of-flight diffraction
Radiography/Radiation Analysis/Neutron Radiography
This method uses radiation imaging to identify internal defects in equipment and parts. Applications include inspection of weldments, castings and sintered parts. This approach is one of the most thorough methods of non-destructive testing available.
The technique is based on measuring the differential absorption of radiation penetrating the part or material. Internal corrosion and flaws absorb differing amounts of radiation, which can be measured and analyzed.
Techniques include:
• Neutron backscatter
• Computed radiography
• Computed tomography (CT)
• Direct radiography
• Positive material identification (PMI)
• Neutron radiography
Laser Interferometry
Laser interferometry measures changes in wave displacement based on a laser-generated, highly accurate wavelength of light. This technique is used to identify surface and subsurface defects in composites and other materials. It is based on the interference of light waves generated by a laser. (Sound and radio/electromagnetic waves are also used.) The interference pattern is then captured and measured by a device called an interferometer.
The various interference patterns can be analyzed to show differences in material characteristics such as the presence of corrosion, surface defects or cavities in the material.
Techniques include:
• Laser shearography
• Laser ultrasonics
• Strain mapping
• Electronic speckle pattern interferometry
• Digital holography (used worldwide to test turbine blades and surgical parts)
• Holographic interferometry (still in laboratory testing/not currently used in general widespread condition monitoring)
Electrical Monitoring
This approach applies the principles of deviations in electrical parameters to identify faults and defects. Characteristics such as resistance, induction, capacitance, pulse response, frequency response and others are used to detect potential maintenance issues. Central to this methodology is the measurement of degradation trends in an electrical system so that preventative action can be taken in advance of any system failure.
Techniques include:
• Megohmmeter testing
• High potential testing
• Power signature analysis
• Battery impedance testing
• Surge testing
• Motor circuit analysis
• Alternating current field measurement (ACFM)
Electromagnetic Measurement
This category of test measures magnetic field distortions and eddy current changes to identify cracks, corrosion, weaknesses and other defects. A magnetic field is applied to surface walls, setting up magnetic fields. These fields interfere with one another causing patterns. Eddy current reporting over an extended period is used to identify gradual deterioration in material quality and surface features.
Similarly, electromagnetic testing induces an electromagnetic field or electric current inside the tubing or test object. Defects will create disturbances, which can be measured and analyzed. A variety of techniques have been developed to take advantage of these properties.
Techniques include:
• Magnetic particle inspection
• Magnetic flux leakage
• Metal magnetic memory method
• Pulsed eddy currents
• Remote and near field eddy current
• Saturated low-frequency eddy currents
• Other eddy current testing
Performance Monitoring/Observation and Surveillance/Process Variable and Performance Trending
This traditional approach to monitoring production equipment uses visual inspection and physical senses to judge the proper functioning of a piece of machinery. The technique also uses tracking of output and manufacturing performance to identify deviations in expected results. When production output changes, defects increase or physical characteristics noticeably vary from the norm (sound, heat, vibration), these changes may indicate problems with equipment and possible failures.
This method of monitoring equipment is a valuable technique where advanced technological testing methods are not available. Much of the interpretation of results depends on careful record keeping and interpretation and application of hands-on experience.
Techniques include:
• Visual inspection
• Audio inspection
• Flow rates
• Touch inspection
• Temperatures
• Pressures
• Output or performance trends
• Downtime analysis
Is this everything?
Probably not, but a majority of known condition monitoring techniques you can find on the market today were covered. As industry moves closer and closer to adopting IoT, the practice of condition monitoring is becoming more critical.
Sensors now allow machines to communicate their condition through the Internet to central databases. Newly created analytics then analyze this data to identify which machine parts may be starting to fail. The condition of the equipment can be monitored in real time so that you can schedule planned downtime and proactive maintenance to prevent costly equipment failures.
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Bryan Christiansen is the Founder and CEO at Limble CMMS (a mobile CMMS software). He can be reached at bryan@limblecmms.com.