Predictive Maintenance Technologies
The start of predictive maintenance (PdM) may have been when a mechanic first put his ear to the handle of a screwdriver, touched the other end to a machine, and pronounced that it sounded like a bearing was going bad. We've come a long way since then with a variety of technologies for analyzing what's going on inside equipment, but the need for a knowledgeable, experienced person to use the ...
The start of predictive maintenance (PdM) may have been when a mechanic first put his ear to the handle of a screwdriver, touched the other end to a machine, and pronounced that it sounded like a bearing was going bad. We’ve come a long way since then with a variety of technologies for analyzing what’s going on inside equipment, but the need for a knowledgeable, experienced person to use the technology hasn’t changed. Today, as in the beginning, successful predictive maintenance is a combination of man and technology.
But let there be no mistake; it is the advances in technology that have made PdM a reality — most notably the ready availability of cheap computing power to gather, store, and analyze the data that makes PdM possible. By some counts, there are more than 40 technologies being used for predictive maintenance. Others might argue that many of these are simply variations on other, more basic methods. Presented here are some of the essentials regarding the most-used PdM technologies.
Any predictive maintenance program should be characterized by a combination of three phases:
Surveillance — monitoring machinery condition to detect incipient problems
Diagnosis — isolating the cause of the problem
Remedy — performing corrective action.
Consistent, accurate data gathering is essential to all three phases.
In general, the predictive maintenance process can be broken into 12 essential steps as shown in the diagram on page 67. The first six steps are actions to be taken before condition monitoring begins. Steps seven through ten represent the routine monitoring of an established program, and the final two steps cover diagnosis and fault correction.
Analysis of data is where the knowledge and experience of maintenance personnel becomes most important in a PdM program. It normally requires extensive training not only in the analysis techniques, but also in the use of the particular hardware and software employed. There are five important analysis techniques in PdM:
Data comparison — recognition of changes in data as compared to earlier data or baseline data on similar equipment.
Limit or range tests — specific testing to discover operating parameters that do not follow continuous trends or repeatable patterns.
Pattern recognition —— identification of deviations from established patterns.
Correlation analysis — comparison of data from multiple sources, related technologies, or different analysts.
Statistical process analysis — use of statistical techniques to identify deviations from the norm.
Misalignment of shafted equipment will not only cause equipment malfunctions or breakdowns, it may be an indicator of other problems.
Checking and adjusting alignments used to be a very slow procedure. But the advent of laser alignment systems has reduced labor time by more than half and increased accuracy significantly.
Laser alignment systems for shafts have been available for many years. Laser devices for aligning sheaves and pulleys have recently come to market.
Although this program was developed for vibration analysis, it can also be applied to most other PdM processes.
Instruments designed for ultrasonic testing sense ultrasound waves produced by operating machinery as well as the turbulent flow of leakage. They provide fast, accurate diagnosis of such problems as valves in blowby mode, faulty steam traps, and vacuum and pressure leaks. Ultrasonic observations may be taken in either airborne or contact mode.
Airborne ultrasonics is extremely useful in the location and diagnosis of mechanical problems, but the technology is not capable of isolating specific sources of ultrasound within a machine. Testing instruments are usually battery operated for portability. Their electronic circuitry converts a narrow band of ultrasound (between 20 and 100 kHz) into the audible range so that a user can recognize the qualitative sounds of operating equipment through headphones. Intensity of signal strength is also displayed on the instrument.
As scanners, ultrasonic instruments are most often used to detect gas pressure or vacuum leaks. Because they are sensitive only to ultrasound, they are not limited to a specific gas, as are most other leak detectors.
In contact mode, a metal rod acts as a waveguide. When it touches a surface, it is stimulated by ultrasound on the opposite side of the surface. This technique is commonly used for locating turbulent flow or flow restrictions in piping.
Ultrasonic detectors are somewhat limited in their use. For example, they may help identify the presence of suspicious vibrations within a machine, but they are not sufficient for isolating the sources or causes of those vibrations.
On the plus side, ultrasonic monitoring is easy (requiring minimal training), and the instruments are inexpensive.
Full benefit of oil analysis can be achieved only by taking frequent samples and trending the data for each machine in the program. The length of the sampling intervals varies with different types of equipment and operating conditions. Based on the results of the analyses, lubricants can be changed or upgraded to meet the specific operating requirements. It is nearly always best to work with a reputable laboratory for sample analysis and data interpretation.
It cannot be overemphasized that sampling technique is critical to meaningful oil analysis. Sampling locations must be carefully selected to provide a representative sample and sampling conditions should be uniform so that accurate comparisons can be made.
A thorough oil analysis typically includes 11 tests:
Viscosity is one of the most important properties of a lubricating oil. The analysis consists of comparing a sample of oil from a machine to a sample of unused oil to determine if thinning or thickening of the oil has occurred during use.
Contamination of oil by water or coolant can cause major problems. Because many of the additives in lubricants contain the same elements used in coolant additives, samples for analysis must be compared to samples of new oil.
Fuel dilution of engine oil weakens the oil’s film strength, sealing ability, and detergency. Dilution may indicate such problems as improper operation, fuel system leaks, ignition problems, improper timing, or other deficiencies.
Solids content is a general test indicating total solids in the oil as a percentage of the sample volume or weight. Any unexpected rise in solids is cause for concern, because the presence of solids can significantly increase wear on lubricated parts.
Fuel soot content is an important indicator for oil in diesel engines. Although fuel soot is always present in diesel engine oil to some extent, increases above normal levels may indicate fuel burning problems.
Oxidation of lubricating oil can result in lacquer deposits, metal corrosion, or thickening of the oil.
Nitration results from fuel combustion in engines. The products formed are highly acidic, and they may leave deposits in combustion areas and accelerate oil oxidation.
Total acid number (TAN) is a measure of the amount of acid or acid-like materials in oil.
Total base number (TBN) indicates an oil’s ability to neutralize acidity. Low TBN is often an indicator that the wrong oil is being used for the application, intervals between oil changes are too long, oil has been overheated, or a high-sulfur fuel is being used.
Particle count as part of a standard oil analysis is quite different from the wear particle analysis offered as a separate, specialized service (see following section). High particle counts indicate that machinery may be wearing abnormally or that failures could be caused by blocked orifices. Particle count tests are especially important in hydraulic systems.
Spectrographic analysis reveals the presence of such elements as wear metals, contaminants, and additives in oil.
Wear particle analysis
While oil analysis provides information about the lubricant itself, wear particle analysis provides direct information about wearing conditions inside the machinery. This information is derived from the study of particle shapes, composition, sizes, and quantitites.
Wear particle analysis is conducted in two stages. The first involves monitoring collected particles to determine normal conditions and trends. The second is the diagnosis of abnormal conditions as indicated by changes in the particle types, sizes, and quantities.
Rubbing wear results from the normal sliding wear in a machine and should remain stable as a surface wears normally. But a dramatic increase in wear particles indicates impending trouble.
Cutting wear particles are generated with one surface penetrates another, much as a cutting tool removes material. Cutting wear particles are abnormal and are always worthy of attention. These particles are produced when a misaligned or fractured hard surface produces an edge that cuts into a softer surface, or when abrasive contaminants become embedded in a surface and cut an opposing surface. Increasing quantities of longer particles signal a potentially imminent component failure.
Rolling fatigue is associated primarily with rolling contact bearings and may produce three distinct particle types: fatigue spall particles, spherical particles, and laminar particles. Rolling spall particles are the most critical, because they indicate damage to a rolling element has already occurred.
Combined rolling and sliding wear results from the moving contact of surfaces in gear systems. The chunkier particles result from tensile stresses on the gear surface, causing the fatigue cracks to spread deeper into the gear tooth before pitting. Scuffing of gears occurs when excessive heat from a high load or speed breaks down the lubricant film. Once started, scuffing usually affects each gear tooth.
Severe sliding wear also results from excessive loads or heat in a gear system. Large particles break away from the wear surfaces. If conditions are not corrected, catastrophic wear is the likely result.
Infrared thermography uses special instruments to detect, identify, and measure the heat energy objects radiate in proportion to their temperature and emissivity. Midwave-range instruments detect infrared in the 2-to-5 micron range; longwave-range instruments detect the 8-to-14 micron range.
Infrared inspections can be qualitative or quantitative. Qualitative inspection concerns relative differences, hot and cold spots, and deviations from normal or expected temperatures. Quantitative inspection concerns accurate measurement of the temperature of the target.
As one of the most versatile predictive maintenance technologies available, infrared thermography is used to study everything from individual components of machinery to plant systems, roofs, and even entire buildings.
Infrared instruments include an optical system to collect radiant energy from the object and focus it, a detector to convert the focused energy pattern to an electrical signal, and an electronic system to amplify the detector output signal and process it into a form that can be displayed. Most instruments include the ability to produce an image that can be displayed and recorded. These thermographs, as the images are called, can be interpreted directly by the eye or analyzed by computer to produce additional detailed information. High-end systems can isolate readings for separate points, calculate average readings for a defined area, produce temperature traces along a line, and make isothermal images showing thermal contours.
It is essential that infrared studies be conducted by technicians who are thoroughly trained in the operation of the equipment and interpretation of the imagery. Variables than can destroy the accuracy and repeatability of thermal data, for example, must be compensated for each time data is acquired. In addition, interpretation of infrared data requires extensive training and experience.
Vibration monitoring might be considered the "grandfather" of predictive maintenance, and it provides the foundation for most plants’ PdM programs.
Monitoring the vibration from plant machinery can provide direct correlation between the mechanical condition and recorded vibration data of each machine in the plant. Used properly, it can identify specific degrading machine components or the failure mode of plant machinery before serious damage occurs.
Vibration monitoring and trending works on the premise that every machine has a naturally correct vibration signature. This signature can be measured when the machine is in good working order, and subsequent measurements can be compared with what is considered the norm. As the machine wears or ages, the vibration spectra change. Analyzing the changes identifies components that require further watching, repair, or replacement.
Most vibration-based PdM programs rely on one or more of the following techniques:
Broadband trending provides a broadband or overall value that represents the total vibration of the machine at the specific measurement point where the data was acquired. It does not provide information on the individual frequency components or machine dynamics that created the measured value. Collected data is compared either to a baseline reading taken when the machine was new (or sometimes data from a new, duplicate machine) or to vibration severity charts to determine the relative condition of the machine.
Narrowband trending monitors the total energy for a specific bandwidth of vibration frequencies and is thus more specific. Narrowband analysis utilizes frequencies that represent specific machine components or failure modes.
Signature analysis provides visual representation of each frequency component generated by a machine. With appropriate training and experience, plant personnel can use vibration signatures to determine the specific maintenance required on the machine being studied.
Until fairly recently, predictive maintenance technologies for motors were limited to vibration testing, high-voltage surge testing for winding faults, meg-Ohm and high-potential tests for insulation resistance to ground, and voltage and current tests for testing phase balance. Many of these test still have their place in plant maintenance, but several of them are impractical, dangerous, or harmful when tests are conducted with motors in place.
New technologies allow for portable, safe, and trendable tests that can be used for more accurate commissioning and troubleshooting. Each of these technologies has its strengths and weaknesses. But as part of a PdM program, they can accurately detect potential faults and avoid costly downtime.
Static motor circuit analysis (MCA) provides a low-voltage, safe method of testing motor winding and rotor defects. The best instruments for this analysis use impedance-based tests coupled with insulation-to-ground testing. Impedance-based instruments are simple to use, and the results are easy to evaluate. Inductive-based instruments are for trending. Tests detect faults in motors, transformers, cabling, and connections. Motors must be de-energized.
Motor current signature analysis (MCSA) is performed by taking current data and analyzing it using fourier transform analysis. Primary purpose of the test is rotor bar fault detection, but it is also useful for detecting rotor faults and power quality problems as well as other motor and load defects in later stages of failure. Motors must be energized and loaded during tests.
Surge comparison testing uses high-voltage pulses to detect winding faults. Only experienced operators should conduct these tests because of the potentially harmful effects of high voltage impressed on used windings and cables. There are also challenges with testing assembled motors due to rotor effects on the motor circuit. Motor being tested must be de-energized with controls disconnected.
High potential testing uses high-voltage ac or dc to detect faults to ground. Only the insulation condition between stator windings and ground can be evaluated and there is a potential for damage to the insulation system if the test is improperly applied or controlled. Motors must be de-energized with controls disconnected during tests.
Plant Engineering would like to acknowledge the contributions of the following people and companies in the preparation of this article.
Howard W. Penrose, Ph.D., ALL-TEST Div., BJM Corp.; bjmcorp.com
Michael Booth, Raytheon Infrared; raytheoninfrared.com
Don Werner, Integrated Condition Monitoring, Rockwell Automation Entek; entekird.com
Ludeca Inc.; ludeca.com
National Electrical Carbon; nationalelectrical.com
Flir Systems; flirthermography.com
Infrared Solutions Inc.; infraredsolutions.com