Predictive maintenance & condition monitoring Measurement Vibration Vibration Sound pressure Sound pressure Motor current Magnetic field Temperature


Sensor Piezo


Table 1. Popular Sensors Used for CbM Key Information


accelerometer MEMS


accelerometer Microphone


Ultrasonic microphone


Shunt, current transformer


Hall,


magnetometer, search coil


Infrared thermography


RTD, Temperature Oil quality


thermocouple, digital


Particle monitor Low cost, size, accurate


Viscosity, particles, and contamination


identify and repair motors running inefficiently, enabling increased performance, productivity, asset availability, and lifetime. The best PdM strategy is one that efficiently utilises as many techniques and sensors as possible to detect faults early and to a high degree of confidence, so, there is no one-sensor- fits-all solution. This article seeks to clarify why predictive maintenance sensors are vital to early detection of faults in PdM applications, as well as their strengths and weaknesses.


SySTeM FaUlT TiMeline Figure 1 shows a simulated timeline of events from the installation of a new motor to motor failure along with the recommended predictive maintenance sensor type. When a new motor is installed, it is under warranty. After several years, the warranty will expire, and it is at this point that a more frequent manual inspection regiment will be implemented. If a fault emerges in between these scheduled maintenance checks, there is a likelihood of unplanned downtime. What becomes vitally important in this case is having the right predictive maintenance sensor to detect potential faults as early as possible and, for this reason, this article will focus on vibration and acoustic sensors. Vibration analysis is generally perceived as the best starting point for PdM.


PrediCTiVe MainTenanCe SenSOrS Some sensors can detect certain faults, such as bearing damage, much earlier than others, as shown in Figure 1. In this section, the sensors


Instrumentation Monthly October 2021


Low noise, frequencies up to 30 kHz, well


established in CbM applications Low cost/power/size,


frequencies up to 20 kHz+ Low cost/power/size,


frequencies up to 20 kHz Low cost/power/size,


frequencies up to 100 kHz


Low cost, non-invasive, usually measured at motor supply


Low cost/size, frequencies up to 250 Hz, stable over temperature


Expensive, accurate, multiple as- sets/sources of heat at one time


Target Faults


Bearing condition, gear meshing, pump cavitation, misalignment, imbalance, load condition


Bearing condition, gear meshing, pump cavitation, misalignment, imbalance, load condition


Bearing condition, gear meshing, pump cavitation, misalignment, imbalance, load condition


Pressure leaks, bearing condition, gear meshing, pump cavitation, misalignment, imbalance


Eccentric rotors, winding issues, rotor bar issues, supply imbalance, bearing issues


Rotor bar, end ring issues


Heat source location due to friction, load changes, excessive start/stop, insufficient power supply


Change in temperature due to friction, load changes, excessive start/stop, insufficient power supply


Detect debris from wear


most commonly used to detect faults at the earliest possible moment are discussed, namely accelerometers and microphones. Table 1 shows a list of sensor specifications and some of the faults they can detect. Most PdM systems will only employ some of these sensors, so it is imperative to ensure potential critical faults are well understood along with the sensors that are best suited to detecting them.


Figure 2. Per cent of occurrences of failed motor components


SenSOr and SySTeM FaUlT COnSideraTiOnS More than 90 per cent of rotating machinery in industrial and commercial applications use rolling-element bearings. The distribution of failed components of a motor are shown in Figure 2, where it is clear to see that, when selecting a PdM sensor, it is important to focus on bearing monitoring. In order to detect, diagnose, and predict potential faults, a vibration sensor must have low noise and wide bandwidth capabilities. Table 2 shows some of the most common


faults associated with rotating machines and some corresponding vibration sensor requirements for use in PdM applications. In order to detect faults as early as possible, PdM systems typically require high performance sensors. The performance level of the predictive maintenance sensor used


Table 2. Brief Overview of Machine Fault and Vibration Sensor Considerations Sensor Requirements


Common Machine Faults Imbalance


Low to medium noise >100 µg/√Hz


Low noise <100 µg/√Hz


Bandwidth: 5× to 10× fundamental frequency


Bandwidth: >5 kHz Multiaxis sensing


Low frequency response for slow rotating machines


High g-range   


Continued on page 42... 41


      Misalignment   


Bearing Defects


Gear Defects


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78