Vibration monitoring is a good application for the Industrial Internet of Things (IIoT) because of its analytics potential. This feature originally appeared in the ebook Automation 2022: IIoT and Industry 4.0 (Volume 3).
Predictive maintenance techniques are effective strategies to reduce unexpected machinery failure. Vibration monitoring is by far the most widely used predictive maintenance technology due to the significant amount of machinery condition information it provides. Most plants that implement a vibration monitoring program begin with a portable data collector and a predetermined route of data collection points. Vibration data is gathered and trended. Maintenance action then is determined based on machinery condition trends. Often, the new vibration information is reviewed and compared to trended data, and no anomalies or exceptions are noted. At this point, vibration analysts often realize that they wasted valuable time and resources taking vibration data on healthy machines. Plant size and the number of measurement points can make implementing a vibration monitoring program a formidable task. Determining the data collection routes and data collection frequency also can be a difficult undertaking. These issues, as well as having machinery with different failure rates (i.e., the time to machinery failure once excessive vibration is detected), direct many plant managers toward investigating continuous vibration monitoring solutions with permanently installed instrumentation. These investigations often reveal that most permanently mounted instrumentation produces a signal that is not compatible with existing plant monitoring instrumentation, such as programmable logic controllers (PLCs), and that proprietary, duplicative equipment must be implemented.
An inline or DIN-rail-mounted vibration transmitter eliminates the need for duplicative equipment by converting the output of a general purpose ICP accelerometer into a 4-20 mA output compatible with a PLC (figure 1). The PLC sends alarms to the vibration analyst when vibration levels become excessive. These alarms alert the predictive maintenance team of the need for closer investigation to pinpoint the exact failure mode. That additional analysis is facilitated by a raw vibration signal also available through the vibration transmitter that can be analyzed with portable diagnostic equipment. Figure 1: The recommended setup of a vibration monitoring system using an inline or DIN- rail-mounted vibration transmitter includes an ICP accelerometer, vibration transmitter, and PLC, along with appropriate cables. This approach is more cost effective, since plant monitoring instrumentation, such as PLCs, is widely used in many factories. Vibration channels can be added at a fraction of the cost of adding separate redundant vibration monitoring equipment. Other costs, such as installation and training, also are reduced since the monitoring instrumentation already is installed and trained personnel are in place. Once the decision is made to implement a vibration monitoring program using existing monitoring instrumentation, the next task is to determine the equipment to be monitored and to define the machinery faults that need to be detected. Answers to the first point are relative to the particular equipment, including repair cost, failure rate and its importance to the production process. Answers to the second part require a basic understanding of the typical machinery failure modes and their respective vibration signatures.
The first step in implementing any vibration monitoring program is to know the equipment. Research the machinery to be monitored to be familiar with its operation and understand its potential failure modes. There are many failure modes for machinery. The more complex the equipment, the more complex the failure mode can be. The four most common failure modes found in standard equipment are imbalance, misalignment, bearing faults and gear mesh failure. Each machinery fault has a unique vibration signature that helps technicians identify the fault. Each fault has specific fault frequencies that help determine the failure mode, while the vibration amplitude helps to determine the severity of the problem. Imbalance and misalignment most often occur at low frequencies. Mechanical looseness and process loading also can produce faults at low frequencies. These machinery failures demonstrate high vibration at the running speed, as well as two- and three-times running speed. These low frequencies are typically in the 2 to 1,000 Hz range for equipment operating at around 1,800 rpm. Since the mechanical defect is a result of a physically massive rotor or shaft, the amplitudes are relatively high. A good range for trending vibration is from 0-1 in/sec RMS. Figure 2 shows a basic spectrum plot of potential machinery failures. The units for the frequency and amplitudes have been left off purposely, as the actual values would not allow all the faults to be visible in the limited area. Bearing faults occur at nonsynchronous multiples of machinery turning speed. Specific bearing fault frequencies are unique to the bearings and depend on the physical bearing parameters. Specific measurements, such as pitch and bearing diameter, number of balls, and turning speed, are needed to calculate the fault frequencies of bearing failures like inner race and outer race defects, as well as ball bearing defects. Bearing defect frequencies are available from most bearing manufacturers. but as a rule of thumb, one can estimate the frequency by calculating the result of the number of balls in the bearing times the machinery turning speed times 50%. Figure 2: The four most common failure modes found in standard equipment are imbalance, misalignment, bearing faults, and gear mesh failure. Each machinery fault has a unique vibration signature that helps to identify the particular fault. The graph shows a basic spectrum plot of potential machinery failures. Vibration amplitudes for these faults are very low, as the mass of the moving parts is relatively small compared to the rotor or shaft mass. Bearing fault frequencies range from 200 to 5,000 Hz with relatively low amplitudes. Trending acceleration data instead of velocity data is desired, since velocity accentuates the lower frequency vibration and attenuates the higher frequency vibration, while acceleration data gives stronger signals at higher frequencies and is better able to measure the lower amplitudes of bearing faults. A typical acceleration range for bearing fault detection may be 0 to 10 g peak. Gear mesh faults occur at higher frequencies than bearing faults. Gear mesh frequencies are the product of the number of teeth times the shaft’s turning speed. Depending on the machine, these gear mesh frequencies can range from 100 Hz to more than 10 kHz. As mentioned previously, acceleration data is preferred over velocity data, as the acceleration measurement emphasizes the higher frequency vibration and de-emphasizes and is less sensitive to the lower frequency mechanical defects and process loading conditions. A typical acceleration range for gear mesh fault detection may be 0 to 50 g peak. Figure 3 shows the simple vibration relationship between velocity, acceleration, and displacement over frequency. Figure 3: Acceleration data is preferred over velocity data for high-frequency fault detection, as the acceleration measurement emphasizes the higher frequency vibration and de-emphasizes and is less sensitive to the lower frequency mechanical defects and process loading conditions.
It is imperative to know the machinery to effectively implement a vibration monitoring program. Current machinery operating conditions, expected failure modes, and potential machinery faults are factors to consider when monitoring equipment. Selecting the proper frequency band to trend relative to the fault of interest is critical to actually detect the given machinery fault and eventually predict machinery failure. Determining the amplitude ranges within the given frequency band also is important so that alarms will provide an early warning when machinery condition has degraded. Figure 4 from ISO 10816-1-1995: Mechanical Vibration—Evaluation of Machine Vibration by Measurements on Non-Rotating Parts shows possible alarm levels for general machinery classes. Figure 4: Alarms provide an early warning when machinery condition has degraded. This graph was taken from ISO 10816-1-1995: Mechanical Vibration—Evaluation of Machine Vibration by Measurements on Non-Rotating Parts. Another critical concern for vibration monitoring equipment and alarms is that a time delay be available for each measurement point. A time delay is used to avoid false alarms that could occur because of transient vibration caused by local traffic, process changes, and even ancillary equipment. Also, the time delay should be sufficient to avoid setting off alarms during machinery startup and coast down. During startup and coast down, the equipment could move through mechanical resonances, and high amplitude vibrations could be present. Transient time delays should be on the order of 5 to 10 seconds, while time delays for machine startup and coast down should be greater at approximately one minute. It may be desirable to deactivate the vibration transmitters and their alarms during startup and coast down to avoid inadvertently setting off alarms.
Machinery condition monitoring is an important facet in modern maintenance. Avoiding unscheduled downtime is critical to maintain corporate competitiveness. Low-cost rotating machinery condition monitoring using general purpose ICP accelerometers, such as Model 603C01, inline or DIN-rail-mounted vibration transmitters, such as Models 682A09 or 682C03, and existing plant monitoring instrumentation is an excellent method to gather information to help determine the overall health of a plant’s machinery. All images courtesy of the IMI division of PCB Piezotronics. This feature originally appeared in the ebook Automation 2022: IIoT and Industry 4.0 (Volume 3).
Eric Saller is with PCB Piezotronics, a wholly owned subsidiary of Amphenol Corporation. PCB is a manufacturer of vibration, pressure, force and strain, shock, and acoustic sensors used by design engineers and predictive maintenance professionals worldwide for test, measurement, monitoring, and control requirements. Primary sensing technologies include piezoelectric (ICP), piezoresistive and capacitive MEMS.
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