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Changes in vibrations of machinery can indicate the condition of balance, lubrication, bearings and gears. Early detection of issues can avoid catastrophic failure, preventing secondary damage and excess downtime.
Measurement of vibration
Vibration can be monitored by measuring displacement, velocity or acceleration. Integration or differentiation of these signals can also convert between them. Most commonly, an accelerometer is used. If displacement is sinusoidal, both the velocity and acceleration are also sinusoidal, but there are 90° phase shifts between these signals.
At very low frequencies, displacement can be the best measure. At frequencies between 10Hz and 2kHz velocity often works best. Acceleration gives the best information at higher frequencies. Unbalance, misalignment and looseness produce characteristic frequencies at, or a few times, the shaft running speed, which usually makes velocity the best measure. The much higher frequencies of bearing faults are better suited to acceleration.
Spectrum analysis
Typically the most useful way to view vibration analysis results is as a spectral plot, which identifies the major underlying frequencies in a vibration signal. Typically, a vibration signal will be made up of a number of underlying sinusoidal waveforms, each with a different amplitude, frequency and phase shift. The combined signal looks chaotic and is hard to interpret.
A Fast Fourier Transform can decompose a complex signal, a process referred to as spectrum analysis. The results are easily interpreted from a spectral plot, characterising the underlying waveforms in terms of frequency and amplitude. When using a spectral plot to understand the condition of rotating machinery, it is useful to quantify frequencies in terms of the shaft running speed, 1X.
Vibration at 1X shaft running speed often indicates unbalance or angular misalignment. A moderate level of 1X vibration, with other frequencies of lower amplitude, is typical of a healthy machine. Vibrations at frequencies a few multiples of shaft running speed can be caused by parallel misalignment or loose bearings.
Looseness or play can cause harmonics, with spikes appearing at many different integer multiples of shaft running speed, and potentially an increase in noise floor.
Other types of fault produce frequencies that are not multiples of shaft running speed. Defects in bearing casings produce a shockwave when a roller impacts on the defect. This is not a sinusoidal signal and will not normally be an exact multiple of the shaft running speed. The frequency of the impact depends on the number of rollers and the precession rate of a roller around the bearing, as well as the shaft running speed.
Bearing defects can result in very high frequencies and the impact shockwave can have a very short duration, requiring very high sampling rates. Some filtering to remove low-frequency and high-amplitude vibration may be required to detect bearing faults at an early stage.
Electrical faults can result in frequencies that are multiples of the AC supply frequency. Examples include distortions of motor stator windings or faulty rectifiers.
To properly interpret vibration signals it is important to understand the configuration of a machine. A vibration analyst might start by moving sensors around a machine, noticing the position and direction where the underlying frequencies have the greatest amplitude.
Time waveform analysis
Time waveform analysis uses the raw data from a sensor or a simple integration of it, such as a plot of acceleration against time. Although it is generally much harder to identify characteristic frequencies, hence the use of spectral plots, the time waveform does have its uses. It is important to consider the resolution of data to ensure that the highest frequencies expected can be detected. The waveform can also provide additional information to distinguish between different faults.
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Content published by Professional Engineering does not necessarily represent the views of the Institution of Mechanical Engineers.