Envelope analysis is a widely used method for rolling element bearing fault detection. To obtain high detection
accuracy, it is critical to determine an optimal frequency narrowband for the envelope demodulation. However, many of the
schemes which are used for the narrowband selection, such as the kurtogram, can potentially produce poor detection results
because they are sensitive to random noise and aperiodic impulses which normally occur in practical applications. To
achieve the purposes of denoising and frequency band optimisation, this keynote presents a modulation signal bispectrum
(MSB) based robust detector for bearing fault detection. Because of its inherent noise suppression capability, the MSB
allows effective suppression of both the stationary random noise and discrete aperiodic noise. The high magnitude features
that result from the use of the MSB also enhance the modulation effects of a bearing fault and can be used to provide optimal
frequency bands for fault detection. A number of simulated and experimental evaluations show that the proposed method
produces more accurate and robust detection results for common bearing faults under a range of representative scenarios.
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