A robust detector for rolling element bearing condition monitoring based on the modulation signal bispectrum and its performance evaluation against the Kurtogram

• Published in: Mechanical systems and signal processing 2018-02, Vol.100, p.167-187
• Main Authors: Tian, Xiange, Xi Gu, James, Rehab, Ibrahim, Abdalla, Gaballa M., Gu, Fengshou, Ball, A.D.
• Format: Article
• Language: English
• Subjects: Analysis; Bearing; Bearing fault detection; Condition monitoring; Data analysis; Demodulation; Envelope analysis; Fault detection; Frequencies; Gears; Kurtogram; Modulation; Modulation signal bispectrum; Motors; Narrowband; Noise reduction; Noise sensitivity; Performance evaluation; Random noise; Robustness; Vibration
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2017.07.037

•A robust MSB detector is developed.•MSB is applied to vibrations of motor and planetary gearboxes.•Simulated data are applied to performance evaluation.•Experimental vibrations of motor and planetary gearbox are investigated. 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 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 paper proposes a novel 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 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. The Kurtogram is generally accepted as a powerful means of selecting the most appropriate frequency band for envelope analysis, and as such it has been used as the benchmark comparator for performance evaluation in this paper. Both simulated and experimental data analysis results show that the proposed method produces more accurate and robust detection results than Kurtogram based approaches for common bearing faults under a range of representative scenarios.