Application of high-order differential energy operator in bearing fault diagnosis

An alternative energy operator demodulation method named high-order differential energy operator is proposed in this paper. The high-order differential energy operator, unlike previous demodulation techniques, can detect the weak fault bearing signature from a heavily contaminated signal because it can increase the signal-to-noise ratio. Furthermore, this energy operator is also able to suppress vibration interferences. Thus, the operator is more robust than the classical Teager energy operator (TEO) and its improved versions (DESA-1 and DESA-2 for short). Besides, it is also a non-parameter and non-filtering method, so it is easy and straightforward to apply. Finally, the built-in amplitude demodulation (AD) capability eliminates the enveloping step required by most AD methods like TEO and Hilbert transform (HT). The results of simulation tests and bearing fault experiments demonstrate that this method can effectively extract fault features, certifying its superiority in comparison with previous demodulation methods. Therefore, it is more likely to be useful and practical in the field of bearing fault diagnosis, especially in the presence of intense noise and interferences.

[1]  Abdolreza Ohadi,et al.  Application of wavelet energy and Shannon entropy for feature extraction in gearbox fault detection under varying speed conditions , 2014, Neurocomputing.

[2]  Wilson Wang,et al.  An enhanced Hilbert–Huang transform technique for bearing condition monitoring , 2013 .

[3]  Cécile Capdessus,et al.  CYCLOSTATIONARY PROCESSES: APPLICATION IN GEAR FAULTS EARLY DIAGNOSIS , 2000 .

[4]  X. An,et al.  Bearing fault diagnosis of a wind turbine based on variational mode decomposition and permutation entropy , 2017 .

[5]  Petros Maragos,et al.  Energy separation in signal modulations with application to speech analysis , 1993, IEEE Trans. Signal Process..

[6]  A. Enis Çetin,et al.  The Teager energy based feature parameters for robust speech recognition in car noise , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[7]  Naoyuki Aikawa,et al.  Instantaneous frequency estimation for a sinusoidal signal combining DESA-2 and notch filter , 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).

[8]  J. Antoni Fast computation of the kurtogram for the detection of transient faults , 2007 .

[9]  Petros Maragos,et al.  Higher order differential energy operators , 1995, IEEE Signal Processing Letters.

[10]  M. Feldman Hilbert transform in vibration analysis , 2011 .

[11]  Byeong-Gwan Iem Generalized Higher Order Energy Based Instantaneous Amplitude and Frequency Estimation and Their Applications to Power Disturbance Detection , 2012, Int. J. Fuzzy Log. Intell. Syst..

[12]  A. Enis Çetin,et al.  Teager energy based feature parameters for speech recognition in car noise , 1999, IEEE Signal Processing Letters.

[13]  Michael Pecht,et al.  Vibration model of rolling element bearings in a rotor-bearing system for fault diagnosis , 2013 .

[14]  Qiang Miao,et al.  Time–frequency analysis based on ensemble local mean decomposition and fast kurtogram for rotating machinery fault diagnosis , 2018 .

[15]  Harvey F. Silverman,et al.  Stop classification using DESA-1 high resolution formant tracking , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[16]  Zongyan Cai,et al.  An alternative demodulation method using envelope-derivative operator for bearing fault diagnosis of the vibrating screen , 2018 .

[17]  Keith Worden,et al.  Fault detection in rolling element bearings using wavelet-based variance analysis and novelty detection , 2016 .

[18]  Aneta Stefanovska,et al.  Nonlinear mode decomposition: a noise-robust, adaptive decomposition method. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Asoke K. Nandi,et al.  CYCLOSTATIONARITY IN ROTATING MACHINE VIBRATIONS , 1998 .

[20]  Abdel-Ouahab Boudraa,et al.  Generalized higher-order nonlinear energy operators. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.