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| L-kurtogram and its application to the fault diagnosis of rolling element bearings |
| MING Anbo1，LI Zheng1,2，ZHANG Wei1，CHU Fulei2 |
1.School of Missile Engineering, Rocket Force University of Engineering, Xi’an 710025, China;
2.Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China |
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Abstract As one of the common used statistic indexes for impulse characterizing, kurtosis is inclined to be disturbed by the outlines or stochastic impulse with large value and is not convenient for the feature extraction of the rotating machinery, such as rolling element bearings and gears.To accurately characterizing the feature of signals with cyclic impulses, the L-kurtosis was introduced to the fault diagnosis of rolling element bearings and a novel feature extraction method, named as L-kurtogram, was proposed on the basis of empirical wavelet transform (EWT).By constructing a tight supported empirical wavelet, the original signal can be orthogonally decomposed to be several sub-signals.Then, the L-kurtogram was constructed by calculating the L-kurtosis of the sub-signals of different decompositions.Finally, the cyclic impulse feature was extracted by calculating squared envelope spectrum of the sub-signal with maximum L-kurtosis.Both simulations and experiments were used to validate the efficacy of the proposed method.It is shown that the L-kurtosis is more suitable than the kurtosis for the impulse feature characterization of the signal with cyclic impulses.Furthermore, compared with the original kurtogram and the fast kurtogram based on sub-frequency-band spectral kurtosis average, the L-kurgram is more powerful for the cyclic impulse feature extraction and is more valuable for the engineering application, since the improvements in both signal decomposition and the impulse feature characterization.However, the consuming time for the construction of the filter bank of L-kurtogram is much longer than that of the fast kurtogram and is the major investigation context in the future.
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Received: 10 September 2018
Published: 15 February 2020
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