A RS-LOD method and its application in failure feature extraction of rotating machinery

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Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (16) : 120-128.

NIU Xiaorui1，ZHANG Kang1,2，CHEN Xiangmin1,2，LIAO Lida1,2，XU Dingjie1

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Abstract

The local oscillatory-characteristic decomposition (LOD) method is a new adaptive time-frequency analysis method.By adopting three operations of differentiation, coordination domain transform and piecewise linear transformation, the method can efficiently decompose a signal into a series of Mono-oscillation component (MOC), which is very suitable for processing multi-component signals.Although the computational efficiency of the algorithm can be significantly improved by the use of piecewise linear transformation, the MOC component lacks smoothness resulting in distortion.For this problem, the rational spline function that spline shape can be adjusted and control is introduced into the LOD method instead of piecewise linear transformation, and the rational spline-local oscillatory-characteristic decomposition (RS-LOD) method was proposed.Based on the detailed description of the principle of RS-LOD decomposition, the RS-LOD, LOD and the empirical mode decomposition (EMD) were compared and analyzed by simulation signals.The results show that the RS-LOD method can significantly improve the problem of poor smoothness of the MOC component in the original LOD method.In addition, the RS-LOD method was applied to the fault feature extraction of rotating machinery for the multi-component modulation characteristics of rotating machinery fault vibration signals.The analysis results of rolling bearing and gearbox fault vibration signals show that the RS-LOD method can effectively extract the fault feature of rotation mechanical vibration signals.

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local oscillatory-characteristic decomposition(LOD) / rational spline function / rotating machinery / vibration signal / fault feature extraction

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NIU Xiaorui1，ZHANG Kang1,2，CHEN Xiangmin1,2，LIAO Lida1,2，XU Dingjie1. A RS-LOD method and its application in failure feature extraction of rotating machinery[J]. Journal of Vibration and Shock, 2020, 39(16): 120-128

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