Abstract：Variational mode extraction (VME) is a new method to extract specific signal modes with very low computational complexity. It obtains intrinsic mode function by setting the expected modal center frequency. However, VME can only extract one component for one central frequency, which cannot realize the adaptive decomposition of multi-component signals. According to the length and bandwidth of the signal data, the signal decomposition problem was transformed into a multi-mode optimization problem, which setting the center frequency parameters of multi-component modes adaptively in this paper. On this basis, an Adaptive Variational Mode Extraction (AVME) method was proposed. Also, to solve the problem that a single index cannot measure the comprehensive information characteristics of the optimal demodulation component, a fused indicator based on the kurtosis, correlation coefficient and orthogonality is developed to highlight the useful components for demodulation and diagnosis. The proposed method is compared with the existing signal decomposition methods by analyzing the fault simulation signal and the measured signal of rolling bearing. The results show that the proposed method is effective and superior in the calculation time and noise reduction.
俞惠惠，郑近德，潘海洋，童靳于，刘庆运. 基于自适应变分模态提取的低速重载滚动轴承故障诊断方法[J]. 振动与冲击, 2022, 41(11): 65-71.
YU Huihui, ZHENG Jinde, PAN Haiyang, TONG Jinyu, LIU Qingyun. Fault diagnosis method of low speed and heavy load rolling bearing based on adaptive variational mode extraction. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(11): 65-71.
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