基于 AVMD 和二阶 FWEO 的滚动轴承故障诊断

In view of the problem that the vibration signal of rolling bearing often contains harmonics，Gaussian white noise and non-periodic transient impact components，which makes it difficult to extract fault features，a fault diagnosis method is proposed based on the combination of adaptive variational mode decomposition （AVMD）and second-order frequency weighted energy operator（SFWEO）. The method firstly determines the number of modes and penalty factors adaptively according to different signals，and decomposes the original signal with parameter-optimized variational mode decomposition（VMD）to obtain multiple instrinsic mode function（IMF）. Secondly，the time-frequency weighted kurtosis of each mode component is calculated to select the best IMF according to the time-frequency weighted kurtosis maximization criterion. Finally， the second-order frequency weighted energy operator is used to demodulate the best IMF. Simulation and experimental results show that the proposed method overcomes the problem that the resolution accuracy of the traditional VMD algorithm is greatly affected by the parameters，which leads to the signal over-decomposition or under-decomposition. At the same time，the second-order frequency-weighted energy operator has a good suppression effect on the interference components in the signal，and effectively improves the diagnostic accuracy.