Bearing Acoustic Emission Signal Processing Based on MEA-WPT
The noise of the working environment of rolling bearings will make it difficult to process the bearing AE signal,so a noise reduction method of the bearing AE signal based on the thinking evolution heuristic algorithm to opti-mize the wavelet packet transform is proposed.In this method,the MEA algorithm is used to optimize the problem that the WPT algorithm has the problem that it is difficult to find the optimal combination of wavelet function and wavelet packet decomposition layer in the signal processing task,and the signal reconstruction and envelope analysis are carried out according to the node component and kurtosis index analysis(KI)of the optimized wavelet packet decomposition.By comparing the extracted bearing fault eigenfrequencies with the theoretical eigenfrequencies,the effectiveness of the pro-posed method in bearing acoustic emission signal processing is verified.
Rolling bearingAcoustic emissionWavelet packet transformation
万方数据
维普
