Accurate fault diagnose of gearbox under noise condition is a difficult problem in gearbox fault diagnosis. In order to solve this problem, the noise reduction method of decomposing and reorganizing complete ensemble empirical mode decomposition with adaptive noise analysis (CEEMDAN) by adaptive wavelet was adopted, and the convolution neural network based on inception(BICNN) was put forward to extract the basic digital characteristics of the reconstructed signal and long short-term memory(LSTM) was adopted to extract the correlation features among the features extracted by BICNN.The method was used to study the fault diagnosis of the gearbox. The diagnosis results show that the proposed method has high anti-noise ability, and it can still obtain 99.63% training accuracy when the gearbox is disturbed by -4 dB noise.
CAI Chaozhi, BAI Jinxin, CHI Yaolei, ZHANG Zhonghang. Research on Gearbox Fault Diagnosis Based on CEEMDAN Adaptive Wavelet Noise Reduction and Convolution Neural Network[J]. Machine Tool & Hydraulics,2022,50(24):171-180