Accurate Diagnosis of Rolling Bearing Based on Wavelet Packet and RBF Neural Networks
WANG Guofeng, WANG Ziliang, QIN Xuda, WANG Taiyong Mechanical Engineering School, Tianjin University, Tianjin 300072, China Tianjin University of Technology, Tianjin 300191, China
The accurate diagnosis of rolling bearing was studied. The wavelet packet analysis was used to abstract the characteristic of signals. The signals were decomposed into eight frequency bands and the information in the high band was used as a characteristic vector. RBF neural networks were used to realize the map between the feature and diagnosis. The analysis of data sampled form a workshop testified correctness of the method proposed.