In this paper,a bearing fault diagnosis method based on vibration signal for belt conveyor is proposed.Firstly,bearing vibration signal is collected by displacement sensor.Secondly,wavelet transform is used to extract the features of vibration signals in time-frequency domain to capture the local features of signals at different frequencies and time scales.Finally,decision tree method is used to classify the extracted feature vectors to realize the identification of different bearing fault types.Based on Case Western Reserve University bearing data set,the validity and robustness of the proposed method are verified by experiments.
关键词
带式运输机/轴承/振动信号/故障诊断/决策树
Key words
belt conveyor/bearings/vibration signal/fault diagnosis/decision tree
维普
万方数据