Coal Mining Machine Rolling Bearing Failure Prediction Model Design and Test
Underground coal mining machine has complex structure and poor working environment,which is prone to various kinds of faults and difficult to dispose of.To meet the demand of rolling bearing fault diagnosis of MG620/1660-WD electric traction coal mining machine,combined with the principle of EEMD vibration signal pre-processing and noise reduction,a fault prediction model based on deep learning is designed,and data training and model testing are implemented,and the test results show that the fault screening accuracy of the prediction model reaches 96.8％,and the fault prediction is highly reliable,which achieves the expected research purpose.research purpose.
coal mining machine rolling bearingfault diagnosisfault prediction modeldeep learningsignal preprocessing
NETL
NSTL
万方数据
