Research on Vibration Information Decomposition and Fault Diagnosis of Coal Mining Machine Based on Sample Entropy
In order to diagnose the faults of coal mining machine,we start from the rolling bearings of the cutting drum in this machine.Firstly,a vibration signal decomposition method based on sample entropy is designed,which combines empirical modal decomposition and time-varying filtering.Secondly,the filtering criterion of the component signals is constructed and the calculation of different criteria is explained.The results show that the errors between the test values and the real values are 0.0 5 Hz and 0.17 Hz for the inner ring and 1.89 Hz and 2.11 Hz for the rolling element,respectively.The decomposition method designed by the study is able to provide a more complete retention of the fault characteristic information,and the diagnostic method has a smaller error in the identification of the fault frequency,which is able to provide technical support for the diagnosis of the faults of rolling bearings.
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