Rolling bearing fault diagnosis method based on variation mode decomposition and permutation entropy
A variational modal decomposition, rolling bearing technology, applied in mechanical bearing testing, character and pattern recognition, testing of mechanical components, etc., can solve problems such as difficulty in extracting fault feature information
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[0053] Combining the advantages of VMD on signal decomposition and permutation entropy can detect the characteristics of time series randomness and dynamic mutation, a rolling bearing fault diagnosis method based on variational mode decomposition and permutation entropy is proposed. First, the original vibration signal is decomposed by VMD to obtain several eigenmode components, and then the permutation entropy of each modal component is calculated, and finally the permutation entropy value is input as a feature vector into a Support Vector Machine (SVM) classifier for fault classification identification. The flow chart of rolling bearing fault diagnosis based on variational mode decomposition and permutation entropy is as follows: figure 1 As shown, the specific steps are as follows:
[0054] (1) Use the acceleration sensor to measure the vibration signal of the rolling bearing, collect the vibration signal of the rolling bearing in the normal state, the inner ring fault, th...
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