Feature Extraction and Diagnosis Analysis of Bearing Failure in Metallurgical Machinery Based on Vibration Signal
In order to further explore the path to improve the accuracy of bearing fault diagnosis in metallurgical machinery,firstly,based on the characteristics of bearing fault signals in metallurgical machinery,we set up an acquisition platform to collect comprehensive and accurate data on the bearing fault characteristics;then,based on the acquisition results,we establish a bearing fault diagnosis method based on the vibration signals with the core of the adaptive fuzzy entropy extraction method.From the simulation analysis test results,the established fault diagnosis method has more advantages in terms of accuracy,and it is expected that it will have potential application value in the subsequent practical work of bearing fault diagnosis.
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