Automatic Fault Diagnosis of Planetary Gearbox Based on Improved Transfer Learning
The traditional machine learning fault diagnosis method relies on professional experience to select statistical features,the diagnosis results are greatly affected by human factors.Therefore,the automatic fault diagnosis of planetary gear boxes based on improved transfer learning is proposed.The vibration signal of the planetary gearbox is collected,the vibration signal is denoised,and the deep learning is improved by transfer learning to build the fault diagnosis model,classify and identify the collected signal,and realize the automatic fault diagnosis of the planetary gearbox.The results show that the fault diagnosis accuracy of different types of planetary gearbox is 96.09％,which confirms the good performance of this method.
improved transfer learningplanetary gearboxfault diagnosisautomatic diagnosis method
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