Mechanical Fault Detection Method Based on Acoustic Characteristics and Auto-encoder
When detecting mechanical faults in the industry,only a small amount or no fault data will increase the detection difficulty and reduce the detection accuracy.To solve this problem,a mechanical equipment fault detection method is proposed based on the fusion acoustic features and auto-encoder.First,the potential features of the auto-encoder are set to 8,and its network structure is optimized.Then MSE is used as its reconstruction error function.Finally,MFCC and MAF are used as input features re-spectively.The results show that compared with BS,the method proposed in this paper can improve the average AUC and the aver-age pAUC while reducing the number of training,which can be completed better in fault detection tasks.
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