A Decision-Making Method for Machinery Abnormalities Based on Neural Network Prediction and Bayesian Hypothesis Testing
For anomaly identification of predicted data in machinery condition monitoring, traditional threshold methods have problems during residual testing. It is difficult to make decisions when the residuals are close to the threshold and fluctuate. This paper proposes a Bayesian dynamic thresholding meth...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
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Series: | Electronics |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-9292/10/14/1610 |