Adversarial adaptive 1-D convolutional neural networks for bearing fault diagnosis under varying working condition

1 May 2018Bo ZhangWei LiJie HaoXiao-Li LiMeng Zhang

Traditional intelligent fault diagnosis of rolling bearings work well only under a common assumption that the labeled training data (source domain) and unlabeled testing data (target domain) are drawn from the same distribution. However, in many real-world applications, this assumption does not hold, especially when the working condition varies... (read more)

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