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- W2894623700 abstract "This paper utilizes convolutional neural network (CNN) combining generalized S transform denoising (GSTD) method to complete noisy bearing fault diagnosis. After GSTD, images with more obvious failure information can be obtained. Then these feature images are trained by convolutional neural network. The recognition accuracy of the proposed method on testing dataset achieves as high as 99.25%. Finally, the proposed method is compared with other diagnosis methods to prove its effectiveness in processing noise signal." @default.
- W2894623700 created "2018-10-12" @default.
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- W2894623700 date "2018-10-04" @default.
- W2894623700 modified "2023-10-18" @default.
- W2894623700 title "Bearing Fault Diagnosis Based on Generalized S Transform Denoising and Convolutional Neural Network" @default.
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- W2894623700 doi "https://doi.org/10.1007/978-981-13-2291-4_42" @default.
- W2894623700 hasPublicationYear "2018" @default.
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