Data augmentation in fault diagnosis based on the Wasserstein generative adversarial network with gradient penalty

Author:

Gao Xin,Deng FangORCID,Yue Xianghu

Funder

Beijing NOVA Program

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference27 articles.

1. Sensor multifault diagnosis with improved support vector machines;Deng;IEEE Trans. Autom. Sci. Eng.,2015

2. An improved sensor fault diagnosis scheme based on TA-LSSVM and ECOC-SVM;Gu;J. Syst. Sci. Complex.,2017

3. A novel scheme for key performance indicator prediction and diagnosis with application to an industrial hot strip mill;Ding;IEEE Trans. Ind. Inf.,2013

4. Enhanced statistical analysis of nonlinear processes using KPCA, KICA and SVM;Zhang;Chem. Eng. Sci.,2009

5. A new support vector data description method for machinery fault diagnosis with unbalanced datasets;Duan;Exp. Syst. Appl.,2016

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