Fault Feature Recovery With Wasserstein Generative Adversarial Imputation Network With Gradient Penalty for Rotating Machine Health Monitoring Under Signal Loss Condition-Reference-Cited by-同舟云学术

Fault Feature Recovery With Wasserstein Generative Adversarial Imputation Network With Gradient Penalty for Rotating Machine Health Monitoring Under Signal Loss Condition

Published:2022 Issue: Volume:71 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Hu Wenyang¹^ORCID,Wang Tianyang¹^ORCID,Chu Fulei¹^ORCID

Affiliation:

1. Department of Mechanical Engineering, State Key Laboratory of Tribology, Tsinghua University, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09760390.pdf?arnumber=9760390

Reference43 articles.

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3. InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets;chen;Adv Neural Inf Process Syst,2016

4. Wasserstein generative adversarial networks;arjovsky;Proc 34th Int Conf Mach Learn,2017

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