Robust Self-Supervised Model and Its Application for Fault Detection-Reference-Cited by-同舟云学术

Robust Self-Supervised Model and Its Application for Fault Detection

Published:2017-06-26 Issue:26 Volume:56 Page:7503-7515
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Jiang Li¹,Song Zhihuan¹^ORCID,Ge Zhiqiang¹^ORCID,Chen Junghui²^ORCID

Affiliation:

1. State Key Laboratory of Industrial Control Technology, Institute of Industrial Process Control, Department of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, P. R. China

2. Department of Chemical Engineering, Chung-Yuan Christian University, Chung-Li 320, Taiwan ROC

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.7b00949

Reference18 articles.

1. A review of process fault detection and diagnosis

2. Review of Recent Research on Data-Based Process Monitoring

3. Survey on data-driven industrial process monitoring and diagnosis

4. Nonlinear process monitoring using kernel principal component analysis

5. Nonlinear process monitoring based on linear subspace and Bayesian inference

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