Fault Detection and Identification Using Modified Bayesian Classification on PCA Subspace-Reference-Cited by-同舟云学术

Fault Detection and Identification Using Modified Bayesian Classification on PCA Subspace

Published:2009-02-03 Issue:6 Volume:48 Page:3059-3077
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Liu Jialin¹,Chen Ding-Sou²

Affiliation:

1. Department of Information Management, Fortune Institute of Technology, 1-10, Nwongchang Rd., Neighborhood 28, Lyouciyou Village, Daliao Township, Kaohsiung County, Taiwan, Republic of China

2. New Materials Research & Development Department, China Steel Corporation, 1, Chung Kang Rd., Hsiao Kang, Kaohsiung, Taiwan, Republic 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/ie801243z

Reference28 articles.

1. The process chemometrics approach to process monitoring and fault detection

2. Multivariate SPC Methods for Process and Product Monitoring

3. Adaptive Fuzzy C-Means clustering in process monitoring

4. Overall Statistical Monitoring of Static and Dynamic Patterns

5. A new fault diagnosis method using fault directions in Fisher discriminant analysis

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