Probabilistic Fault Diagnosis Based on Monte Carlo and Nested-Loop Fisher Discriminant Analysis for Industrial Processes-Reference-Cited by-同舟云学术

Probabilistic Fault Diagnosis Based on Monte Carlo and Nested-Loop Fisher Discriminant Analysis for Industrial Processes

Published:2016-12-12 Issue:50 Volume:55 Page:12896-12908
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Zhao Chunhui¹^ORCID,Wang Wei¹,Gao Furong²^ORCID

Affiliation:

1. State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China

2. Department of Chemical and Biomolecular Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong Special Administrative Region

Funder

National Natural Science Foundation of China

State Key Laboratory of Industrial Control Technology, Zhejiang University

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.6b03221

Reference39 articles.

1. On-line fault diagnosis using the signed directed graph

2. A Multiple-Time-Region (MTR)-Based Fault Subspace Decomposition and Reconstruction Modeling Strategy for Online Fault Diagnosis

3. A branch and bound method for isolation of faulty variables through missing variable analysis

4. Analysis of smearing-out in contribution plot based fault isolation for Statistical Process Control

5. Statistical analysis and online monitoring for multimode processes with between-mode transitions

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