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Decentralized Modified Autoregressive Models for Fault Detection in Dynamic Processes

  • Published:2018-11-09 Issue:46 Volume:57 Page:15794-15802
  • ISSN:0888-5885
  • Container-title:Industrial & Engineering Chemistry Research
  • language:en
  • Short-container-title:Ind. Eng. Chem. Res.

Author:

Tong Chudong1ORCID,Lan Ting1,Yu Haizhen1,Shi Xuhua1

Affiliation:

1. Faculty of Electrical Engineering & Computer Science, Ningbo University, Ningbo 315211, P.R. China

Funder

Ministry of Education of the People's Republic of China

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

K.C.Wong Magna Fund, Ningbo University

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

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1. Condition Process Monitoring for Thermal Process Based on Local Normal Space Alignment;2023 3rd International Conference on Energy Engineering and Power Systems (EEPS);2023-07-28

2. Abnormal Condition Monitoring Based on Multiview Data Collaborative Feature Regression;IEEE Transactions on Instrumentation and Measurement;2023

3. Local coordinates and global structure preservation for fault detection and diagnosis;Measurement Science and Technology;2021-07-21

4. Low-Rank Joint Embedding and Its Application for Robust Process Monitoring;IEEE Transactions on Instrumentation and Measurement;2021

5. Nonlinear process monitoring based on decentralized generalized regression neural networks;Expert Systems with Applications;2020-07
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