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Compensation of accuracy by increased data “thickness” for high timeliness in fault diagnosis of chemical process

  • Published:2023-11 Issue: Volume:152 Page:105178
  • ISSN:1876-1070
  • Container-title:Journal of the Taiwan Institute of Chemical Engineers
  • language:en
  • Short-container-title:Journal of the Taiwan Institute of Chemical Engineers

Author:

Rao Silin,Wang JingtaoORCID

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Tianjin University

Publisher

Elsevier BV

Subject

General Chemical Engineering,General Chemistry

Reference26 articles.

1. Chemical process fault diagnosis based on a combined deep learning method;Bao;Can. J. Chem. Eng.,2022

2. Fault diagnosis based on Fisher discriminant analysis and support vector machines;Chiang;Comput. Chem. Eng.,2004

3. Challenges in the industrial applications of fault diagnostic systems;Dash;Comput. Chem. Eng.,2000

4. A plant-wide industrial process control problem;Downs;Comput. Chem. Eng., Industrial challenge problems in process control,1993

5. An approach to fault diagnosis of chemical processes via neural networks;Fan;AIChE J,1993

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