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Improved key performance indicator-partial least squares method for nonlinear process fault detection based on just-in-time learning

  • Published:2023-01 Issue:1 Volume:360 Page:1-17
  • ISSN:0016-0032
  • Container-title:Journal of the Franklin Institute
  • language:en
  • Short-container-title:Journal of the Franklin Institute

Author:

Lin Xuning,Sun Rongrong,Wang YouqingORCID

Funder

China National Funds for Distinguished Young Scientists

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Applied Mathematics,Computer Networks and Communications,Signal Processing,Control and Systems Engineering

Reference32 articles.

1. Survey on recursive statistical process monitoring methods;Wang;Can. J. Chem. Eng.,2022

2. Gear fault diagnosis based on variational modal decomposition and wide+ narrow visual field neural networks;Wang;IEEE Trans. Autom. Sci. Eng.,2021

3. Fault detection for dynamic processes based on recursive innovational component statistical analysis;Ma;IEEE Trans. Autom. Sci. Eng.,2022

4. Recursive correlative statistical analysis method with sliding windows for incipient fault detection;Qin;IEEE Trans. Ind. Electron.,2021

5. An analytical partial least squares method for process monitoring;Qin;Control Eng. Pract.,2022

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