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Nonlinear Quality-Related Fault Diagnosis

  • Shen Yin*
  • , Guang Wang
  • , Kaitao Chen
  • , Anjie Wang
  • *Corresponding author for this work
  • Norwegian University of Science and Technology
  • North China Electric Power University

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Over the past decade, quality-related fault detection and diagnosis, as an important branch of multivariate statistical process monitoring, has become a critical component of industrial process monitoring. As one of the pioneering research teams in this field, we have achieved significant research outcomes. In particular, we have proposed many effective methods in nonlinear quality-related fault modeling, detection, isolation, and root cause analysis. In this chapter, we will provide a detailed summary and review of these methods and validate them through simulations using numerical examples and industrial case studies. We hope this will serve as a valuable reference for future research.

Original languageEnglish
Title of host publicationLecture Notes in Control and Information Sciences
PublisherSpringer Science and Business Media Deutschland GmbH
Pages463-519
Number of pages57
DOIs
StatePublished - 2026
Externally publishedYes

Publication series

NameLecture Notes in Control and Information Sciences
Volume148
ISSN (Print)0170-8643
ISSN (Electronic)1610-7411

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