Novel Fault Diagnosis Method Integrating D-L2-FDA and AdaBoost

Yang Zhao, Wei Ke, Wei Zhang, Yi Luo, Qun Xiong Zhu, Yan Lin He, Yang Zhang, Ming Qing Zhang, Yuan Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Industrial process safety has always been a concern for engineers and researchers. Fault diagnosis frameworks based on data-driven methods are prevalent and play a vital role in guaranteeing industrial process safety. However, the data collected in actual industrial production regularly exhibits high-dimensional and complex timing characteristics. In this research, a new framework for fault diagnosis is constructed on the strength of dynamic L2-norm normalized fisher discriminant analysis (FDA) integrating with AdaBoost. Firstly, timing characteristic in industrial process is taken into account so that a dynamic fault dataset is constructed. Then, the FDA vectors are normalized by L2-norm and utilized to reduce data dimension which can learn fault patterns in feature extraction. In addition, an ensemble learning method named AdaBoost is adopted for pattern classification. To verify the effectiveness of the proposed method, simulation experiments based on Tennessee Eastman process are carried out and satisfactory results are obtained.

Original languageEnglish
Title of host publicationAdvanced Computational Intelligence and Intelligent Informatics - 8th International Workshop, IWACIII 2023, Proceedings
EditorsBin Xin, Naoyuki Kubota, Kewei Chen, Fangyan Dong
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9789819975891
Publication statusPublished - 2024
Event8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2023 - Beijing, China
Duration: 3 Nov 20235 Nov 2023

Publication series

NameCommunications in Computer and Information Science
Volume1931 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2023


  • AdaBoost
  • D-L2-FDA
  • Feature Extraction
  • Tennessee Eastman Process


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