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Fault Detection Method Based on Artificial Immune System for Complicated Process

  • Chunliu Xiong
  • Yuhong Zhao
  • Wei Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

Fault detection is an important problem in process engineering. A new fault detection method based on artificial immune system is developed for complicated process. Real-valued negative selection algorithm with variable–radius detectors is adopted to generate the detectors set which covers the non-self space. In order to decrease the complexity of detector generation, principal component analysis is introduced to reduce the dimension of the process data. The effectiveness of the proposed method is illustrated by the simulation on the Tennessee Eastman process.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chunliu Xiong
    • 1
  • Yuhong Zhao
    • 1
  • Wei Liu
    • 1
  1. 1.Institute of Industrial Control, Zhejiang University, Hangzhou 310027China

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