JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (5): 44-50.doi: 10.6040/j.issn.1672-3961.0.2017.171

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A fault detection method based on modified canonical correlation analysis

CHEN Zhiwen1, PENG Tao1*, YANG Chunhua 1, HE Zhangming2, YANG Chao1, YANG Xiaoyue1   

  1. 1. School of Information Science and Engineering, University of Central South, Changsha 410083, Hunan, China;
    2. College of Science, National University of Defense Technology, Changsha 410083, Hunan, China
  • Received:2017-04-18 Online:2017-10-20 Published:2017-04-18

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Abstract: In order to improve the effectiveness of the fault detection(FD)method based on standard canonical correlation analysis(CCA), the original residual generation was modified. By analyzing the statistical characteristics of the residual signal and changing the residual generation mode, the improved residual generation method did not depend on the selection of the number of principal components, so that the fault detection performance would be free of such a selection. The proposed method was further applied to the Tennessee Eastman benchmark process, in which four typical faults were simulated. The achieved results showed that the proposed method could successfully detect the faults. Due to the different fault sensitivity of the two test statistics, it could be found that the fault detectability of the two test statistics were different.

Key words: data-driven, canonical correlation analysis, Tennessee Eastman process, fault detection

CLC Number: 

  • TP206+.3
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