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Volume 42 Issue 10
Oct.  2016
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Journal of Beijing University of Aeronautics and Astronautics  > 2016  >  42(10): 2099-2106.
JIANG Dongnian, LI Wei. Fault diagnosis of particle filter nonlinear systems based on adaptive threshold[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(10): 2099-2106. doi: 10.13700/j.bh.1001-5965.2015.0611(in Chinese)
Citation: JIANG Dongnian, LI Wei. Fault diagnosis of particle filter nonlinear systems based on adaptive threshold[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(10): 2099-2106. doi: 10.13700/j.bh.1001-5965.2015.0611(in Chinese)
shu

Fault diagnosis of particle filter nonlinear systems based on adaptive threshold

doi: 10.13700/j.bh.1001-5965.2015.0611
  • 1.

    College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China

  • 2. Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou 730050, China

Funds:  National Natural Science Foundation of China (61364011); Natural Science Foundation of Gansu Province of China (2015GS05221)
  • Received Date: 17 Sep 2015
  • Publish Date: 20 Oct 2016
    Abstract
  • In view of the problem of actual nonlinear system that the traditional method is difficult to obtain reliable fault diagnosis, this paper uses the particle filter method and applies the logarithm likelihood function as evaluation index to study the nonlinear non-Gaussian system fault detection and fault isolation with the aid of adaptive threshold design. The selection of threshold value is the criterion for accurately judging system failure. This paper analyzes the statistical properties of residual error, determines the residual error statistical property of normal distribution, and designs an adaptive threshold method based on particle filter fault diagnosis, which reduce the miss alarm and false alarm ratios of fault diagnosis. Through the simulation example of non-constant temperature continuous stirred tank reactor, the accuracy and feasibility of this method in fault diagnosis are verified.

     

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