Fault detection based on SIR state estimation and smoothed residual

Jun Liang*, Li Yan Qiao, Xi Yuan Peng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

It is often needed for many fault detection approaches based on model for stochastic systems that the model should be linear and Gaussian. But the performance of these approaches usually be awful when the model is nonlinear and non-Gaussian. Now one of the better approaches for nonlinear and non-Gaussian stochastic systems is the fault detection approach based on SIR likelihood. In this paper a novel approach named fault detection based on SIR state estimation and smoothed residual is proposed. In this approach the estimate value of the state of the nonlinear stochastic system is obtained firstly using SIR. Then the difference between these ideal observation of the estimate value and those observation of the state of the system is smoothed. The fault detection is done according to these smoothed difference. The simulation results indicate that the false alarm rate of the two approaches is like while the missing alarm rate of the novel approach is better the one of the fault detection approach based on SIR likelihood.

Original languageEnglish
Pages (from-to)32-36
Number of pages5
JournalTien Tzu Hsueh Pao/Acta Electronica Sinica
Volume36
Issue numberSUPPL. 2
Publication statusPublished - Dec 2007
Externally publishedYes

Keywords

  • Fault detection
  • Fault false alarm rate
  • Fault missing alarm rate
  • Nonlinear stochastic system
  • SIR particle filtering
  • State estimation

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Liang, J., Qiao, L. Y., & Peng, X. Y. (2007). Fault detection based on SIR state estimation and smoothed residual. Tien Tzu Hsueh Pao/Acta Electronica Sinica, 36(SUPPL. 2), 32-36.