Literature DB >> 28372799

Fault prediction for nonlinear stochastic system with incipient faults based on particle filter and nonlinear regression.

Bo Ding1, Huajing Fang2.   

Abstract

This paper is concerned with the fault prediction for the nonlinear stochastic system with incipient faults. Based on the particle filter and the reasonable assumption about the incipient faults, the modified fault estimation algorithm is proposed, and the system state is estimated simultaneously. According to the modified fault estimation, an intuitive fault detection strategy is introduced. Once each of the incipient fault is detected, the parameters of which are identified by a nonlinear regression method. Then, based on the estimated parameters, the future fault signal can be predicted. Finally, the effectiveness of the proposed method is verified by the simulations of the Three-tank system.
Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Keywords:  Fault detection; Fault prediction; Incipient fault; Nonlinear regression; Nonlinear stochastic system; Particle filter

Year:  2017        PMID: 28372799     DOI: 10.1016/j.isatra.2017.03.018

Source DB:  PubMed          Journal:  ISA Trans        ISSN: 0019-0578            Impact factor:   5.468


  1 in total

1.  Fault Critical Point Prediction Method of Nuclear Gate Valve with Small Samples Based on Characteristic Analysis of Operation.

Authors:  Zhilong Liu; Jie Liu; Yanping Huang; Tongxi Li; Changhua Nie; Yanjun Xia; Li Zhan; Zhangchun Tang; Lin Zhang
Journal:  Materials (Basel)       Date:  2022-01-19       Impact factor: 3.623

  1 in total

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