Fault Diagnosis Method Based on High Precision CRPF under Complex Noise Environment


Jinhua Wang, Jie Cao, Journal of Information Processing Systems Vol. 16, No. 3, pp. 530-540, Jun. 2020  

https://doi.org/10.3745/JIPS.01.0053
Keywords: Cost Reference Particle Filter (CRPF), Fault diagnosis, resampling, Time-Varying Noise
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Abstract

In order to solve the problem of low tracking accuracy caused by complex noise in the fault diagnosis of complex nonlinear system, a fault diagnosis method of high precision cost reference particle filter (CRPF) is proposed. By optimizing the low confidence particles to replace the resampling process, this paper improved the problem of sample impoverishment caused by the sample updating based on risk and cost of CRPF algorithm. This paper attempts to improve the accuracy of state estimation from the essential level of obtaining samples. Then, we study the correlation between the current observation value and the prior state. By adjusting the density variance of state transitions adaptively, the adaptive ability of the algorithm to the complex noises can be enhanced, which is expected to improve the accuracy of fault state tracking. Through the simulation analysis of a fuel unit fault diagnosis, the results show that the accuracy of the algorithm has been improved obviously under the background of complex noise.


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Cite this article
[APA Style]
Wang, J. & Cao, J. (2020). Fault Diagnosis Method Based on High Precision CRPF under Complex Noise Environment. Journal of Information Processing Systems, 16(3), 530-540. DOI: 10.3745/JIPS.01.0053.

[IEEE Style]
J. Wang and J. Cao, "Fault Diagnosis Method Based on High Precision CRPF under Complex Noise Environment," Journal of Information Processing Systems, vol. 16, no. 3, pp. 530-540, 2020. DOI: 10.3745/JIPS.01.0053.

[ACM Style]
Jinhua Wang and Jie Cao. 2020. Fault Diagnosis Method Based on High Precision CRPF under Complex Noise Environment. Journal of Information Processing Systems, 16, 3, (2020), 530-540. DOI: 10.3745/JIPS.01.0053.