Fault Diagnosis Based on the Updating Strategy of Interval-Valued Belief Structures

XU Xiaobin; LIU Ping; SUN Yanbo; WEN Chenglin

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Article Navigation > Chinese Journal of Electronics > 2014 > 23(4): 753-760

XU Xiaobin, LIU Ping, SUN Yanbo, et al., “Fault Diagnosis Based on the Updating Strategy of Interval-Valued Belief Structures,” Chinese Journal of Electronics, vol. 23, no. 4, pp. 753-760, 2014,

Citation:

XU Xiaobin, LIU Ping, SUN Yanbo, et al., “Fault Diagnosis Based on the Updating Strategy of Interval-Valued Belief Structures,” Chinese Journal of Electronics, vol. 23, no. 4, pp. 753-760, 2014,

XU Xiaobin, LIU Ping, SUN Yanbo, et al., “Fault Diagnosis Based on the Updating Strategy of Interval-Valued Belief Structures,” Chinese Journal of Electronics, vol. 23, no. 4, pp. 753-760, 2014,

Citation:

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Fault Diagnosis Based on the Updating Strategy of Interval-Valued Belief Structures

1.
Institute of Systems Science and Control Engineering, School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China;
2.
Department of Control Science and Engineering, School of Astronautics, Harbin Institute of Technology, Harbin 150006, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61004070, No.61374123, No.61104019, No.61034006) and the Zhejiang Province Research Program Project of Commonweal Technology Application (No.2012C21025).

Received Date: 2013-09-01
Rev Recd Date: 2013-12-01
Publish Date: 2014-10-05

Abstract

Abstract

This paper presents the dynamic method for fault diagnosis based on the updating of Interval-valued belief structures (IBSs). The classical Jeffrey's updating rule and the linear updating rule are extended to the framework of IBSs. Both of them are recursively used to generate global diagnosis evidence with the form of Interval basic belief assignment (IBBA) by updating the previous evidence with the incoming evidence. The diagnosis decision can be made by global diagnosis evidence. In the process of evidence updating, the similarity factors of evidence are used to determine switching between the extended Jeffrey's and linear updating rules, and to calculate the linear combination weights. The diagnosis examples of machine rotor show that the proposed method can provide more reliable and accurate results than the diagnosis methods based on Dempster-Shafer evidence theory.
- Fault diagnosis,
- Dempster-Shafer evidence theory,
- Interval-valued belief structures,
- Evidence updating

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References(13)

References

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