Study on Fault Diagnosis Method for Nuclear Power Plant Based on Fuzzy Rough Sets and Decision Tree

Yu Mu; Gui Min Sheng; Hong Xia; Pu Nan Sun; Yan Qian

doi:10.4028/www.scientific.net/AMR.981.701

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 981Study on Fault Diagnosis Method for Nuclear Power...

Study on Fault Diagnosis Method for Nuclear Power Plant Based on Fuzzy Rough Sets and Decision Tree

Abstract:

The technology of real-time fault diagnosis for nuclear power plants (NPP) has great significance to improve the safety and economy of reactor. Nuclear power plants are complex system, which collect and monitor the vast parameters. A parameter reduction method based on fuzzy rough sets was proposed. According to the characteristics the parameters were fuzzed, and they were reducted using the algorithm of forward greedy search. The decision tree was applied to learn from training samples which were the typical faults of nuclear power plant, i.e., loss of coolant accident (LOCA), feed water pipe rupture, steam generator tube rupture (SGTR), main steam pipe rupture, and diagnose by using the acquired knowledge. The result shows that this method can diagnose the faults of the NPP rapidly and accurately.

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Periodical:

Advanced Materials Research (Volume 981)

Pages:

701-705

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.981.701

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Online since:

July 2014

Authors:

Yu Mu*, Gui Min Sheng, Hong Xia, Pu Nan Sun, Yan Qian

Keywords:

Decision Tree, Fault Diagnosis, Fuzzy Rough Set, Nuclear Power Plant (NPP)

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* - Corresponding Author

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