Study on Fault Diagnosis Technology for Nuclear Power Plants Based on Time Series Data Mining

MU Yu; XIA Hong; LIU Yongkuo

Mar. 2025

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MU Yu, XIA Hong, LIU Yongkuo. Study on Fault Diagnosis Technology for Nuclear Power Plants Based on Time Series Data Mining[J]. Nuclear Power Engineering, 2011, 32(5): 45-48.

Citation:

MU Yu, XIA Hong, LIU Yongkuo. Study on Fault Diagnosis Technology for Nuclear Power Plants Based on Time Series Data Mining[J]. Nuclear Power Engineering, 2011, 32(5): 45-48.

MU Yu, XIA Hong, LIU Yongkuo. Study on Fault Diagnosis Technology for Nuclear Power Plants Based on Time Series Data Mining[J]. Nuclear Power Engineering, 2011, 32(5): 45-48.

Citation:

MU Yu, XIA Hong, LIU Yongkuo. Study on Fault Diagnosis Technology for Nuclear Power Plants Based on Time Series Data Mining[J]. Nuclear Power Engineering, 2011, 32(5): 45-48.

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Study on Fault Diagnosis Technology for Nuclear Power Plants Based on Time Series Data Mining

1. Nuclear Safety and Simulation Technique National Defense Key Subject Laboratory; Harbin Engineering University; Harbin, 150001, China;
2. Nuclear Power Institute of China, Chengdu, 610041, China

Received Date: 2010-05-24
Available Online: 2025-03-08

Abstract

Abstract

Time series data mining is applied to the fault diagnosis for nuclear power plants.dow method is used to convert the problem to a standard supervised learning problem.Simulation experiment is carried out by LOCA.The simulation results show that the diagnostic accuracy has certain improvement when the sliding-window method is applied.Furthermore,extracting the feature of the time series data in the sliding-window,the diagnostic accuracy is improved greatly.Some problems which can not be solved by classical algorithm can be diagnosed by time series data mining method.
- Nuclear power plants,
- Fault diagnosis,
- Time series data mining,
- Sliding-window