Nuclear Power Plant Status Diagnostics Using an Artificial Neural Network

1992 ◽  
Vol 97 (3) ◽  
pp. 272-281 ◽  
Author(s):  
Eric B. Bartlett ◽  
Robert E. Uhrig
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Artificial Neural

Condition Monitoring of a Nuclear Power Plant Check Valve Based on Acoustic Emission and a Neural Network

2005 ◽  
Vol 127 (3) ◽  
pp. 230-236 ◽  
Author(s):  
Min-Rae Lee ◽  
Joon-Hyun Lee ◽  
Jung-Teak Kim
Keyword(s):  
Neural Network ◽  
Acoustic Emission ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Condition Monitoring ◽  
Nuclear Power ◽  
Failure Modes ◽  
Check Valve ◽  
Flow Loop ◽  
Artificial Neural

The analysis of acoustic emission (AE) signals produced during object leakage is promising for condition monitoring of the components. In this study, an advanced condition monitoring technique based on acoustic emission detection and artificial neural networks was applied to a check valve, one of the components being used extensively in a safety system of a nuclear power plant. AE testing for a check valve under controlled flow loop conditions was performed to detect and evaluate disk movement for valve degradation such as wear and leakage due to foreign object interference in a check valve. It is clearly demonstrated that the evaluation of different types of failure modes such as disk wear and check valve leakage were successful by systematically analyzing the characteristics of various AE parameters. It is also shown that the leak size can be determined with an artificial neural network.

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