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Performance Evaluation of SG Tube Defect Size Estimation System in the Absence of Defect Type Classification  

Jo, Nam-Hoon (Department of Electrical Engineering, Soongsil University)
Publication Information
Abstract
In this paper, we study a new estimation system for the prediction of steam generator tube defects. In the previous research works, defect size estimators were independently designed for each defect types in order to estimate the defect size. As a result, the structure of estimation system is rather complex and the estimation performance gets worse if the classification performance is degraded for some reason. This paper studies a new estimation system that does not require the classification of defect types. Although the previous works are expected to achieve much better estimation performance than the proposed system since it uses the estimator specialized in each defect, the performance difference is not so large. Therefore, it is expected that the proposed estimator can be effectively used for the case where the defect type classification is imperfect.
Keywords
Eddy Current Testing(ECT); Steam Generator(SG) Tube; Neural Network; Feature Extraction;
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Times Cited By KSCI : 3  (Citation Analysis)
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