Signal processing schemes for Eddy Current Testing of steam generator tubes of nuclear power plants

被引:15
|
作者
Tian, Shuxia [1 ]
Chen, Zhenmao [1 ]
Ueda, Masashi [2 ]
Yamashita, Takuya [2 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Strength & Vibrat Mech Struct, Xian 710049, Peoples R China
[2] JAEA, Int Cooperat & Technol Dev Ctr, Tsuruga, Fukui 9191279, Japan
基金
中国国家自然科学基金;
关键词
NEURAL-NETWORK; INSPECTION; ECT;
D O I
10.1016/j.nucengdes.2011.12.033
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
In this paper, signal processing schemes developed for upgrading the Eddy Current Testing system utilized for In-Service Inspection of Steam Generator (SG) tubes of a Fast Breeder Reactor nuclear power plant are presented. Schemes for the wobbling noise recognition, signal indication extraction, defect signal classification, and the separation of mixed signals are proposed, and are applied to both signals measured in a SG mock-up and signals measured with short tube test-pieces in a laboratory environment. The signal indications are extracted based on a wavelet decomposition and threshold value approach in addition with the signal similarity and signal distance information in case of support plate signals. As it is possible for the position of a signal point to be adjusted based on the signature of the support plates, signals of a welding joint or a bending zone can be recognized based on the design or/and manufactory information. The mixed signals of defects and support plate are processed with the similarity analysis strategy and the identification of defect signals is performed by means of both a neural network approach and a statistic method. Satisfactory extraction and classification results are obtained for all the measured signals, which validated the efficiency of the proposed schemes. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:78 / 88
页数:11
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