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Volumn 42, Issue 7, 2009, Pages 658-663

A novel feature extraction for eddy current testing of steam generator tubes

Author keywords

Eddy currents; Neural networks; Pattern recognition

Indexed keywords

CLASSIFICATION ACCURACY; DEFECT CHARACTERIZATION; DEFECT CLASSIFICATION; DEFECT SIZE; DEFECT SIZING; DEFECT TYPE; INPUT VECTOR; MULTI LAYER PERCEPTRON; PREDICTION ACCURACY; STEAM GENERATOR TUBE;

EID: 67650087611     PISSN: 09638695     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ndteint.2009.05.006     Document Type: Article
Times cited : (18)

References (9)
  • 1
    • 0032075061 scopus 로고    scopus 로고
    • A novel signal processing technique for eddy-current testing of steam generator tubes
    • Chen G., Yamaguchi A., and Miya K. A novel signal processing technique for eddy-current testing of steam generator tubes. IEEE Trans Magn 34 3 (1998) 642-648
    • (1998) IEEE Trans Magn , vol.34 , Issue.3 , pp. 642-648
    • Chen, G.1    Yamaguchi, A.2    Miya, K.3
  • 3
    • 0036643127 scopus 로고    scopus 로고
    • A generalized likelihood ratio technique for automated analysis of bobbin coil eddy current data
    • Das M., Shekhar H., Liu X., Polikar R., Ramuhalli P., Udpa L., et al. A generalized likelihood ratio technique for automated analysis of bobbin coil eddy current data. NDT&E Int 35 (2002) 329-336
    • (2002) NDT&E Int , vol.35 , pp. 329-336
    • Das, M.1    Shekhar, H.2    Liu, X.3    Polikar, R.4    Ramuhalli, P.5    Udpa, L.6
  • 4
    • 0036493311 scopus 로고    scopus 로고
    • Inverse analyses for natural and multicracks using signals from a differential transmit-receive ECT probe
    • Haoyu H., and Takagi T. Inverse analyses for natural and multicracks using signals from a differential transmit-receive ECT probe. IEEE Trans Magn 38 2 (2002) 1009-1012
    • (2002) IEEE Trans Magn , vol.38 , Issue.2 , pp. 1009-1012
    • Haoyu, H.1    Takagi, T.2
  • 5
    • 0025401737 scopus 로고
    • Eddy current defect characterization using neural network
    • Udpa L., and Udpa S.S. Eddy current defect characterization using neural network. Mater Eval 48 (1990) 342-347
    • (1990) Mater Eval , vol.48 , pp. 342-347
    • Udpa, L.1    Udpa, S.S.2
  • 6
    • 0033639481 scopus 로고    scopus 로고
    • Automatic detecting and classifying defects during eddy current inspection of riveted lap-joints
    • Lingvall F., and Stepinski T. Automatic detecting and classifying defects during eddy current inspection of riveted lap-joints. NDT&E Int 33 (2000) 47-55
    • (2000) NDT&E Int , vol.33 , pp. 47-55
    • Lingvall, F.1    Stepinski, T.2
  • 7
    • 0033891170 scopus 로고    scopus 로고
    • Eddy current flaw characterization in tubes by neural networks and finite element modeling
    • Song S.-J., and Shin Y.-G. Eddy current flaw characterization in tubes by neural networks and finite element modeling. NDT&E Int 33 (2000) 233-243
    • (2000) NDT&E Int , vol.33 , pp. 233-243
    • Song, S.-J.1    Shin, Y.-G.2
  • 8
    • 0037221009 scopus 로고    scopus 로고
    • A feature extraction technique based on principal component analysis for pulsed eddy current NDT
    • Sophian A., Tian G.Y., Taylor D., and Rudlin J. A feature extraction technique based on principal component analysis for pulsed eddy current NDT. NDT&E Int 36 (2003) 37-41
    • (2003) NDT&E Int , vol.36 , pp. 37-41
    • Sophian, A.1    Tian, G.Y.2    Taylor, D.3    Rudlin, J.4
  • 9


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.