강 구조물 접합부의 건전성 감시를 위한 램 웨이브와 확률 신경망의 적용 Application of Lamb Waves and Probabilistic Neural Networks for Health Monitoring of Joint Steel Structures

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage classs region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.
Publisher
한국소음진동공학회
Issue Date
2005-01
Language
KOR
Citation

한국소음진동공학회논문집, v.15, no.1, pp.53 - 62

ISSN
1598-2785
URI
http://hdl.handle.net/10203/14696
Appears in Collection
NE-Journal Papers(저널논문)
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