期刊
SENSORS AND ACTUATORS A-PHYSICAL
卷 132, 期 2, 页码 557-566出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.sna.2005.12.035
关键词
bonding integrity; impact acoustics; acceleration sounds; artificial neural network
The objective of this paper is to investigate the acoustics characteristics obtained from impact sounds excited by impact on tiled-walls and hence to develop a rapid, effective and robust non-destructive evaluation method for bonding integrity inspection. Most of the previous research on impact acoustics evaluation relies on the frequency-domain characteristics of the free-vibration component of impact sounds for detection and feature extraction. This method proves to be too sensitive to the surface roughness of the practical structures. In the present work, special attention is paid to the time-domain acoustics to present a solution tolerant of high surface non-uniformity. Based on the impact dynamics analysis, the relationship between the acceleration and ringing components of impact sounds and the corresponding bonding state is firstly clarified. Investigation performed on the pattern of the initial acceleration component in the time record reveals its effectiveness in indicating the existence of bonding defects in tile-walls with satisfactory immunity to surface roughness. By properly selecting the feature vectors extracted from the initial acceleration peaks of the impact sounds, a multilayer back-propagation artificial neural network (ANN) classifier is developed for automatic health monitoring of the tile-walls. The inspection results obtained experimentally on sample slabs are presented and discussed, confirming the validity of the proposed method. (c) 2006 Published by Elsevier B.V.
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