文章基本信息

标题：Damage detection using vibration data and dynamic transmissibility ensemble with auto-associative neural network
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作者：Yun-Lai ZHOU ; Magd Abdel Wahab
期刊名称：Mechanika
印刷版ISSN：1392-1207
出版年度：2017
卷号：23
期号：5
页码：688-695
DOI：10.5755/j01.mech.23.5.15339
语种：English
出版社：Kauno Technologijos Universitetas
摘要：In this paper, a transmissibility based damage detection methodology using artificial intelligence is proposed.Structural health monitoring requires accurate damage detection in real engineering while the environmental uncertain-ties make this a challenge.In order to reduce this effect, artificial intelligence, such as artificial neural networks might be a possible strategy for achieving a better interpretation of the monitored data during operational condition.In this study, transmissibility is taken into account as damage sensitive feature because it accounts for the response data only.Then, auto-associative neural network is employed for detecting the structural damage and predicting its severity.In order to validate our proposed technique, a ten-floor structure is simulated and studied.The results show good perfor-mance in detecting damages.
关键词：Vibration data;dynamic Transmissibility;Damage detection;Auto-associative neural network