.png){kind=icon}
返回
Crack detection in beam-like structures using genetic algorithms
.png){kind=icon}
PRE
AI
DOI：10.1016/j.asoc.2007.10.003.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A fault diagnosis method based on genetic algorithms (GAs) and a model of damaged ( cracked) structure is proposed. For modeling the cracked-beam structure an analytical model of a cracked cantilever beam is utilized and natural frequencies are obtained through numerical methods. Our method utilizes genetic algorithms to monitor the possible changes in the natural frequencies of the structure. The identification of the crack location and depth in the cantilever beam is formulated as an optimization problem, and binary and continuous genetic algorithms (BGA, CGA) are used to find the optimal location and depth by minimizing the cost function which is based on the difference of measured and calculated natural frequencies. Also we present a new cost function based on natural frequencies. The average values of location and depth prediction errors are 1.02% and 1.98%, respectively, using the BGA. These values become 0.73% and 1.11% for the CGA. To validate the proposed method and investigate the modeling and measurement errors some experimental results are also included. The average values of experimental location and depth prediction errors are 10.57% and 11.19%, respectively, for the BGA. These values become 10.21% and 10.39% for the CGA. (C) 2007 Elsevier B.V. All rights reserved.
Keyword:
crack detection
health monitoring
genetic algorithms
natural frequencies
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
机构
引用论文
.png){kind=icon}
查看更多内容