人工神经网络
无损检测
计算机科学
自然(考古学)
人工智能
结构工程
工程类
地质学
物理
量子力学
古生物学
标识
DOI:10.1243/pime_proc_1995_209_238_02
摘要
An effective and reliable damage assessment methodology is a valuable tool for the timely determination of damage and the deterioration stage of structural members as well as for non-destructive testing (NDT). In this work artificial neural networks are used to identify the approximate location of damage through the analysis of changes in the natural frequencies. At first, a methodology for the use of artificial neural networks for this purpose is described. Different ways of pre-processing the data are discussed. The proposed approach is illustrated through the simulation of a free-free beam with a crack whose natural frequencies were obtained experimentally.
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