钢筋
涡流
波形
涡流检测
材料科学
人工神经网络
振幅
结构工程
电磁线圈
信号(编程语言)
电流(流体)
声学
复合材料
工程类
电气工程
计算机科学
光学
物理
电压
人工智能
程序设计语言
作者
Junji Koido,Hiroshi Hoshikawa
出处
期刊:Review of Progress in Quantitative Nondestructive Evaluation
日期:1995-01-01
卷期号:: 841-847
被引量:1
标识
DOI:10.1007/978-1-4615-1987-4_105
摘要
Techniques for determining the covering thickness and diameter of reinforcing bars are needed in the evaluation of the existing strength of reinforced concrete structures. When eddy current testing is used with a relatively high test frequency, the covering thickness and diameter of the rebar can be determined simultaneously using relations between amplitude versus covering thickness and phase versus diameter. Neural networks were employed to estimate covering and diameter of rebar in this study. The phase waveform of the eddy signal generated by scanning the test coil along the surface of concrete was used for input data for the neural network.
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