摘要
小波分析和人工神经网络的引入,让检测得到了从定性到定量的提高。运用小波分析从超声波检测装置提取的信号,得到的特征值可作为神经网络的输入参数,用于训练和识别,实践表明,通过这种智能诊断系统可以得到令人满意的定量诊断结果。
This paper covers ultrasonic quantitative testing of harbor crane structure crack based on wavelet analysis and Artificial Neural Networks （ANN） . Eigenvalues are obtained by wavelet analyzing the signal from ultrasonic instrument, which is used as ANN input for training and identifying. Actual running shows that the intelligent diagnosing system given in this paper delivers satisfying diagnosis results.
出处
《起重运输机械》
北大核心
2008年第10期94-97,共4页
Hoisting and Conveying Machinery
