基于频响函数的结构状态识别神经网络方法

Structure State Identification by Neural Network Based on Frequency Response Function

用神经网络BP算法直接对所测结构频响函数进行分析,用来识别结构的状态。给出了一个tansig/purelin应用的例子,比较了两种网络,发现newff比newcf能够获得更好的识别效果。结果也表明,与基于特征值分析的方法相比,数据处理的方法更加简单,可以进行状态的分类识别。

This paper presents a Back-Propagation network method(BP network) applying structure frequency response function as the network inputs.The method is proposed to identify a structure's state information.A example is given in detail,in which a two-layer tansig/purelin network is used.Two kinds of networks are compared,the newff network tends to give a more reasonable answer than the newcf network.And the results show that the method is more simple,correct and effective than other methods such as the eigenvalue analysis.