损伤识别系统中小波包信号特征量的提取  

Drawing of the Wavelet Package Signal Energy Eigenvalue in Damage Recognition System

作　　者：信思金[1] 舒丹[2] 梁磊[1] 蒋冬青[3] 

机构地区：[1]武汉理工大学光纤传感技术中心,湖北武汉430070 [2]武汉理工大学信息工程学院,湖北武汉430070 [3]湖南建材高等专科学校,湖南衡阳421008

出　　处：《河南科技大学学报（自然科学版）》2006年第2期29-32,共4页Journal of Henan University of Science And Technology:Natural Science

基　　金：国家自然科学基金项目(50179029)

摘　　要：基于结构损伤识别系统,构建了耦合神经网络模型,阐述了小波包分析技术的原理和方法,对小波基的选取原则进行了分析和探讨,确定了小波基函数DbN中的N以及小波包分解尺度j;从模式识别的观点对结构损伤识别进行了分析,分析了小波包信号能量特征提取的方法。利用小波包多分辨率的特点,提出了以小波包信号成分能量特征向量为结构损伤识别的损伤特征指标,并在实验中得到了良好的识别效果。Based on the structural damage recognition system, the coupled neural network model is constructed, the principles and methods of wavelet package analysis technology expatiated, and the principles of wavelet base selection analyzed and discussed. N of wavelet base function DbN and j of wavelet package decomposed scale are ascertained. The structural damage recognition is studied with the mode identification method, and the method for drawing the wavelet package signal energy eigenvalue is analyzed. Based on the multiresolution trait of wavelet package, it is proposed that the wavelet package signal component energy eigenvector be used as damage index property of structural damage recognition. Experiments show that the method can achieve a fairly good recognition effect.

关 键 词：小波包分析 神经网络 损伤识别 光纤光栅传感器 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP212.14[自动化与计算机技术—控制科学与工程]