采用主成分分析与最邻近法的复合材料板损伤检测实验

A Better Experimental Method for Damage Detection of Composite Plate Using Principal Component Analysis(PCA) and Nearest Neighbor Principle

文章采用主成分分析结合最邻近法对复合材料板进行了损伤检测实验。首先在正弦扫频激励下,通过测试获得复合材料板在各种损伤工况下的频响函数;然后选取若干种损伤工况的频响函数,经过主成分分析法处理后,提取出各个频响函数携带结构健康状态信息最多的前若干阶主成分,组成最邻近法的样本集;最后采用最邻近法来识别被检测结构频响函数所代表的结构健康状态。该方法的优点是直接利用测试得到的频响函数进行损伤检测,避免了识别结构模态参数所带来的误差,检测过程简单。通过对复合材料板结构不同位置和不同程度损伤的检测实验,验证了该方法用于复合材料层合结构损伤检测的可行性和有效性。

Aim.The introduction of the full paper reviews Refs.3 through 7 and points out what we believe to be their respective deficiencies;then,we propose what we believe to be a better method.We explain our method in sections 1,2 and 3,whose core consists of：（1） we used the frequency response functions（FRFs） of the intact and damaged plates as input data and measured the FRFs of specific nodes of the composite plates by sweeping sinusoidal excitation;（2） we applied the PCA method to reducing the number of dimensions of the FRFs and used,instead of raw FRFs data,as training sample sets in the nearest neighbor principle,the first 13 orders of their principal components which contain the majority of structural health information;（3） we used the nearest neighbor principle to recognize the damage states of the tested FRFs of the composite plates.Section 4 presents the damage detection results of three training sample sets;the detection results,given respectivedly in Tables 2,3 and 4,and their analysis show preliminarily that our damage detection method can correctly and effectively detect the damage state of a composite plate.