烟台大学学报（自然科学与工程版）2013，Vol.26Issue(3)：207-211,5.
时间序列与主成分分析的结构损伤识别
Structural Damage Identification Based on Time Series and Principal Component Analysis
摘要
Abstract
Structural damage identification based on the principal component analysis method for the root mean squared error (RMSE) of auto regressive (AR) model is proposed in this paper.Firstly,the AR model is established by using dynamic responding data,and the RMSE of AR model is calculated.The loading matrix is obtained from principal component analysis,and the damage characteristic index is obtained through standardized processing of the loading matrix.The damage is located by comparing with the damage characteristic index resulted from sensors placed in different positions of a structure.Finally,based on a series of experimental data of a three-story frame structure model of the Los Alamos National Laboratory,the damage states are detected with two methods,namely the presented method and the AR model coefficient method.A comparison shows that the present method can lead to less amount of computing time,high suitability and identification accuracy,because the principal component analysis eliminates external interference.关键词
损伤识别/框架结构/时间序列/主成分分析/AR模型Key words
damage identification/ frame structur/ time series/ principal component analysis/ AR model分类
建筑与水利引用本文复制引用
朱旭,逯静洲,徐娜,陈林..时间序列与主成分分析的结构损伤识别[J].烟台大学学报（自然科学与工程版）,2013,26(3):207-211,5.基金项目
山东省自然科学基金资助项目(ZR2012EEM014). （ZR2012EEM014）
