STATISTICAL DAMAGE DETECTION ON GROUPED DATA WITH STRUCTURE DYNAMIC RESPONSES
Structure statistical parameters change while damage occurs. The change contains the damage information, which is always insignificant to indicate the information even for preliminary damage existence detection. An approach is discussed in this study to amplify the damage information of the existence, location, and quantification by grouped the response data. It could be considered as a modified principal component analysis (PCA) approach on the structure modal curvatures directly without any other algorithms, which is efficient and gives a further interpret beyond the data compression. The recognition is performed based on the statistical variance matrix and the coordinate rotation of the PCA, in two single-damage scenarios with different damage ratios and in the other two multi-damage scenarios with different damage ratios. The approach provides a potential instructive structure information discrimination method, which indicates not only the damage information but also the structural characters in a straightforward illustration by data grouping.
statistical method damage detection data grouping principal component analysis
Hong-Ping Zhu Wei-Ming Li Lie-Yun Ding Han-Bin Luo
School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan 430074, P.R. China Hubei Key Laboratory of Control Structure, Huazhong University of Science and Technology, Wuhan 430074, P.R. China
国际会议
广州
英文
1266-1271
2009-11-28（万方平台首次上网日期，不代表论文的发表时间）