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Structural damage detection using principal component analysis of frequency response function data
Author(s) -
Esfandiari Akbar,
Nabiyan MansurehSadat,
Rofooei Fayaz R.
Publication year - 2020
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2550
Subject(s) - sensitivity (control systems) , truss , principal component analysis , frequency response , identification (biology) , function (biology) , frame (networking) , relation (database) , mathematics , algorithm , control theory (sociology) , computer science , structural engineering , engineering , data mining , statistics , artificial intelligence , electronic engineering , telecommunications , botany , electrical engineering , control (management) , evolutionary biology , biology
Summary In this paper, a new sensitivity‐based model updating method is presented based on the changes of principal components (PCs) of frequency response function (FRF). Structural damage estimation, identification of damage location and severity, is conducted by an innovative sensitivity relation. The sensitivity relation is derived by incorporating PC analysis (PCA) data obtained from the incomplete measured structural responses in a mathematical formulation and is then solved by the least square method. In order to demonstrate the performance of the proposed method, it is applied to a truss and a frame model. The results prove the ability of the method as a robust damage detection algorithm in the presence of measurement and mass modeling errors. The comparative studies prove that the results obtained by the proposed sensitivity relation are more accurate than the results based on using FRF data directly.