TY - JOUR ID - 3775 TI - Damage Detection of Structures Using Blind Source Separation and Multifractal Detrend Fluctuation Analysis JO - Amirkabir Journal of Civil Engineering JA - CEEJ LA - en SN - 2588-297X AU - Darvishan, Ehsan AD - Assistant Professor, Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran Y1 - 2021 PY - 2021 VL - 53 IS - 4 SP - 1367 EP - 1382 KW - Structural health monitoring KW - damage detection KW - signal processing KW - Cross wavelet transform KW - Support Vector Machine DO - 10.22060/ceej.2020.16919.6392 N2 - In this paper, a damage detection technique is proposed based on multifractal detrended fluctuation analysis and blind source separation. In the first stage, the accuracy of three methods of blind source separation is compared and the most efficient method in decomposing structural vibration signals is selected. These methods include blind modal identification, combined method, and sparse coding. Three structural models are employed to investigate the  of the procedures which consists of a range of numerical SDOF models with a limited degree of freedom to real structures. In the second stage, a damage index is proposed based on the width of the multifractal spectrum. Results show that the aforementioned method can identify various damage patterns and can detect slight damages. UR - https://ceej.aut.ac.ir/article_3775.html L1 - https://ceej.aut.ac.ir/article_3775_1d23454f3015bb3628a4e6646497b393.pdf ER -