Development of damage detection methods in containment building using system identification

This study presents an SI-based damage detection schemes using minimization of an error function. The singular value decomposition is utilized to investigate the instability of the SI. The Tikhonov regularization scheme is introduced to alleviate oscillations in the solutions of the SI. The optimal regularization factor is determined by the GMS and the GGMS. The characteristics of measurement error are investigated. The regularization effect is estimated by the concept of the error level and the resolution limit. The statistical approach is employed for reliable damage detection. The Monte-Carlo simulation is performed by the artificially perturbed data. The statistical distribution of system parameters obtained by the Monte-Carlo simulation is utilized in the hypothesis test for the damage detection. The validity and effectiveness of the proposed method is demonstrated through three types of numerical examples identification of an inclusion in a plate, determination of prestress losses in a containment building and damage detection in a containment building