Bridge damage identification by finite element model updating with Tikhonov regularization and wavelet denoising

This paper develops a damage identification method by finite element model updating with Tikhonov regularization and wavelet denoising based on the classic sensitivity-based model updating method. In order to improve the method a wavelet denoising treatment is proposed by using the differences between measured modes and analyzed modes of the finite element model and the objectives contructed by revised modes according to different time-frequency features between structural modal signals and noises, while the introduction of Tikhonov regularization can alleviate the ill-conditioning in solving the damage identification problems. Since the solution of damage identification inverse problem is improved at two respects: input data and calculation method, the affection of noise in the measured modal parameters can be suppressed efficiently and therefore the structure damages can be correctly identified. Numerical simulations for continuous beam model show that the proposed method can identify structural damages more accurately while preserving the robustness of the identification algorithms and suppressing the noises.