去噪正则化模型修正方法在桥梁损伤识别中的应用

以传统基于灵敏度分析的有限元模型修正方法为基础,提出一种结合小波去噪过程的正则化模型修正损伤识别方法.为改进模型修正方法损伤识别效果,一方面利用有损结构模态与模态噪声的波形在时频域内的差异,以结构有限元模型为基准,对实测模态差进行小波去噪处理,并利用修正后的模态构造目标函数；一方面采用正则化方法改善反问题求解的非适定性.由于从输入数据和求解过程两方面同时改善了结构损伤识别反问题的求解,因此可以有效抑制实测模态参数中噪声的影响,正确识别结构损伤.以连续梁桥模型为例的损伤识别数值模拟表明,所提出方法在保持识别算法鲁棒性、抑制噪声的同时,可有效提高桥梁结构损伤的识别精度.

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.