基于不完备实测模态数据的结构损伤识别方法研究

在传统的基于模型修正的损伤识别中,由于实测模态信息有限而待识别参数过多,往往导致损伤识别方程出现较大误差,从而限制了该方法在复杂结构中的应用。为解决这一问题,对结构的自由度进行了分解,将损伤结构中模态振型的未测量部分表达为已测量到的模态振型、模态频率以及结构其它参数的函数。将损伤视为结构单元刚度的减小,利用完好结构的计算模态数据以及损伤结构扩充后的实测模态数据,建立了结构的损伤识别方程。运用信赖域优化算法对具有双重约束条件的目标函数进行最小化,识别出了结构各单元的刚度损伤参数。通过两个损伤识别数值仿真算例及实验验证,结果表明,在测点数量有限及测试噪声等不利因素影响下,所提方法只需运用少量的实测模态信息,即可实现结构损伤位置及程度的准确识别,同时算法具有较好的鲁棒性。

Structural damage detection method using incomplete measured modal data

Owing to the measured modal data is far less than the under identified parameters and the damage identification equation always have large errors, it leads to the application in complex structure is always limited in the traditional damage detection based on model updating. In this paper, the drawback is solved by dividing structural degrees of freedom into measured and unmeasured parts. Meanwhile, the unmeasured parts of the mode shapes of the damaged structure are characterized as a function of the structural parameter and measured parts of the mode shape. Considering damage as a reduction in element stiffness, then using the calculated modal data of an intact structure and the measured modal data of a damaged structure to establish the damage detect equation. The dual constrained objective function succeeds to recognize the changes in structural parameters, utilizing the trust region optimization method. The proposed method are verified by two numerical simulation cases and a damage detection experiment, the results show that it has a good ability to detect any damage of structures using incomplete measured modal data, and the algorithm also has good robustness.