基于改进遗传算法的桥梁结构损伤识别应用研究

Improved Genetic Algorithm for Bridge Damage Detection

提出了一种基于残余力向量和改进遗传算法的桥梁结构损伤识别方法。在无噪声的情况下,使用任意一阶模态数据,残余力向量法都能够对损伤进行准确定位。但是,振动测试数据中往往包含噪声,导致运用残余力向量法进行损伤识别完全不可行。考虑到这个问题,在常规模态分析的基础上,以节点的残余力向量构造目标函数,提出了一种用于遗传搜索优化的目标函数形式。利用改进遗传算法重点进行了噪声条件下的结构损伤定位和定量研究,并对遗传算法的参数选取问题进行了深入探讨。遗传算法的主要改进包括:采用浮点编码、采用基于标准化几何分布排名的选择策略、采用最优保存策略、采用算术交叉算子、采用自适应变异算子。最后,本文用一个连续梁桥模型进行了数值模拟,验证了所提出方法的有效性,并对方法应用中存在的一些问题进行了深入探讨。

A combined method based on residual forces and improved genetic algorithm (GA) for bridge damage detection is presented. The residual forces method can accurately localize the structural damage with any order of the noise-free modal measurements, where the unavoidable noise prevents the complete damage identification, Based on the conventional modal analysis theory, a new formulation of the objective function for GA, constructed by the residual forces at the nodes, is presented, the localization and quantification of the structural damage with noise are further performed with GA. The improvements on GA include the adoption of real-valued representation, normalized geometric ranking operator, elitist model, arithmetical crossover operator and adaptive mutation operator. An example of a continuous beam bridge model is illustrated to demonstrate the effectiveness of the proposed method.