基于改进自适应遗传算法的固定结合面动态特性参数优化识别

Optimization Identification for Dynamic Characteristics Parameters of Fixed Joints Based on Improved Adaptive Genetic Algorithm

针对固定结合面传统建模方法精度较低和结合面的动态特性参数难以确定的问题,改进了基于弹簧阻尼单元的建模方法,提出了基于实验模态分析和改进自适应遗传算法的固定结合面动态特性参数的优化识别方法。该方法以有限元计算的理论固有频率和阻尼比与其对应实验模态分析结果的相对误差最小为目标函数,使用改进的自适应遗传算法优化识别固定结合面的刚度和阻尼参数。以自行设计制作的固定结合面模型为研究对象进行了建模、实验、参数识别等分析,分析结果表明:所提出的方法是正确的、有效的,参数识别误差在5%以内,达到了较高的识别精度。

In allusion to the low precision of fixed joints＇ traditional modeling method and the difficulties to determine dynamic characteristic parameters of fixed joints, a modeling method based on spring-damper unit was improved,and a new method was proposed to identify the dynamic characteristics parameters of fixed joints based on experimental modal analysis and improved adaptive genetic algorithm. The minimum of relative error between natural frequency and damping ratio of finite element method and their corresponding experimental results was considered as objective function, the improved adaptive genetic algorithm was utilized to identify the stiffness and damping of fixed joints. Modeling, experiment and parameter identification were conducted with a self-designed and manufactured fixed joint modal which was treated as the research object. The analytic results indicate that the proposed method is correct and effective, and the parameter identification achieves high precision that the error is within 5%.