基于粒子群优化算法的动力学模型修正
Dynamic Model Updating Using Particle Swarm Optimization Method
摘要：
本文提出了使用粒子群优化方法（PSO）的有限元（FE）模型修正。将PSO方法与现有的模拟退火（SA）或遗传算法（GA）方法进行了比较。对一个非对称H型结构进行了试验研究。据观察，所提出的方法更新的固有频率最准确，其次是由一个更新的模型，使用GA和一个完整的FE模型获得的。还观察到，所提出的方法给出了最好的相关测量的，其次是由一个更新的模型，使用SA和一个完整的FE模型得到的更新的模式形状。此外，据观察，粒子群算法实现这一精度的计算速度比GA和一个完整的FE模型，这是比SA和一个完整的FE模型更快。
英文摘要：
This paper proposes the use of particle swarm optimization method (PSO) for finite element (FE) model updating. The PSO method is compared to the existing methods that use simulated annealing (SA) or genetic algorithms (GA) for FE model for model updating. The proposed method is tested on an unsymmetrical H-shaped structure. It is observed that the proposed method gives updated natural frequencies the most accurate and followed by those given by an updated model that was obtained using the GA and a full FE model. It is also observed that the proposed method gives updated mode shapes that are best correlated to the measured ones, followed by those given by an updated model that was obtained using the SA and a full FE model. Furthermore, it is observed that the PSO achieves this accuracy at a computational speed that is faster than that by the GA and a full FE model which is faster than the SA and a full FE model.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
