基于IMPSCO和改进Newmark-β算法的结构系统及激励辨识研究

摘要

基于振动的土木工程结构系统识别中,常用的识别方法如基于Newmark-β算法的方法,常常需要已知激励,而事实上激励和完整的输出响应是很难测得的.基于此,在现有的Newmark-β算法中引入多项式拟合来解决结构系统识别误差带来的漂移现象,进而提出了改进的Newmark-β算法,并结合改进协同粒子群算法(IMPSCO),给出了仅用部分结构响应的系统识别和激励辨识方法.最后,通过一七层钢框架数值算例和实验室模型试验验证了方法的有效性和可行性,并探讨了噪声、输出响应完整性的影响.研究表明,所提方法能准确地实现未知激励和部分实测响应状态下的结构系统和未知激励的识别,而且具有较强的容噪性和鲁棒性.%In vibration-based structural system identification (SI) of a civil structure,the commonly used SI method,such as,the one based on Newmark-β algorithm usually needs the known excitation.In fact,it is difficult to measure the actual excitation and full output responses of a structure system.Here,a modified Newmark-β algorithm was proposed through introducing polynomial fitting into Newmark-β algorithm to effectively solve the drift phenomenon brought by the error of SI.Furthermore,combining the modified Newmark-β algorithm with the improved multi-particle swarm co evolution optimization (IMPSCO),an identification approach of SI and excitation adopting responses of parts of a structure system was presented.Finally,numerical simulation for a seven-story steel frame and its model tests were conducted to verify the effectiveness and feasibility of the proposed method.The effects of noise and completeness of structural response were also discussed.The results showed that the proposed method can be used to effectively identify a structural system and its excitation only adopting responses of parts of the structure system;it has stronger noise tolerance and robustness.