结构恢复力非参数化模型识别的改进容积卡尔曼滤波方法  

Nonparametric identification of structural nonlinear restoring force based on an updated cubature Kalman filter

作　　者：杜义邦 许斌[1,2] 赵冶 邓百川 DU Yi-bang;XU Bin;ZHAO Ye;DENG Bai-chuan(College of Civil Engineering,Huaqiao University,Xiamen 361021,China;Key Laboratory for Intelligent Infrastructure and Monitoring of Fujian Province,Huaqiao University,Xiamen 361021,China;Department of Civil,Structural and Environmental Engineering,University at Buffalo,the State University of New York,Buffalo,NY 14260,USA)

机构地区：[1]华侨大学土木工程学院,福建厦门361021 [2]福建省智慧基础设施与监测重点实验室(华侨大学),福建厦门361021 [3]纽约州立大学布法罗分校土木、结构与环境工程系,纽约布法罗14260

出　　处：《振动工程学报》2023年第2期389-399,共11页Journal of Vibration Engineering

基　　金：国家自然科学基金资助项目(50978092);华侨大学科研基金资助项目(605-50Y18016)。

摘　　要：对地震等强动力荷载作用过程中结构损伤的发生发展过程进行识别,必须考虑结构行为的非线性。本文运用相对位移和相对速度的幂级数多项式表征结构恢复力模型,提出一种基于改进的容积卡尔曼滤波算法(Updated Cubature Kalman Filter, UCKF)和结构部分自由度上加速度响应时程的结构参数、未知响应及恢复力非参数化模型识别方法。以一个含磁流变阻尼器的多自由度数值模型为例,考虑20%的加速度响应测量噪声影响,识别出模型的结构参数、未知响应及阻尼力。并将本文方法所得结果分别与基于扩展卡尔曼滤波算法、传统容积卡尔曼滤波算法及含记忆衰退的扩展卡尔曼滤波算法所得结果进行比较。对一个带磁流变阻尼器的四层剪切型框架模型进行激振试验,基于部分自由度上的加速度响应时程实测值,识别出结构参数、未知动力响应以及阻尼器阻尼力的非参数化模型,通过与实测结果的比较,验证了本文方法的可行性。Structural nonlinear behavior under the excitation of strong dynamic loadings should be considered for structural damage initiation and propagation identification of engineering structures.In this study,a power series polynomial of relative displacement and velocity is employed to model the nonlinear restoring force(NRF)of a structure in a nonparametric way and structural mass,stiffness,damping coefficients and NRF are identified based on an updated cubature Kalman filter(UCKF)algorithm using accel⁃eration response at limited degrees of freedoms(DOFs)of the structure during dynamic excitation.Then,a multi-degree-of-free⁃dom(MDOF)numerical model equipped with a magnetorheological(MR)damper mimicking structural nonlinearity is employed to validate the proposed approach numerically.By adding 20%measurement noise to the acceleration measurements,the stiffness,damping coefficients and mass of the structure,the unmeasured response and the NRF are identified.The effectiveness of the pro⁃posed method is validated by comparing the theoretical values with the identified values.Moreover,the identification results of the proposed approach are also compared with them of the approach with the traditional extended Kalman filter(EKF),cubature Kal⁃man filter(CKF),and extended Kalman filter with memory fading(EKF-MF).Dynamic test on a four-story shear frame model with a MR damper is carried out.The structural parameters of the frame structure itself,the unused dynamic response in identifica⁃tion and the NRF provided by the MR damper are identified with the proposed approach using acceleration responses at certain floors.The identified results are compared with the test measurements directly and the performance of the proposed identification approach is experimentally validated.

关 键 词：非线性恢复力 改进的容积卡尔曼滤波 非参数化识别 幂级数多项式 磁流变阻尼器 

分 类 号：TU311.3[建筑科学—结构工程]