噪声与振动控制2018，Vol.38Issue(2)：179-187,9.DOI:10.3969/j.issn.1006-1355.2018.02.034
基于部分加速度测量的结构Bouc-Wen非线性恢复力及质量识别
Identification of Bouc-Wen Nonlinear Restoring Force and Mass of Structures with Limited Acceleration Measurements
摘要
Abstract
Structural nonlinear restoring force identification is critical for damage evaluation of structural disasters. Traditional extended Kalman filter (EKF) has been proposed to deal with the identification problems when limited measurements of dynamic responses are available,but it usually requires that the structural mass is known.To identify the structural nonlinear restoring forces with the structural mass unknown and the acceleration responses partially known, an iterative approach is proposed based on the EKF and least square method.In this approach,based on the assessed mass and the partially known acceleration responses,the entire time-history process of the response can be predicted using the EKF. Then,least square method is utilized to identify the updated mass distribution.This iterative procedure is carried out until the result converges.Finally,based on the updated mass,physical parameters of stiffness and damping and nonlinear parameters of the structure can be identified. Furthermore, the nonlinear restoring force of the structure can be determined. Taking a multi-DOF structure with a Bouc-Wen magneto-rheological (MR) damper as an example, and considering four types of different initial errors of the mass, the mass and the non-linear restoring force of the structure are identified by means of numerical simulation with this approach. The effectiveness and feasibility of this approach are verified. Meanwhile, considering the influence of the acceleration measurement noise,robustness of this approach is proved.关键词
振动与波/扩展卡尔曼滤波方法/最小二乘法/Bouc-Wen模型/磁流变阻尼器/非线性恢复力Key words
vibration and wave/extended Kalman filter (EKF)/least square method/Bouc-Wen constitutive model/magneto-rheological(MR)damper/nonlinear restoring force分类
机械制造引用本文复制引用
程骄阳,许斌,贺佳..基于部分加速度测量的结构Bouc-Wen非线性恢复力及质量识别[J].噪声与振动控制,2018,38(2):179-187,9.基金项目
国家自然科学基金资助项目(50978092) （50978092）
