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    许斌

    • 教授 博士生导师 硕士生导师
    • 主要任职:Director and Founder, Key Laboratory for Intelligent Infrastructure and Monitoring of Fujian Province
    • 性别:男
    • 出生日期:1972-03-04
    • 毕业院校:Ibaraki University
    • 学历:博士研究生
    • 学位:工学博士学位
    • 入职时间:2016-08-01
    • 所在单位:土木工程学院土木工程系
    • 办公地点:College of Civil Engineering, Huaqiao University, Jimei Avenue 668, Xiamen, China
    • 电子邮箱:
    • 在职信息:在岗
    • 其他任职:Director and Founder, International Research Center for Safety and Sustainability of Civil Engineering
    • 职务:Director, Key Laboratory
    • 学科:土木工程
    • 2008当选:教育部“新世纪优秀人才支持计划”入选者
    • 2008当选:教育部新世纪优秀人才支持计划
    • 2016当选:桐江学者
    • 2017当选:福建省“闽江学者奖励计划”特聘教授
    • 2017当选:厦门市双百计划
    • 2017当选:福建省闽江学者-特聘教授
    • 2018当选:福建省引进高层次人才
    • 福建省引进高层次人才(海外B类)

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    Nonparametric identification for hysteretic behavior modeled with a power series polynomial using EKF-WGI approach under limited acceleration and unknown mass

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    发表刊物:International Journal of Non-Linear Mechanics

    摘要:Identifying damage initiation and development in engineering structures non-parametrically in the form of a nonlinear restoring force (NRF) after strong dynamic loading is attractive. Due to the individuality of various engineering structures, it is quite challenging to assume, in advance, a general parametric model describing the nonlinear behavior. Although a traditional extended Kalman filter (EKF) is efficient in state vector estimation and structural parameter identification with partially available output measurements, a known structural mass is usually required. In this study, a simultaneous NRF and mass identification approach is developed for multi-degree-of-freedom (MDOF) structures using the EKF with weighted global iteration (EKF-WGI) based on limited available absolute acceleration response. The NRF is modeled in a nonparametric way with a power series polynomial model (PSPM) as a function of unknown structural displacement and velocity responses. Then, the performance of the new approach is numerically evaluated using multi-story structures equipped with magneto-rheological (MR) dampers having known applied excitations and partially available noise-contaminated acceleration measurements, but unknown mass. No parametric model for the NRF of the MR dampers is employed. The effect of different noise levels and different initial estimation errors of structural mass on both NRF and mass identification results and the convergence of the approach are investigated. Finally, a dynamic test on a four-story frame structure equipped with an MR damper is carried out and the algorithm is experimentally validated. Comparisons show that the identified NRF provided by the MR damper matches the measurement and that the identified mass is also accurate.

    论文类型:期刊论文

    文献类型:J

    卷号:119

    页面范围:103324

    是否译文:

    发表时间:2020-03-23

    收录刊物:SCI

    影响因子:3.336

    第一作者:许斌

    合写作者:李靖,Dyke, Shirley J,邓百川,贺佳