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结构损伤识别的序贯辅助粒子滤波方法
引用本文:唐和生,薛松涛,陈镕,杨晓楠.结构损伤识别的序贯辅助粒子滤波方法[J].同济大学学报(自然科学版),2007,35(3):309-314.
作者姓名:唐和生  薛松涛  陈镕  杨晓楠
作者单位:1. 同济大学,结构工程与防灾研究所,上海,200092
2. 同济大学,结构工程与防灾研究所,上海,200092;日本近畿大学,理工学部建筑学科,日本,大阪,577-8502
基金项目:教育部留学回国人员科研启动基金
摘    要:提出一种非平稳动力系统突变参数识别的序贯辅助粒子滤波方法(SAPF方法).该方法采用的重要抽样密度函数是一种依靠系统过去状态与系统最近观测量的联合密度函数,因此该方法具有较强的时域在线识别能力,比传统的粒子滤波方法更适合进行非平稳动力系统的参数识别.数值仿真结果证明了此方法在结构损伤在线识别中的有效性.

关 键 词:结构损伤识别  序贯  辅助粒子滤波  非平稳
文章编号:0253-374X(2007)03-0309-06
修稿时间:2005-06-24

Sequential Auxiliary Particle Filtering Method for Structural Damage Identification
TANG Hesheng,XUE Songtao,CHEN Rong,YANG Xiaonan.Sequential Auxiliary Particle Filtering Method for Structural Damage Identification[J].Journal of Tongji University(Natural Science),2007,35(3):309-314.
Authors:TANG Hesheng  XUE Songtao  CHEN Rong  YANG Xiaonan
Institution:1. Research Institute of Structural Engineering and Disaster Reduction, Tongji University, Shanghai 200092, China; 2. Department of Architecture, School of Science and Engineering, Kinki University, Osaka 577 - 8502, Japan
Abstract:A sequential auxiliary particle filtering(SAPF) method is proposed to identify a non-stationary dynamic system with abrupt changes of system parameters.In the APF,the sampling importance density is proposed as a mixture density that depends upon the past state and the most recent observations,and hence the method has a good time tracking ability.The APF,therefore is more suitable for tracking the non-stationary system than the conventional particle filtering.The numerical simulations confirm the effectiveness of the proposed method for the online structural damage identification.
Keywords:structural damage identification  sequential  auxiliary particle filtering  non-stationary
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