Condition assessment of buildings using acceleration data for life cycle predictions

摘要：

A damage detection approach via monitoring and measuring acceleration using limited number of sensors is proposed for life cycle prediction of buildings.It is a time-domain evaluation procedure capable of localizing and quantifying damage by transforming system identification problems into optimization problems.The particle swarm optimization(PSO)is utilized for the damage identification problem with accuracy advantage over some other optimization methods,such as Simulated Annealing(SA)and Genetic Analysis(GA).The method is effective and efficient especially for cases with very limited sensors.Based on the numerical simulation for a 5-story shear structure,the performance of the proposed approach is verified.With the minimal one sensor,the high practicability and flexibility are realized.The shake-table experiments are also used to verify the performance of the proposed approach.

关键词： Particle swarm optimization Neural network Life cycle prediction Damage identification

作者: Y. Qian A. Mita

作者单位: Keio University,Yokohama,Japan

会议类型: 国际会议

会议名称: The World Forum on Smart Materials and Smart Structures Technology(SMSST07)(2007年世界智能材料与智能结构技术论坛)

会议地点: 重庆·南京

会议语种:英文

在线出版日期: 2007-05-01（万方平台首次上网日期，不代表论文的发表时间）