摘要
为提高结构损伤识别的准确率,在大型复杂土木工程结构的健康监测中引入多传感器数据融合技术,提出了基于数据融合技术的结构损伤识别方法的实用模型,建立了结构损伤识别方法的评价指标,并通过钢筋混凝土板试验分析了常用的数据融合方法——Bayes方法和D-S证据理论的有效性。分析结果表明:采用数据融合技术,结构损伤识别方法的评价指数更高,即结构损伤识别的效果更好。
To improve the validity of structural damage identification, multi-sensor data fusion technique is imported into structure health monitoring for large-scale civil engineering structures. In this paper, practical models for structural damage identification based on data fusion technique are put forward, and an evaluating indicator for structural damage identification methods is developed. Bayes method and D-S evidence theory, which are in common use in data fusion technique, are discussed through an experiment on two RC plates. The analysis results reveal that damage identification evaluating indicators with data fusion technique are higher than those with single structural damage identification method. That is to say, structural damage identification methods based on data fusion yield better results.
出处
《工程力学》
EI
CSCD
北大核心
2008年第1期16-21,共6页
Engineering Mechanics
基金
国家高技术发展研究计划(863计划)资助项目(2006AA04Z416)
国家自然科学基金重大国际合作资助项目(50410133)
国家自然科学基金资助项目(50378017)
教育部高等学校科技创新工程重大项目培育基金项目(704024)
东南大学优秀博士学位论文基金资助项目(0705)
