摘要
目的为了充分利用大型结构健康监测系统中来自不同时间与空间的多传感器信息资源,获得被测对象的一致性决策和估计任务,进而提高确诊率.方法从多传感器数据融合的概念、基本原理出发,探讨了数据融合技术在结构健康监测与诊断中应用的可行性,重点研究了基于人工智能的数据融合技术在结构健康监测及诊断中的应用方法.结果提出了小波概率神经网络数据融合损伤检测技术及其在结构损伤检测中的应用.结论基于多传感器数据融合的健康监测与诊断是可行的、有效的.
In order to make full use of different time-space multi-sensors information resources and to obtain the coincidence decision-making and assessment task of the objective from large-type structural health monitoring system, this paper, firstly, introduced the basic concepts and principals of multi-sensors data fusion. Secondly, the feasibility of the multi-sensors data fusion technique applied to the structural health monitoring was discussed. Thirdly, the method of data fusion-based structural health monitoring and diagnosis was emphasized, and the wavelet probabilistic neural network data fusion damage detection technique was proposed. Finally, it was investigated and discussed for data fusion technique to be applied in structural damage detection. The result showed that the method of data fusion-based structural health monitoring is feasible and effective.
出处
《沈阳建筑大学学报（自然科学版）》
EI
CAS
2005年第1期18-22,共5页
Journal of Shenyang Jianzhu University：Natural Science
基金
国家自然科学基金资助(50408033)
国家十五科技攻关项目(2002BA806B-4-4C)
辽宁省自然科学基金(20022136)
