STRUCTURAL DAMAGE IDENTIFICATION METHOD BASED ON ROUGH SET AND PROBABILISTIC NEURAL NETWORK

摘要：

With the large structural health monitoring system successfully developed and applied, it has become to be focus how to make full use of the redundant and complementary information and assess on structural healthy states. A new structural damage identification method is proposed in this paper. In this method, rough set is employed to process initial data and reduce attributes in advance.Thus a probabilistic neural network (PNN) is employed to fuse multi-sensor data and conclude the damage identification results. To validate the proposed method, six damage patterns from a 7-DOF building model are identified finally, and a comparison is made. The results show that the method can reduce spatial dimension of data, as well as have a good consist with un-attributes reduction.

关键词： Rough set Damage identification Probabilistic neural network Data fusion

作者: Shao-Fei Jiang Juan Yao

作者单位: College of Civil Engineering, Fuzhou University, Fuzhou 350002, P.R. China School of Civil Engineering, Shenyang Jianzhu University, Shenyang 110168, P.R. China

会议类型: 国际会议

会议名称: 第十届国际结构工程青年学者研讨会(The Tenth International Symposium on Structural Engineering for Young Experts)

会议地点: 长沙

会议语种:英文

页码: 1579-1584

在线出版日期: 2008-10-19（万方平台首次上网日期，不代表论文的发表时间）