DAMAGE IDENTIFICATION METHOD BASED ON BP NETWORK AND D-S EVIDENCE THEORY
In order to make full use of multi-resource information from a structural health monitoring system, neural network and multi-sensor data fusion technique were employed to detect structural damage in this paper. A 5-phase decision-level data fusion damage identification method that based on the combination of BP neural network and evidence theory was proposed. To validate the proposed method, six simulation damage patterns from a 7-DOF shear-type building model were identified. The results show that the proposed method cannot only improve the identification accuracy but also have good adaptive capability. This implies that the proposed method is feasible and effective in damage identification.
Damage detection data fusion BP neural network D-S evidence theory
Shao-Fei Jiang Chun-Mei Zhang Xiao-Fei Lv
College of Civil Engineering, Fuzhou University, Fuzhou 350002, P.R. China School of Civil Engineering, Shenyang Jianzhu University, Shenyang 110168, P.R. China
国际会议
长沙
英文
495-501
2007-11-19（万方平台首次上网日期，不代表论文的发表时间）