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基于多模态的神经网络的结构损伤识别方法的研究
引用本文:孙杰.基于多模态的神经网络的结构损伤识别方法的研究[J].武汉水运工程学院学报,2012(6):1240-1242.
作者姓名:孙杰
作者单位:[1]武汉理工大学交通学院,武汉430063 [2]武汉科技大学城市建设学院,武汉430074
摘    要:采用曲率模态和柔度曲率组合成多模态参数,针对连续梁结构在有限元模型基础上对结构进行了损伤识别研究.结果表明,以此多模态参数作为网络输入参数,并通过学习训练所得网络不仅可以准确地对结构损伤进行定位,而且对损伤的定量也取得了比较理想的效果,表明此网络还具备良好的容错性和鲁棒性.

关 键 词:曲率模态  柔度曲率  神经网络  损伤识别

Research on Damage Identification Based on Multi-modal Using Neural Networks
Authors:SUN Jie
Institution:SUN Jie (School of Transportation, Wuhan University of Technology, Wuhan 430063, China;Colleges of Urban Construction, Wuhan University Science and Technology, Wuhan 430074)
Abstract:The multi-modal parameter which is composed of the curvature mode and the flexibility cur- vature is used to identify the damage on the base of finite element method model based on continuous beam. It has been proved that multi-mode parameter is considered as networks inputting parameter, and the location of the structure damage can be accurately determined and the quantitative of the struc- ture damage can be obtained by the neural networks. It has indicated that this neural network has a excellent identification ability with good ideal error tolerance and robustness.
Keywords:curvature mode  flexibility curvature  neural networks  damage identification
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