基于多模态的神经网络的结构损伤识别方法的研究 |
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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. |
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作者姓名: | 孙杰 |
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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 |
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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.
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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 |
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Authors: | SUN Jie |
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Institution: | SUN Jie (School of Transportation, Wuhan University of Technology, Wuhan 430063, China;Colleges of Urban Construction, Wuhan University Science and Technology, Wuhan 430074) |
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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. |
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Keywords: | curvature mode flexibility curvature neural networks damage identification |
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