DEFECT IDENTIFICATION USING LEARNING VECTOR QUANTIZATION NEURAL NETWORK

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概要

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• The Learning Vector Quantization (LVQ) neural network is applied to the defect identification problem for structures, which is important when constructing the mathematical model of structures. In this study the eigenmodes of a plate obtained from FEM and the location of a defect contained in that plate are used as the training deta for neural network and the position of the defect is identified by giving the unlearned input data to the trained network. As a result the better accuracy is obtained compared to the case when using the backpropagation neural network commonly used in the various studies

• 一般社団法人日本機械学会の論文

著者

• Miyaji Hideyuki

  Department Of Mechanical Engineering Kanagawa Institute Of Technology

• Kozukue Wakae

  Department Of Mechanical Engineering Kanagawa Institute Of Technology

関連論文

• DEFECT IDENTIFICATION USING LEARNING VECTOR QUANTIZATION NEURAL NETWORK

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