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Damage Identification of Structure Based on RBF Neural Network

机译:基于RBF神经网络的结构损伤识别

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Health monitoring of the structure is a topic widely concerned and researched in the fields of technology and engineering at home and abroad. Damage identification of structure is an important aspect of the whole health monitoring system. In this paper, the RBF neural network with the effect of bionic is used to the extent, location and area recognition of the damage on the structure with single damage. The method of orthogonal least squares (OLS) is used as the learning method of the network. The test results show that the RBF neural network and the learning method of OLS can identify the damage status of the structure quickly and effectively with high accuracy.
机译:该结构的健康监测是一个主题,在国内外技术与工程领域中得到广泛,研究。结构的损害识别是整个健康监测系统的一个重要方面。在本文中,RBF神经网络具有仿生效应的范围,位置和面积对结构的损坏,单一损坏。正交最小二乘(OLS)的方法用作网络的学习方法。测试结果表明,RBF神经网络和OLS的学习方法可以快速有效地识别结构的损坏状态,高精度。

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