| 应用人工神经网络技术的大型斜拉桥子结构损伤识别研究 |
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| 引用本文： | 李忠献,杨晓明,丁阳.应用人工神经网络技术的大型斜拉桥子结构损伤识别研究[J].地震工程与工程振动,2003,23(3):92-99. |
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| 作者姓名： | 李忠献 杨晓明 丁阳 |
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| 作者单位： | 天津大学建筑工程学院,天津,300072 |
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| 基金项目： | 国家自然科学基金(50178047，50278064) |
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| 摘 要： | 本文应用人工神经网络技术对大型斜拉桥结构进行了子结构损伤识别研究。文中首先介绍了子结构损伤识别的基本方法，然后应用自组织竞争神经网络建立了对于大型桥梁结构识别子结构损伤情况的子结构损伤识别方法，并且应用BP网络进一步建立了大型桥梁结构各子结构内部的损伤位置和损伤程度的识别方法，数值模拟了一大跨度斜拉桥子结构损伤以及子结构内部损伤的识别过程，最后得出结论：(1)基于自组织竞争网络的子结构损伤识别方法能迅速准确地识别大型结构的损伤情况；(2)基于BP网络所建立的结构损伤识别方法，能对子结构中结构损伤的位置和程度进行进一步的识别；(3)基于人工神经网络技术的结构损伤识别方法是大型土木工程结构损伤识别的有效方法，可在工程结构损伤识别中广泛应用。
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| 关 键 词： | 人工神经网络技术 斜拉桥 子结构 损伤识别 自组织竞争网络 BP网络 土木工程 |
| 文章编号： | 1000-1301(2003)03-0092-08 |
Research on substructural damage identification of large cable-stayed bridges using artificial neural networks |
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| LI Zhong-xian,YANG Xiao-ming,DING Yang.Research on substructural damage identification of large cable-stayed bridges using artificial neural networks[J].Earthquake Engineering and Engineering Vibration,2003,23(3):92-99. |
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| Authors: | LI Zhong-xian YANG Xiao-ming DING Yang |
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| Abstract: | In this paper, the research on identification of structural damage to large cable-stayed bridges is performed using Artificial Neural Networks (ANN). At first, based on the review of the present status and future development of the identification of structural damage and the ANN technology, a method of substructural damage identification is established using the self-organizing competitive neural network, and the numerical simulation for the damage identification of a large cable-stayed bridge is carried out. Then, the identification for damage position and damage level is investigated using the BP network and the process of damage identification of the large cable-stayed bridge is numerically simulated again. Finally, some conclusions are drawn as; (1) The substructural damage identification based on the self-organizing competitive neural network is able to identify the structural damage rapidly and accurately. (2) The structural damage identification based on BP network is able to further identify the position and level of damage in the damaged substructure. (3) The method of identification of structural damage based on ANN is an effective measurement to identify the structural damage, which can be widely used in practical engineering. |
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| Keywords: | cable-stayed bridge substructure damage identification Artificial Neural Network (ANN ) self-organi- zing competitive neural network back-propagation neural network |
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