Time Varying Analysis Model for Cracks Causality of Concrete Dams
Time Varying Analysis Model for Cracks Causality of Concrete Dams
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DOI：
10.1061/40988(323)71
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发表时间：
2008-09
期刊：
影响因子：
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通讯作者：
H. Su;Jiang Hu;Z. Wen;Zhongru Wu;Bin Zhao
中科院分区：
文献类型：
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作者：
H. Su;Jiang Hu;Z. Wen;Zhongru Wu;Bin Zhao
影响混凝土坝裂缝变化的主要因素可以归结为水压、温度和老化三部分，但这三部分分别得到效果是非常困难的。裂纹变化与其影响因素之间的非线性时变关系很强。利用人工神经网络独特的数据分析和学习能力，通过大坝建设知识的交叉，可以为解决这些问题提供一个很好的途径。本文基于混凝土坝现场监测数据，从机器学习的角度，引入混凝土坝裂缝因果关系时变分析模型，分析预测荷载裂缝随时间和荷载变化的演化规律。算例表明，该模型能够精细地描述和预测混凝土坝裂缝因果关系的时变特征，并能给出各因素对裂缝张开的贡献。
The main factors of influencing the crack change of concrete dams can be reduced to three parts of water pressure, temperature and aging, but it is very difficult to get the effects of this three parts respectively. The nonlinear time-varying relationship between the crack change and its influencing factors is very strong. Using the unique ability of data analysis and learning of artificial neural network, and through the intercrossing of dam construction knowledge, then a good approach to solve these problems can be offered. In this paper, based on in-situ monitoring data of concrete dams, from the angle of machine learning, the time varying analysis model for causality of cracks of concrete dams is introduced, and the evolution law of load cracks with the change of time and load is analyzed and forecasted. The example indicates that the model can finely describe and forecast the time varying characteristic of cracks causality in concrete dams, and can give each factor's contribution to crack opening.