| 摘要: |
| 在混凝土坝裂缝开度预测中得到了广泛应用的统计回归模型仍存在不足。首先，对小容量样本的观测时间序列难以建立有效的统计回归模型；其次，预测模型未能考虑残差项，而残差项包含了裂缝发展演变的海量信息，为了准确预测裂缝开度还须在预测模型中纳入残差项。同时，统计回归模型的残差序列中存在混沌成分，残差项受到某种动力特性支配，故基于混沌理论对残差项进行推求，建立了统计与混沌混合预测模型。采用基于Legendre多项式的RLS(递推最小二乘法)自适应预测算法，提出了针对小容量样本观测数据时间序列的实时预测模型以及针对大容量样本观测数据时间序列的统计回归-Legendre多项式残差预测模型。最后，结合陈村重力拱坝在105 m高程的裂缝开度实测数据，对裂缝开度实时预测模型以及统计回归-Legendre多项式组合模型分别进行了检验，结果表明模型具有良好的预测精度，可为工程的安全运行管理工作提供一定的技术支持。 |
| 关键词: 混凝土坝 裂缝开度 Legendre 多项式 RLS自适应算法 |
| DOI：10.12170/201902016 |
| 分类号:TV698.1 |
| 基金项目:国家自然科学基金资助项目（51779155） |
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| Application of MLR-Legendre polynomials model in concrete dam crack opening prediction |
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QIU Liting1, SHEN Zhenzhong2, MA Fuheng1, NIE Baisong3
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1.Nanjing Hydraulic Research Institute, Nanjing;2.Hohai University, Nanjing;3.Huadong Engineering Corporation Limited, Hangzhou
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| Abstract: |
| The statistical regression model widely used to predict the crack opening displacements of the concrete dams still has some shortcomings. Firstly, it is difficult to establish an effective statistical regression model for the observation time series of small sample size; secondly, the model fails to consider the residual term, which contains a large amount of information about crack development and evaluation. In order to accurately predict the crack opening, the residual terms should be included in the prediction model. At the same time, there is a chaotic component in the residual sequence of the statistical regression model, and the residual term is dominated by some dynamic characteristics. Based on the chaotic theory, the residual term is deduced and a mixed prediction model of statistics and chaos is developed. Specifically, the RLS (recursive least squares) adaptive prediction algorithm based on Legendre polynomials is used to propose a real-time prediction model for small sample observation data time series and a statistical regression-Legendre polynomial residual prediction model for large sample observation data time series. Finally, the real-time prediction model for the crack opening and the statistical regression-Legendre polynomial combination model are tested with the measured data of the crack opening at 105 m height of Chencun gravity arch dam. The calculation results show that the MLR-Legendre prediction model has good prediction accuracy and can provide some technical supports for the safe operation and management of the works. The model and the crack criterion established above can be used to describe objectively the actual status of the dam engineering. |
| Key words: concrete dams crack opening displacement Legendre polynomials RLS adaptive algorithm |
