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A Fractal Prediction Method for Safety Monitoring Deformation of Core Rockfill Dams

机译:核心堆石坝安全监测变形的分形预测方法

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Deformation mechanism in the core rockfill dams with heavy load and high-stress level is difficult to predict and control, which is one of the key problems to be solved in the dam operation safety management and control. Aiming at the large error problems obtained by the parameter-based functional models (regression model, grey theory model, etc.) in the deformation prediction of the core rockfill dams, a fractal prediction method and its technical process by combining the variable dimension fractal dimension and the "metabolism" of prediction data are proposed through analyzing the fractal adaptability and deformation characteristics of original monitoring data based on the resealed-range (R/S) method and fractal dimension theory. It effectively solves the error in the process of constant dimension fractal accumulation and transformation greatly in dam deformation prediction and provides a new way for dam safety monitoring deformation prediction and early warning. The trend analysis of deformation monitoring data of the Pubugou core rockfill dam and the deformation prediction show that the fractal prediction information of dam deformation has a good corresponding relationship with its physical causes, which is in line with the actual deformation trend and operation state of the dam. Compared with the traditional stepwise regression method, the prediction results obtained by the proposed method in this paper are of high accuracy, implying that the improved fractal prediction of dam deformation is effective and the Hurst fractal index is applicable in the evaluation of the dam deformation trend.
机译:具有重载和高应力水平的核心堆石坝中的变形机制难以预测和控制,这是大坝操作安全管理和控制中的关键问题之一。针对基于参数的功能模型(回归模型,灰色理论模型等)在核心堆石坝的变形预测中获得的大错误问题,通过组合可变尺寸分形维数,分形预测方法及其技术过程并通过分析基于重新置换范围(R / S)方法和分形维理论的原始监测数据的分形适应性和变形特性来提出预测数据的“代谢”。它有效地解决了大坝变形预测中恒定尺寸分形累积和变换过程中的误差,为大坝安全监测变形预测和预警提供了一种新的方式。 Pubugou核心堆石坝变形监测数据的趋势分析及变形预测表明,坝变形的分形预测信息与其物理原因具有良好的相应关系,这与实际变形趋势和操作状态符合坝。与传统的逐步回归方法相比,通过本文所提出的方法获得的预测结果具有高精度,这意味着改进的坝变形的分形预测是有效的,并且赫斯特分形指数适用于坝体变形趋势的评估。

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