利用卡尔曼滤波法进行水电站大坝沉降分析 - 越南 Hoa Binh 水电站案例研究

Thi Kim Thanh Nguyen
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引用次数: 0

摘要

水电站大坝对下游地区的安全有很大影响。因此,为评估大坝的安全性,应定期进行变形监测。为了提高大坝管理的效率,有必要对大坝的位移值进行空间和时间分析,以全面评估大坝的位移情况。为此,我们尝试使用一种最有用的方法--卡尔曼滤波法--来分析位于越南和平省的水电站大坝的沉降情况。卡尔曼滤波法是一种独特的方法,可以确定外部因素(特别是水库水位的升高)对大坝的影响,同时预测大坝未来的位移值。此外,卡尔曼滤波法可以在 6 个月左右的时间内准确预测沉降,比其他静态模型的预测时间更长。文章清楚地介绍并讨论了这些问题。所获得的结果表明卡尔曼滤波法在分析和预测华平水电站大坝沉降方面具有很高的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SUBSIDENCE ANALYSIS OF HYDROELECTRIC DAM USING THE KALMAN FILTER – A CASE STUDY IN HOA BINH HYDROPOWER PLANT, VIETNAM
Hydroelectric dams have a great influence on the safety of the downstream area. Therefore, deformation monitoring for assessing the safety of dam should be carried out regularly. In order to improve efficiency of the dam management, it is necessary to analyse the displacement values in space, over time to assess overally the displacement of dam. In this purpose, an attempt was conducted to analyse the subsidence of hydroelectric dams located in Hoa Binh, Vietnam using one of the most useful method – Kalman filter. Kalman filter is the unique method that can determine influence of external factors (particularly, elevation of water level in the reservoir) on dams, simultaneously forecast the displacement values of dam in the future. Moreover, Kalman filter allows to predict subsidence accurately in about 6 months that is longer prediction time than other static models. These are clearly presented and discussed in the article. The obtained results demonstrate the high applicability of Kalman filter method in analysing and forecasting the subsidence of the Hoa Binh hydroelectric dam.
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