摘要
边坡变形预测是安全施工和运行的重要手段,边坡变形受到较多外部因素的影响,很难用力学模型或经验公式进行计算及预测。引入布朗运动模型对边坡变形数据进行建模,在监测数据的基础上利用卡尔曼滤波对边坡变形进行预测。根据实际监测数据及基于布朗运动模型的预测模型,进行了某矿山边坡监测数据的预测实验。结果表明,该方法能够根据历史监测数据进行较为准确、高效的预测。
Slope deformation prediction is vital to ensure the safety of implementation and construction of foundation engineering. External variables have tremendous influence on slope deformation, thus it is difficult to utilize mechanics models and empirical formula to predict the deformation. In this paper, we model the slope deformation data with Brownian motion model, and use Kalman filter to predict the future deformation based on historical deformation data. A practical slope deformation predictions provided to substantiate the superiority of the proposed model. The results show that our model can provide accurate estimation of future slope deformation.
作者
胡俊
李远文
HU Jun;LI Yuanwen(Guangdong Nonferrous Geometrical Surveying and Mapping Institute, Guangzhou 510000, China)
出处
《测绘地理信息》
2019年第4期45-48,共4页
Journal of Geomatics
基金
广东省有色金属地质局财政项目(粤财工[2015]632号)
关键词
布朗运动模型
边坡监测
卡尔曼滤波
变形预测
Brownian motion
slope monitoring
Kalman filtering
deformation forecast
