基于空间面板数据模型的拱坝变形缺失数据处理

An interpolation method for filling in missing data of arch dam deformation using a spatial panel data model

  • 摘要: 变形监测信息缺失会对拱坝安全性态的分析造成困难甚至引起误判,需要采用科学合理的方法对缺失数据进行处理,从而获取完整可靠的监测数据。传统的缺失值处理方法仅考虑了拱坝测点的局部空间关联性,而拱坝变形整体性较强,在进行缺失值插补时有必要考虑拱坝所有测点间的时空关联性。鉴于此,从拱坝的整体性和测点的空间相关性出发,首先引入空间权重矩阵,证明拱坝变形具有显著的空间正自相关性;在此基础上,基于空间面板数据模型提出一种考虑拱坝整体时空关联性的变形缺失数据处理方法;最后结合某拱坝工程实例,验证了所构建模型的有效性。工程实例表明:该方法插补残差值低于SL 601—2013《混凝土坝安全监测技术规范》所规定的误差限值,具有较高的插补精度,可对变形监测缺失数据进行有效处理。

     

    Abstract: The absence of deformation monitoring data in arch dams can lead to difficulties and inaccuracies in analyzing their safety behavior. Therefore, it is crucial to employ a scientific and reasonable method to fill in missing data and obtain complete and reliable monitoring data. Traditional approaches for handling missing values only consider the local spatial correlation among measurement points in arch dams. However, it is necessary to consider the spatiotemporal correlation across all measurement points, considering that an arch dam functions as an inseparable entity. In this paper, we introduce a spatial weight matrix that takes into account the integrity of the arch dam and the spatial correlation among measurement points. We demonstrate a significant positive spatial autocorrelation in the deformation data of arch dams. Based on this, we propose a method to fill in missing deformation data using a spatial panel data model, which considers the spatiotemporal correlation of the entire arch dam. Finally, we validate the proposed model by applying it to an arch dam project. The results indicate that the interpolation residual error of the proposed method is lower than the error limit specified in The Code for Dam Safety Monitoring (SL 601—2013). Consequently, the proposed method effectively handles missing deformation monitoring data.

     

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