Construction and Analysis of Slope Plane Deformation of High <scp>CFRD</scp> Based on Statistical Analysis of Multi‐Points Monitoring Data

ABSTRACT CFRD have been widely used worldwide because of their superior structural stability and economy. However, with the increasing of dam height, the issue of deformation control is becoming increasingly prominent, especially the panel deformation control which closely related to the internal rockfill deformation. Comparing with the monitoring data of a single monitoring point, the slope plane deformation can reflect the deformation characteristics of the dam rockfill area more effective. To ensure the long‐term stability and safe operation of the CFRD, construction and analysis the slope plane deformation of the CFRD is particularly important. In order to improve the accuracy of prediction, a method of modeling and analysis of dam slope plane deformation based on multi‐points monitoring data is proposed in this paper. Based on the actual monitoring data of the Hongjiadu CFRD, this paper comprehensively analyzes the influence of the filling process, water level change, and time effect on the settlement of the CFRD during the construction and impoundment periods, and establishes the settlement statistical model of all monitoring points. By studying the relationship between the parameters of the settlement statistical model of each monitoring point and its own position coordinates, a spatial–temporal distribution model of the dam slope plane is established by using the thin plate spline interpolation method, and it is used to predict the settlement of the dam slope plane. This method has great advantages in the prediction accuracy. By considering the temporal and spatial distribution characteristics, this method can effectively capture the whole and local deformation of the dam body and improve the prediction accuracy of settlement. Compared with the traditional single point monitoring method, the proposed method provides more accurate prediction results on the basis of multi‐point data collaborative analysis, provides a new idea for dam displacement monitoring and settlement prediction, and has high engineering application and popularization value.