Real-Time Spreading Thickness Monitoring of High-core Rockfill Dam Based on K-nearest Neighbor Algorithm

Abstract

During the storehouse surface rolling construction of a core rockfill dam, the spreading thickness of dam face is an important factor that affects the construction quality of the dam storehouse’ rolling surface and the overall quality of the entire dam. Currently, the method used to monitor and control spreading thickness during the dam construction process is artificial sampling check after spreading, which makes it difficult to monitor the entire dam storehouse surface. In this paper, we present an in-depth study based on real-time monitoring and control theory of storehouse surface rolling construction and obtain the rolling compaction thickness by analyzing the construction track of the rolling machine. Comparatively, the traditional method can only analyze the rolling thickness of the dam storehouse surface after it has been compacted and cannot determine the thickness of the dam storehouse surface in real time. To solve these problems, our system monitors the construction progress of the leveling machine and employs a real-time spreading thickness monitoring model based on the K-nearest neighbor algorithm. Taking the LHK core rockfill dam in Southwest China as an example, we performed real-time monitoring for the spreading thickness and conducted real-time interactive queries regarding the spreading thickness. This approach provides a new method for controlling the spreading thickness of the core rockfill dam storehouse surface.