# A LiDAR-Based Backfill Monitoring System
###### Abstract  
A backfill system in underground mines supports the walls and roofs of mined-out areas and improves the structural integrity of mines. However, there has been a significant gap in the visualization and monitoring of the backfill progress. To better observe the process of the paste backfill material filling the tunnels, a LiDAR-based backfill monitoring system is proposed. As long as the rising top surface of the backfill material enters the LiDAR range, the proposed system can compute the plane coefficient of this surface. The intersection boundary of the tunnel and the backfill material can be obtained by substituting the plane coefficient into the space where the initial tunnel is located. A surface point generation and slurry point determination algorithm are proposed to obtain the point cloud of the backfill body based on the intersection boundary. After Poisson surface reconstruction and volume computation, the point cloud model is reconstructed into a 3D mesh, and the backfill progress is digitized as the ratio of the backfill body volume to the initial tunnel volume. The volumes of the meshes are compared with the results computed by two other algorithms; the error is less than 1%. The time to compute a set of data increases with the amount of data, ranging from 8 to 20 s, which is sufficient to update a set of data with a tiny increase in progress. As the digitized results update, the visualization progress is transmitted to the mining control center, allowing unexpected problems inside the tunnel to be monitored and addressed based on the messages provided by the proposed system. p 2024 12 December 2  
in situ pressures [5]. Inside the backfill material, roof subsidence sensors and stress sensors were installed during coal mining and backfilling to monitor the variations in subsidence and stress, thus the stress distribution in the coal mine gob was analyzed [6]. To investigate the variation law of the stope backfill strength along the flow direction of the slurry, the VS150 three-dimensional laser scanner was used to scan the final flowing track of slurry 28 days after the completion of the backfill process [7]. In the wider area, [PERSON] et al. [8] conducted field monitoring of cemented paste backfill in an underground coal mine, including measurements of temperature, humidity, stress conditions inside the backfill body, and displacement. This provides guidance for backfilling design and predictions of surface subsidence in underground mines. Backfill grouting is also generally used to limit the ground surface settlement induced by shield tunneling, which also provides valuable guidance for backfill monitors in underground mines. Ground-penetrating radar (GPR) was employed in a shield tunneling machine to monitor the thickness and volume of the grouting layer, successfully detecting several defects [9; 10]. In recent years, advanced technologies such as intelligent sensors and artificial intelligence have been used to detect subsidence and assess the stability of backfill bodies, making backfill monitoring safer and more efficient [11; 12; 13; 14]. However, former studies on backfill monitors, as highlighted earlier, have primarily focused on the physical and mechanical parameters during the backfill process detected using different types of sensors, with the aim of ensuring a stable backfill system; nevertheless, methods for monitoring backfill progress are still insufficient. In general mining operations, the methods for monitoring the backfill progress are often rudimentary. These typically involve using indirect indicators like the rate of material usage and pumping pressure. Without advanced sensors or real-time data monitoring, miners rely on experience, occasional sampling, or manual gauges to estimate when the backfill process is nearing completion. If there were a way to digitize and visualize the backfill progress, we could monitor the process more intuitively, identify issues in a timely manner, prevent the waste of backfill materials, and reduce costs.