# A LiDAR-Based Backfill Monitoring System
## 5 Conclusions  
A LiDAR-based backfill monitoring system was designed to monitor the process of slurry entering and filling the mined-out tunnel. LiDAR technology was used to obtain the constantly changing spacial distribution shape of the filling process. An NUC was connected to the LiDAR to compute the backfill progress and return the real-time processed results to the mining control center. The proposed system enables timely monitoring and precise visualization of backfill progress, demonstrating its feasibility and practicality.  
A simulation environment of backfill was constructed. Different types of filling conditions were designed and recorded into ROS bags using a simulated LiDAR sensor. Because of the fixed LiDAR position, the only change in all of the LiDAR scans is the ever-rising top surface of the slurry. Therefore, the key to compute the backfill progress is to compute the volume of the growing backfill body.  
To exploit this feature, outlier searching and the RANSAC plane-fitting algorithm were used to locate and screen out the top surface, which is recognized as the intersection boundary of the slurry top surface and the tunnel. After applying slurry points determination and the moving sampling method, the whole point cloud of backfill body was generated. By using Poisson surface reconstruction on the point cloud of the backfill body, the triangular mesh was obtained. The backfill progress was determined by computing the percentage of the slurry to the volume of the tunnel.  
If the accuracy of LiDAR scanning and Poisson reconstruction algorithm are not considered, the error of volume calculation results compared with other methods is less than 1%. In the late stage of backfill, the large amount of point cloud data affects the processing speed of Poisson surface reconstruction and volume computation, resulting in the time to process one set of LiDAR scans to rise to around 45 s. According to the designed flow rate of the slurry, the maximum time to update the progress is less than the time needed for the progress to increase by 0.5%.  
The backfill system in underground mining includes both tunnel and mined-out area backfilling. A key limitation of the proposed system is that a single LiDAR cannot capture the vast mined-out areas, even with a wide field of view. Multiple LiDAR sensors are required, and challenges in data transmission, fusion, and processing must be addressed.  
Additionally, measurements for filling thick deposits with layered divisions can be a valuable consideration for future work. Layered backfilling allows for better control over material distribution and settling behavior, which can influence the accuracy of volume calculations and the overall progress monitoring. This approach could improve the robustness of backfill monitoring systems in complex mining environments.  
Figure 12: The time to process each set of scans: (**a**) results in the LiDAR range of 100 m; (**b**) results in the LiDAR range of 200 m.  
**Author Contributions:** Conceptualization, X.X. and L.B.; methodology, X.X., L.B. and P.H.; software, L.B. and P.H.; validation, Z.H. and Z.Z.; formal analysis, Z.H. and Z.Z.; investigation, Z.H. and Z.Z.; resources, X.X.; data curation, Z.H. and Z.Z.; writing--original draft preparation, L.B. and P.H.; writing--review and editing, X.X., L.B. and P.H.; visualization, Z.H. and Z.Z.; supervision, X.X.; project administration, X.X.; funding acquisition, X.X. and L.B. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by National Key R&D Program of China, grant number 2023 YFC2907305.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data supporting this study's findings are available from the corresponding author upon reasonable request.  
**Conflicts of Interest:** The authors declare no conflicts of interest.