LiDAR-IMU Fusion System with Adaptive Scanning for High-Resolution Deformation Monitoring of Underground Infrastructures

Abstract

A LiDAR-IMU fusion system utilizing adaptive scanning is developed for high-resolution deformation monitoring of underground coal mine infrastructure, such as sealed walls. The system integrates data from a LiDAR scanner and an IMU, employing a penalty function-based scanning strategy to optimize point cloud quality. Following feature extraction and state estimation, a 3D point cloud model of the sealed wall is constructed. Deformation monitoring is achieved through point cloud segmentation, registration, and error analysis across multiple time intervals. A methodology for optimizing equipment placement on walls of varying dimensions is proposed to efficiently capture deformation details. Two metrics, PATD and PARE, are introduced to evaluate system performance. Calibration experiments using standardized boards and blocks are designed to determine optimal monitoring parameters, including distance, height, and sampling frequency. Simulated deformation experiments under real-world conditions validate the system’s rationality and accuracy.