Key points are not available for this paper at this time.
ABSTRACT: Rockfalls pose a critical risk to the mining industry. In collaboration with NIOSH and industry partners, the Geotechnical Center of Excellence (GCE) has previously shown that thermal video can effectively observe rockfall events. Currently, work is underway to automate the detection, tracking, and alarming of these events. To facilitate this work, a prototype thermal imaging system that uses an early version of the detection algorithm has been developed. Designed to withstand extreme environments, the system can be easily transported with a light vehicle and installed in under 20 minutes. It includes a high-resolution security-type thermal camera, a tripod, a processing unit in a weatherproof case, and a backup battery to mitigate temporary power loss. While initially developed for detecting rockfall in open pit mines, the system can be customized for specific use cases. The presentation will provide an overview of the prototype's deployments and associated research to date, document lessons learned, and outline plans for future prototype development. 1. INTRODUCTION Rockfalls and slope failures represent a critical and escalating risk to the mining industry, posing threats to both personnel and infrastructure. Despite great progress in monitoring solutions targeting movement at rates of inches per year to inches per day, there are limited methods to detect rapid movement due to rockfall in real time (Sharon and Eberhardt, 2020). Currently, rockfall mitigation is largely limited to ‘manual’ methods such as trigger lines and human spotters. While important progress has been made to analyze rockfall sources and deposition zones with unmanned aerial vehicle (UAV) and light detection and ranging (LiDAR) systems, this requires significant post-processing time (Walton, et. al, 2023; Graber and Santi, 2023; Wang, et.al, 2021). Two Doppler radar systems are in commercial development for rockfall detection, but neither has been widely adopted in the US mining industry, and there remains a notable absence of widely adopted tools in this domain (Viviani, et. al, 2020).
Potter et al. (Sun,) studied this question.