Artificial intelligence assisted technology for ground support construction

Benny Chen, Tom Harrington, P. Ayres, L. Gelinas
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Abstract

The typical underground mining development and reconciliation process across the world utilises the common design, construct, verify and rework methodology. The primary focus of a mining development contractor is to meet the required development schedule. Hence, the development cycle is often designed and optimised to reduce the cycle time and increase the advance rate. The reconciliation of development headings is time consuming, and often a manually intensive process of verifying the installation against design via survey. Hence, this is often left as a secondary task with long delays between any feedback to the development crews. Leveraging the latest in artificial intelligence technology, high density LiDAR and high speed computing systems can provide the ability for development crews to receive real-time in-cycle feedback on their ground support construction and also to monitor the effectiveness of the ground support. This has potential to significantly increase the efficiency and quality of reinforcement, whilst reducing wastage in development.
人工智能辅助地面保障建设技术
世界各地典型的地下采矿开发和协调过程采用了通用的设计、施工、验证和返工方法。采矿开发承包商的主要重点是满足所需的开发时间表。因此,经常设计和优化开发周期,以减少周期时间并提高进度率。开发标题的协调是耗时的,并且通常是一个手动密集的过程,通过调查来验证安装与设计。因此,这通常是次要任务,在向开发团队提供任何反馈之间存在很长的延迟。利用最新的人工智能技术,高密度激光雷达和高速计算系统可以为开发人员提供关于其地面保障结构的实时周期反馈,并监控地面保障的有效性。这有可能显著提高加固的效率和质量,同时减少开发过程中的浪费。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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