Method to Haulage Path Estimation and Road-Quality Assessment Using Inertial Sensors on LHD Machines

P. Stefaniak, S. Anufriiev, Artur Skoczlas, Bartosz Jachnik, P. Śliwiński
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引用次数: 4

Abstract

For many years now, the mining industry has seen a boost in exploring and developing the systems for monitoring operational parameters of mining machines, in particular load-haul-dump machines. Therefore, further researches on algorithmics have also advanced dynamically regarding effective performance management as well as predictive maintenance. Nonetheless, the issue of road conditions is still being neglected. That issue has a substantial impact on both the overall operator’s convenience, their performance, and machinery reliability, especially its construction node and tire damages. Moreover, such negligence pertains also to the maintenance of mine infrastructure, including the network of passages. The paper explains the use of the portable inertial measurement unit (IMU) in evaluating road conditions in the deep underground mine. The detailed descriptions of the road quality classification procedure and bump detection have been included. The paper outlines the basic method of tracking the motion trajectory of vehicles and suggests the method of visualization of the results of the road conditions evaluation. This paper covers the sample results collected by the measurements unit in the deep underground mine during six experiments. This paper is an extended version of a paper presented at the ACIIDs 2020 conference [P. Stefaniak, D. Gawelski, S. Anufriiev and P. Śliwiński, Road-quality classification and motion tracking with inertial sensors in the deep underground mine, Asian Conference on Intelligent Information and Database Systems, March 2020, Springer, Singapore, pp. 168–178].
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基于惯性传感器的LHD机器运输路径估计与道路质量评估方法
多年来,采矿业在探索和开发监测采矿机器,特别是装卸倾卸机的操作参数的系统方面取得了很大进展。因此,在有效的性能管理和预测性维护方面,对算法的进一步研究也在不断推进。尽管如此,道路状况的问题仍然被忽视。该问题对操作人员的便利性、性能和机械可靠性,特别是施工节点和轮胎损坏都有重大影响。此外,这种疏忽也涉及地雷基础设施的维修,包括通道网。介绍了便携式惯性测量仪(IMU)在深埋地下矿山道路状况评估中的应用。详细描述了道路质量分类程序和碰撞检测。概述了车辆运动轨迹跟踪的基本方法,提出了道路状况评价结果可视化的方法。本文介绍了测量单元在深井井下六次试验中采集的样品结果。这篇论文是在ACIIDs 2020会议上发表的一篇论文的扩展版本。王晓明,王晓明,王晓明,P. Śliwiński,基于惯性传感器的深埋矿山道路质量分类与运动跟踪,中国公路交通大学学报(自然科学版),2020年3月,pp. 168-178。
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