Development of mine haul road surfacing condition monitoring through digital image processing

Abstract

As the concept of autonomous haulage systems (AHS) moves from proto-types to production-ready applications, the operating performance of the haul road will become 'mission critical' to the overall success of autonomy in mining. Deterioration in road performance will require remediation, human intervention and significant, albeit temporary, changes to operating procedures, to accommodate road maintenance. With autonomous trucks comes the opportunity to reduce road formation and operating width, and therefore generating potentially significantly reductions in stripping ratios and improvements to mine economics, but only if the design of the road, and it's associated deterioration rate, is predictable and manageable, based both on the materials used to construct the road and the maintenance interventions to be carried out on the road. This paper presents the assessment of a digital photogrammetric approach to the characterization of a mine haul road surfacing, or wearing course material. Design and maintenance parameters for these roads are currently determined from physical particle size distribution (PSD) assessments of 'in-road' material. However, this approach does not accommodate the need, nor leverage the benefits from, AHS. The digital imaging approach is assessed in this paper, using two standard digital analysis software tools, together with in-service mine haul road wearing course samples and images which are assessed to determine the applicability and reliability of the approach to deliver a real-time assessment of haul road surfacing conditions and thus to identify the road maintenance interventions required to address deterioration.