Design of a Digital 3D Model of Transport–Technological Environment of Open-Pit Mines Based on the Common Use of Telemetric and Geospatial Information

Abstract

This article is devoted to the issues of processing and analysis of heterogeneous information related to the functioning of mining transport equipment, which becomes available for analysis within the framework of modern technological operations control systems in open-pit mines. These issues are very relevant to robotized technological operations. The paper gives a brief overview of the modern landscape of the autonomous haulage systems management problems, the features of the platform approach to solving the problem of managing unmanned transport and technological processes in open pits are considered. The concept of an agent-based approach to the modeling of an open-pit mining is described in detail on the basis of the interaction of three systems: technical, infrastructural–technological, and geostructural. Some features of the developed platform architecture integration of heterogeneous information are discussed. The principles of information integration are considered in detail when constructing a dynamic 3D model (digital twin) of infrastructure and technological system elements using large arrays of telemetric data. The results of building digital models of open-pit technological roads are presented. The resulting models are comparatively analyzed in the process of optimizing of the interaction of technical autonomous mobile agents and elements of technological infrastructure.

Digital twins in the minerals industry – a comprehensive review

“…The minerals industry is putting a large emphasis on sustainable operation in response to the rising concern about its contribution towards climate change (Ali et al 2017; Stothard et al 2019; El Bazi et al 2023), and the ongoing labour shortage among younger generations at remote locations. The concept of having DTs that can control and monitor physical entities in real-time has been explored in the literature (Temkin et al 2021; El Bazi et al 2022; Hazrathosseini and Moradi 2023; Fu et al 2023) which involves establishing bi-directional data flows through the integration of sensors, PLC, databases, and front-end HMIs for human operators to visualise as well as interact with the DT (Figure 22). The use of cloud computing in DT allows remote data access by multiple users across an organisation to maximise flexibility and redundancy in mining applications which are subjected to harsh environmental factors.…”

Renewable-Resource Technologies in Mining and Metallurgical Enterprises Providing Environmental Safety

“…All these measures make it possible to reduce the conditional threshold of natural and man-made georesources involved in the development, to obtain an additional marketable product, and to dispose of man-made waste after deep processing [42][43][44]. In total, this will increase the financial efficiency of a mining [45][46][47] and processing enterprise [23,24,33,[48][49][50] and ensure high environmental safety. Even after introducing all these measures, we will still be far from circular economy and closed-loop that still seem to be a wishful thinking in the case of mineral processing.…”

On some aspects of increasing the target productivity of unmanned mine dump trucks

“…The performed optimization of movement modes was carried out in manual mode and has required certain time costs. In the future, it is necessary that this procedure for achieving the effectiveness could be universally applied to any trajectories and areas of operation of robotic complexes without timeconsuming additional experimental haulage rounds of dump trucks [4,9,17,22]. Two approaches can be proposed to achieve this goal.…”

“…1. That a digital model of the route (roadbed) is pre-constructed and used [23] and a specific route is selected -that is, a set of macrocoordinates of the centers of basic geometric primitives (for example, hexagons with a face size of 1 m) [17].…”

“…3. Finally, it is necessary to calculate the sequence of coordinates within the framework of a given route between loading and unloading depots, that is, the route of the robot's movement [17] and determine such speed modes for individual sections of the route that would optimize the time of the route while minimizing both emergency risks and consumption of fuels and lubricants.…”