A METHODOLOGY FOR AUTONOMOUS ROOF BOLT INSTALLATION USING INDUSTRIAL ROBOTICS

The mining sector is currently in the stage of adopting more automation, and with it, robotics. Autonomous bolting in underground environments remains a hot topic for the mining industry. Roof bolter operators are exposed to hazardous conditions due to their proximity to the unsupported roof, loose bolts, and heavy spinning mass. Prolonged exposure to the risk inevitably leads to accidents and injuries. The current thesis presents the development of a robotic assembly capable of carrying out the entire sequence of roof bolting operations in full and partial autonomous sensor-driven rock bolting operations to achieve a high-impact health and safety intervention for equipment operators. The automation of a complete cycle of drill steel positioning, drilling, bolt orientation and placement, resin placement, and bolt securing is discussed using an anthropomorphic robotic arm.A human-computer interface is developed to enable the interaction of the operators with the machines. Collision detection techniques will have to be implemented to minimize the impact after an unexpected collision has occurred. A robust failure-detection protocol is developed to check the vital parameters of robot operations continuously. This unique approach to automation of small materials handling is described with lessons learned. A user-centered GUI has been developed that allows for a human user to control and monitor the autonomous roof bolter. Preliminary tests have been conducted in a mock mine to evaluate the developed system\u27s performance. In addition, a number of different scenarios simulating typical missions that a roof bolter needs to undertake in an underground coal mine were tested

Implementation of explosion safety regulations in design of a mobile robot for coal mines

The article focuses on specific challenges of the design of a reconnaissance mobile robotic system aimed for inspection in underground coal mine areas after a catastrophic event. Systems that are designated for these conditions must meet specific standards and regulations. In this paper is discussed primarily the main conception of meeting explosion safety regulations of European Union 2014/34/EU (also called ATEX-from French "Appareils destines a etre utilises en ATmospheres Explosives") for Group I (equipment intended for use in underground mines) and Category M1 (equipment designed for operation in the presence of an explosive atmosphere). An example of a practical solution is described on main subsystems of the mobile robot TeleRescuera teleoperated robot with autonomy functions, a sensory subsystem with multiple cameras, three-dimensional (3D) mapping and sensors for measurement of gas concentration, airflow, relative humidity, and temperatures. Explosion safety is ensured according to the Technical Report CLC/TR 60079-33 "s" by two main independent protections-mechanical protection (flameproof enclosure) and electrical protection (automatic methane detector that disconnects power when methane breaches the enclosure and gets inside the robot body).Web of Science811art. no. 230

Pose Adjusting Simulation of Hydraulic Support Based on Mechanical-Electrical-Hydraulic Coordination

The pose variations of the hydraulic support have significant influence on its performance. And the pose adjusting operations are required to be fast and precise, while they have typical mechanical-electric-hydraulic coordination characteristics which are challenging to simulate. In view of these problems, a method has been proposed in this work for accurately monitoring and controlling the pose of the hydraulic support, and using a suitable multi-software co-simulation model to simulate it. A mathematical model for pose monitoring and control was initially established.A teaching-learning-based optimization algorithm (TLBO) was then introduced to obtain the numerical solution of the nonlinear equations.Finally, a numerical model based on mechanical-electrical-hydraulic co-simulation was established. The model was tested and validated by using different pose signals. The results indicate that the pose controller developed in this paper can control the support pose well (iteration time less than 1 s and cumulative error less than 1.5 mm). Moreover, the multi-software co-simulation approach was effective for describing the complex system. The co-simulation platform proposed in this study can benefit the virtual monitoring technology for hydraulic supports.The research provides theoretical basis and technical guidance for the automation and unmanned control of underground mining

Dragline excavation simulation, real-time terrain recognition and object detection

The contribution of coal to global energy is expected to remain above 30% through 2030. Draglines are the preferred excavation equipment in most surface coal mines. Recently, studies toward dragline excavation efficiency have focused on two specific areas. The first area is dragline bucket studies, where the goal is to develop new designs which perform better than conventional buckets. Drawbacks in the current approach include operator inconsistencies and the inability to physically test every proposed design. Previous simulation models used Distinct Element Methods (DEM) but they over-predict excavation forces by 300% to 500%. In this study, a DEM-based simulation model has been developed to predict bucket payloads within a 16.55% error. The excavation model includes a novel method for calibrating formation parameters. The method combines DEM-based tri-axial material testing with the XGBoost machine learning algorithm to achieve prediction accuracies of between 80.6% and 95.54%. The second area is dragline vision studies towards efficient dragline operation. Current dragline vision models use image segmentation methods that are neither scalable nor multi-purpose. In this study, a scalable and multi-purpose vision model has been developed for draglines using Convolutional Neural Networks. This vision system achieves an 87.32% detection rate, 80.9% precision and 91.3% recall performance across multiple operation tasks. The main novelty of this research includes the bucket payload prediction accuracy, formation parameter calibration and the vision system accuracy, precision and recall performance toward improving dragline operating efficiencies --Abstract, page iii

Parallel Mining Operating Systems: From Digital Twins to Mining Intelligence

With the rapid development and modernization requirement of global coal industry, there is an emerging need for intelligent and unmanned mining systems. In this paper, the Intelligent Mining Operating System (IMOS) is proposed and developed, based on the parallel management and control of mining operating infrastructure that integrates the intelligent mining theory, the ACP-based (Artificial societies, Computational experiments, Parallel execution) parallel intelligence approaches, and the new generation of artificial intelligence (AI) technologies. To satisfy the intelligent and unmanned demand of open-pit mines, the IMOS architecture is developed by integrating the theory of digital quadruplets. The main subsystems and functions of IMOS are elaborated in detail, including a single-vehicle operating subsystem, multi-vehicle collaboration subsystem, vehicle-road collaboration subsystem, unmanned intelligent subsystem, dispatch management subsystem, parallel management and control subsystem, supervisory subsystem, remote takeover subsystem, and communication subsystem. The IMOS presented in this paper is the first integrated solution for intelligent and unmanned mines in China, and has been implemented over ten main open pits in the past few years. Its deployment and utilization will effectively improve the production efficiency and safety level of open-pit mines, promote the construction of ecological mines, and bring great significance to the realization of sustainable mining development

A virtual reality collaborative planning simulator and its method for three machines in a fully mechanized coal mining face

The existing automatic control program and its parameters for three machines in a fully mechanized Coal Mining face are static and simplex and are therefore inadequate for satisfying the complex and dynamic environment of underground coal mines. To overcome this problem, a collaborative mathematical model is established that includes the effects of a dynamic environment. A virtual reality collaborative planning simulator with methods for the three machines is also proposed based on a multi-agent system. According to the dynamic characteristics of the environment, equipment, and technologies, a fully mechanized Unity3D simulator (FMUnitySim) is designed in terms of multiple factors and multiple dimensions. The factors affecting the coordinated operation of the three machines are analyzed and modeled. The communication modes, coordination, and redundant sensing process among multiple agents, which include the shearer agent and the scraper conveyor agent, are also investigated in detail. Using this system, the key parameters of the three machines can be planned and adjusted online to design and distinctly observe the corresponding collaborative simulations of coordinated operation with multiple perspectives and in real time. Tests of different maximum shearer haulage speeds for regular or reverse transporting coal are designed; their key parameters, including the average shearer haulage speed, average follower distance, and average scraper conveyor load, are planned and simulated using FMUnitySim. The optimal parameter combination is obtained by analyzing and comparing the simulation results. The proposed FMUnitySim offers an effective means and theoretical basis for the rapid planning and safe automatic production of a fully mechanized Coal Mining face

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

Proceedings of the NASA Conference on Space Telerobotics, volume 1

The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty

Green Low-Carbon Technology for Metalliferous Minerals

Metalliferous minerals play a central role in the global economy. They will continue to provide the raw materials we need for industrial processes. Significant challenges will likely emerge if the climate-driven green and low-carbon development transition of metalliferous mineral exploitation is not managed responsibly and sustainably. Green low-carbon technology is vital to promote the development of metalliferous mineral resources shifting from extensive and destructive mining to clean and energy-saving mining in future decades. Global mining scientists and engineers have conducted a lot of research in related fields, such as green mining, ecological mining, energy-saving mining, and mining solid waste recycling, and have achieved a great deal of innovative progress and achievements. This Special Issue intends to collect the latest developments in the green low-carbon mining field, written by well-known researchers who have contributed to the innovation of new technologies, process optimization methods, or energy-saving techniques in metalliferous minerals development