Search Results (11)

China has made notable advancements in the intelligent construction of coal mines. However, for longwall top coal caving (LTCC) mining faces, a key obstacle impeding the intelligent transition of the coal-cutting process is automated control. This paper focuses on the aforementioned issue and comprehensively considers the pre-, intra-, and post-coal-caving stages. In this work, diverse detection and monitoring technologies are integrated at various stages through a computer platform, facilitating the construction of an automated coal caving control system with self-perception, self-learning, self-decision-making, and self-execution capabilities. Key technologies include ground-penetrating radar-based top coal thickness detection, inertial navigation-based shearer positioning, tail beam vibration-based identification of coal and gangue, and magnetostrictive sensor-based monitoring of the tail beam and insert plate attitude. In this study, the 12309 working face of the Wangjialing Coal Mine was experimentally validated, and the efficacy of the aforementioned key technologies was assessed. The results demonstrated that the control requirements for automated coal caving are satisfied by the maximum errors. Automatic regulation of coal caving was realized through the implementation of this system, thereby facilitating initiation and cessation and yielding promising experimental outcomes. Overall, this system offers practical insights for intelligent construction in current LTCC mining faces and the sustainable development of coal resources. Full article

The longwall system is an extraction system commonly used in coal mining in many countries, including Poland. One of the methods for reducing extraction costs is the dual use of the gateroad. In the first instance, the gateroad serves as the tailgate, and during the exploitation of the second coal panel, it functions as the headgate. Such a situation requires maintenance of the roadway behind the longwall face, which is typically challenging, due to significant stress-related loads on the support and its substantial deformation. The support design for this kind of roadway should take into consideration the dual impact of exploitation pressure and the caved zone influence behind the longwall face. This article presents the results of in-situ research conducted on two roadways behind the longwall face. In both roadways, the effectiveness of specially designed steel arch frames and rock bolt patterns were examined to minimize roadway deformations and maintain their functionality. The research project was comprised of several stages. Initially, mining and laboratory studies were conducted to determine the geomechanical parameters of the rocks. Subsequently, excavation stability and functionality forecasts were performed based on the authors’ empirical indicators. Then, numerical analyses were carried out to design support schemes (steel arches and rock bolt) in both roadways. A fully automated monitoring system with programmed data loggers was designed to check the behaviour of a specific rock mass and the support elements. The load on the steel arch support was measured with the help of load cells, while the load on the rock bolt support was carried out with the help of measurement bolts. Behind the longwall face, the loads on the wooden cribs set from the goaf side were also monitored. Additionally, the measurement station was equipped with extensometers to monitor the movement of roof layers and stress meters to determine changes in rock mass stress. Laser scanning or traditional surveying methods were also used to verify the support schemes through roadway convergence measurements. The obtained results allowed us to draw conclusions regarding the optimization of support schemes and to give recommendations for the practical application of specific reinforcements in excavations maintained behind the longwall face. Full article

The shearer positioning method is of great significance to the automation of longwall mining. The research teams in the Longwall Automation Steering Committee (LASC) of Australia and China University of Mining and Technology (CUMT) have focused on shearer positioning and identified the shearer inertial navigation system, the measurement of longwall retreat and creep displacement, and the backward calibration of the shearer trajectory as three key technologies to obtain accurate shearer positioning information. In underground environments without GPS, due to the characteristics of inertial navigation system (INS) autonomous full-parameter navigation, shearer positioning based on INS is adopted by the LASC and CUMT, and error reduction algorithms are proposed to inhibit the rapid error accumulation of INS. In order to obtain the periodic calibration information when the shearer reaches the end of the longwall face, it is necessary to measure the retreat and creep displacements in order to back-correct the shearer trajectory. Finding a suitable measurement method for this task is challenging, especially in the presence of dust and moisture. The LASC used a scanning laser and FMR 250 microwave radar to measure these two displacements, while CUMT adopted an ultra-wideband (UWB) radar. In terms of the backward calibration method, minimum-variance fixed-interval smoothing (MFS) proposed by LASC and the global optimization model (GOM) for the shearer trajectory from CUMT are described in detail. The experiment demonstrates that the GOM outperforms MFS in terms of accuracy but requires more computational resources. Therefore, our next research objective is to develop an efficient and accurate algorithm for performing backward calibration on the shearer trajectory. Full article

Space adaptability between mining equipment and coal-rock mass, to ensure the machines cut in a coal seam, is an importance technique in longwall mining automation. In order to guide the mining equipment cutting in the coal seam, a cutting path planning method based on multiple hierarchical clustering was proposed. Morphology similarity and the coplanarity measurement method were defined to evaluate the similarity of clusters. The coal seam floor series in the face-advancing direction were clustered according to the morphology similarity and coplanarity, respectively. Taking the morphology-based and coplanarity-based cluster centers as generating lines and stretching angle, respectively, the coal seam floor was reconstructed. The reconstructed floor can be regarded as the cutting path. The coal seam geological model of the 18,201 longwall face was analyzed with the proposed cutting path planning method. Comparing the reconstructed floor and original floor, the amounts of coal left and cut gangue were 1999 m³ and 1856 m³, respectively, for the segmental floor. For the case of whole floor, the amounts of coal left and cut gangue were 5642 m³ and 5463 m³, respectively. The coal loss rates only were 0.57% and 0.87% for the segmental and whole coal seam, respectively. Full article

China suffers the worst coal mine disasters in the world. Lots of miners lose their lives or suffer occupational injury. Fortunately, China is developing vigorously intelligent coal mining, which is the combination of traditional coal mining and the latest technology. Mining expects to relieve or solve coal mine safety, health and intensive labor issues and ensure energy security by applying intelligent coal mining. This paper fully reviews the promotion of intelligent coal mining to coal mine safety. Firstly, a brief history of intelligent coal mining is introduced. Then the safety motivation of the intelligent coal mine is discussed in four perspectives, including current the coal mine safety tendency, the positive impact of mechanized coal mining on safety, coal mine safety conception of “Mechanization Replacement and Automation Reduction”, and government initiatives. The intelligent prevention and control scheme of major disasters matching intelligent coal mining are also reviewed in the present paper, including intelligent gas extraction, intelligent coal and gas outburst/rock-burst prevention, and the real-time monitoring of water diversion fissure zone. Finally, the positive impacts of intelligent coal mining on safety are evaluated. Compared with traditional longwall face, the number of miners of coal cutting shift is reduced from 20~30 to 5~7, and the working environment is greatly improved. The statistics have shown that the employees in large coal mines, the mortality rates per 10⁶ tons of coal output, and the number of deaths decreased by 33%, 72.2%, and 66.9% during the period of rapid development of intelligent mining technology (2016–2021). In the future, more and more key technologies and management skills should be introduced, aiming at workless mining and the intrinsic safety of the coal mine. This paper provides a way for safety researchers around the world to understand the tendency of coal mine safety in China. Full article

The cost, complexity, lack of filling space and time create challenges in the longwall backfill operation, resulting in poor subsidence control and reduced productivity. This paper proposes an automated continuous mining and continuous backfill (CMCB) method by examining its key requirements and investigates the optimum sequence of coal panel (such as drifts) excavation to ensure ground strata control at relatively high productivity. The automated CMCB adopts the highwall mining technique underground, which enables easier automation at the workface. A numerical simulation of the Changxing coal mine in China was undertaken, and five different sequences of coal excavation were investigated, using the automated CMCB excavation parameters (assuming a 4 m width cut, 5 m mining height for a 200 m long coal slice) to determine the optimum sequence of resource excavation. The plastic zones and vertical displacement across the five models were analyzed. Simulation results of the 5 m high coal seam excavation show that the odd-even slice (OES) mining sequence, which has a vertical ground displacement of 74 mm, is the most efficient excavation method, due to its effective stress redistribution and lower induced ground displacement. Full article

Underground mining belongs to immensely complex processes and depends on many natural, technical and organizational factors. The main factor that hinders this process is the environmental conditions in which it is carried out. One of the problems associated with the use of increasingly modern machines in such conditions is the issue of unplanned downtime during their operation. This paper presents the developed methodology and IT system for recording breaks in the operation of mining machines and identifies their causes. The basis of this methodology is a sensor-based information system used to register mining machinery parameters, based on which interruptions in their operation can be determined. In order to register these parameters, an industrial automation system (together with a SCADA system supervising the process) was used, which is practically independent from the operator and enables continuous registration of these parameters. In order to identify the reasons for the recorded breaks, an IT tool was developed in the form of an application in the module of the integrated mining enterprise management support system (ERP system). This application enables (with a continuously updated database) the identification of the causes in question. Thus, the developed solution enables the objective registration of machine downtime and, for most cases, the identification of causes. The acquired knowledge, so far largely undisclosed, has created opportunities to improve the utilization level of machinery exploited in the mining production process. The paper discusses the methodology, together with the IT system, for identifying the causes of machine downtime and presents an example of its application for a shearer loader, which is the basic machine of a mechanized longwall system. The results indicate great potential for the application of the developed system to improve the efficiency of machinery utilization and the whole process of mining production. Full article

Mining in underground plants is associated with high risk. Improving work safety and increasing the productivity of longwall systems in the mining industry is a problem considering many criteria. Safety aspects concern both the crew and the machinery. The KOMAG Institute of Mining Technology designed and manufactured a geometry monitoring system based on inclinometers that meet the requirements of the ATEX directive. Monitoring of the roof support geometry is used for the prevention of loss of roof stability: roof fall or/and cave-in. The system was tested on a real object in real conditions. Full article

The article concerns the condition of automation and robotization of underground mining in Poland. Attention has been focused on the specific character of the mining industry. This limits the possibility of using robotization, and sometimes even the mechanization of certain processes. In recent years, robotic and automated machines and machine system solutions have been developed and applied in Poland. They are autonomous to a various degree, depending on the branch. The type of automation and artificial intelligence depends on the specific use. Some examples presently being used include the MIKRUS automated longwall system and autonomous device(s) for breaking rocks or mining rescue work. In Poland, fully automated plow systems produced by foreign companies are also used. Companies in Poland and international research centers are also actively engaged in the development of underwater and space mining. where robotization is of key importance. Research is also being undertaken by Robotics in Mining, euRobotics and PERASPERA as well as Space Mining Conference. Full article

Geophysical logs can be used not only for qualitative interpretation such as strata correlation but also for geotechnical assessment through quantitative data analysis. In an emerging digital mining age, such a use of geophysical logs helps to establish reliable geological and geotechnical models, which reduces safety and financial risks due to geological and geotechnical uncertainty for new and existing coal mining projects. This paper presents some examples of geological and geotechnical characterizations from geophysical logs at various coal mines in Australia and India. The applications include rock strength and coal quality estimations, automated lithological/geotechnical interpretation and geophysical strata rating, all based on geophysical logs. These derived parameters could provide input to modelling, control, even ‘digital twin’ generation in a form of geological and geotechnical models as part of the future digital mining. The outcomes can be visualized in 3D space and used for identifying the key geotechnical strata units that are responsible for caving behaviors during longwall mining. This could assist site geologists and planning and production engineers predict and manage mining conditions on an ongoing basis. Both conventional logs such as density, natural gamma and sonic and less common logging data, such as full waveform sonic, televiewer and SIROLOG spectrometric natural gamma logging data are examined for their potential applications. The geotechnical strata classification and rock strengths predicted from the geophysical logs match the laboratory tests, drill core geotechnical strata classification, core photos and the mining condition/behavior observed. These illustrate the usefulness and effectiveness of using geophysical logs for geological and geotechnical characterizations. Full article

Growing competition in the market for energy raw materials needed for power generation has led to an increasing number of measures being undertaken in the mining sector to reduce the unit costs of mining production. One of the areas that offer considerable savings in this regard is the utilisation of the technical resources owned by mines. This article is therefore focussed on analysing the utilisation effectiveness of these machines, based on the data recorded by industrial automation systems, as well as on measurements from independent surveying and chemical analysis of the excavated material’s quality. For this purpose, a methodology was developed to use the data about the operational parameters of the machines in order to analyse the effectiveness of their utilisation. It was assumed that the reliability of this assessment would depend mainly on the quality of the data used to conduct it. It was also assumed that using independent data sources for the analysis would provide objective and reliable information on the operation of the machines, devoid of any subjective feelings of the personnel or other factors. The developed methodology, based on a modified Overall Equipment Effectiveness (OEE) model, was used to analyse four machines that comprise the automated longwall system. Values were determined for each machine, including their availability, performance and product quality. This, in turn, made it possible to determine a total effectiveness indicator, based on a modified Overall Equipment Effectiveness (OEE) model, for the particular machines and the entire technical systems they form. The obtained results were used to assess the effectiveness of their utilisation and recommend corrective measures aimed at improving this metric. Moreover, the analysis results made it possible to assess the utilisation status of the machines in question. They also served as the basis for determining further lines of research, the purpose of which is to improve the effectiveness of the mining sector. The obtained results indicated that this process requires the wide application of IT tools, especially for data archiving and analysis. These tools, along with the developed model and methodology based on the analysis of large volumes of digital data, are in accord with the activities related to the implementation of Industry 4.0 idea in mining. It is the authors’ opinion that the material at hand should find a wide range of practical applications in supporting the management of technical resources within the mining sector. Full article