Mining Environment Research Articles

Visual information perception system of coal mine comprehensive excavation working face for edge computing terminal

AbstractAiming at the problems of low detection accuracy, high computational complexity and long‐time consumption of visual perception model in a complex mining environment, this research designs a visual information perception system of coal mine comprehensive excavation working face for an edge computing terminal. Firstly, the C3‐Fast feature extraction module, spatial pyramid pooling with cross‐stage partial connection (SPPCSPC) pooling module, bi‐directional feature pyramid network and lightweight decoupled detection head are used to optimize the YOLOv5s model, so as to construct the FSBD‐YOLOv5s multi‐object detection model. Secondly, the pruning and distillation algorithm is used to lighten the FSBD‐YOLOv5s model, and the model complexity is greatly reduced while maintaining the model detection accuracy. Further, the lightweight FSBD‐YOLOv5s model is migrated and deployed to the edge computing terminal platform and the TensorRT engine is used to accelerate model inference. Finally, experiments are carried out based on the data set of the coal mine comprehensive excavation working face. The experimental results show that on the edge computing terminal platform, the parameters and computational volume of the lightweight FSBD‐YOLOv5s model are reduced by 50.8% and 34.0%, while its detection accuracy and speed reach 94.0% and 43.7 fps, which can fully satisfy the requirements of the accuracy and real‐time for the coal mine engineering applications.

Morphological Enrichment and Environmental Factors Correlation of Heavy Metals in Dominant Plants in Typical Manganese Ore Areas in Guizhou, China.

Bioavailable heavy metal and their efficient phytoremediation in mining areas have major implications for environmental and human health. In this study, we investigated 12 dominant plants in a typical Mn ore area of Zunyi, Guizhou Province, China, to determine the heavy metal contents, morphologies, and environmental factors affecting Mn, Cd, Pb, Cu, Zn, and Cr in the plant parts and rhizosphere soil. The bioavailabilities and degrees of metals were evaluated using the ratios of the secondary to primary phase distributions and potential ecological risk indices. Principal component analysis, cluster analysis, positive matrix factorisation modelling, and redundancy analysis were used to trace the origins and correlations among the metals. The results indicate that the bioavailabilities were the highest for Mn and Cd in the study area, and all of the target heavy metals had bioavailabilities above the moderate ecological harm level. Statistical modelling indicates that there are four main pollution sources: mining, smelting, processing operations, and atmospheric deposition. The dominant plants had high heavy metal enrichments, bioconcentration factors, and translocation factors for Mn, Cu, Cr, Cd, and Zn. The redundancy analysis indicates that soil total N, total P, and pH affect metal absorption and distributions in Compositae and non-Compositae plants in low-N, low-P, and slightly alkaline mining environments. This study provides a feasible basis for the screening of heavy metal enrichment plants and the improvement of remediation technology in manganese ore area under the extreme environment of poor nutrition.

Implementasi Metode Reliability Centered Maintenance untuk Menunjang Ketersediaan Suku Cadang Unit Prime Mover Truck Tipe 550 Horse Power

One of mining materials transport units is a 550 horse power prime mover truck. The prime mover truck functions as the main power source of trailer unit. This research was motivated by unexpected failures of 550 horsepower prime mover truck which operating on extreme mining environments, and unreachable component lifetime also delays of part supply, which contributed to increased downtime. The research purposes are to improve and develop the best maintenance system by identifying critical components, determining reliability values, determine maintenance intervals, and ensuring spare parts availability. The research was conducted using the Reliability Centered Maintenance (RCM) method, with independent variables are failure frequency data and failure duration data. The results identified five critical components, air piping and hose, fast fuel filler, radiator components, radiator hose, and wheel stud and nut. Maintenance intervals were determined when the reliability value approached 0.6, with the air piping and hose component reaching 1750 hours of operation or every 97 days, the fast fuel filler component reaching 1,250 hours or every 69 days, the radiator and reservoir tank component reaching 2250 hours or every 125 days, the radiator hose and line component reaching 2750 hours or every 152 days, and the wheel stud and nut component of 3000 hours or every 166 days.

A Non-Source Optical Fiber Sensor for Multi-Point Methane Detection.

Fast, accurate, real-time measurement of gas concentration is an important task for preventing coal mining disasters. In order to develop an accurate monitoring method for methane gas concentration at different locations in a mine environment, a non-source optical fiber sensor for multi-point methane detection has been developed in this paper. A 16-channel fiber splitter and a multi-channel time-sharing acquisition module are employed within the sensor, enabling simultaneous detection of methane gas at 16 points by a host. Furthermore, the methane sensors are connected to the monitoring host via an all-optical method, achieving non-source and long-range detection of methane. To assess the performance of the methane gas sensor, experiments were conducted to evaluate its detection range, response time, and stability. The results indicated that the average detection error was approximately 1.84% across the full range, and the response time did not exceed 10 s. The minimum detection limit of the sensor, as determined by the 1σ criteria, was obtained as 58.42 ppm. Additionally, the concentrations of methane gas measured at varying distances (1 km, 2 km, 5 km) were found to be essentially consistent over an extended period. These results suggest that the development of this non-source optical fiber sensor holds significant potential for providing a method for mine environment, multi-point online methane gas detection.

Remediation of AMD based on hydrogeochemical zonation: A typical metal mine in China

Mining activities disrupt the natural oxidative balance underground, increasing the oxidation of metal sulfides like pyrite. This process leads to the formation of highly acidic mine drainage (AMD) with elevated concentrations of iron (Fe) and sulfate (SO42−). However, generic plugging and backfilling methods, when applied without considering the specific post-mining oxidative environments of different metal mines, often yields minimal results. To clarify the distribution of the underground redox environment after mining of a metal mine in Dexing, China, fifteen water samples from flood and dry periods, as well as fifteen borehole samples, were collected for hydrogeological and chemical analysis. For the first time, the study proposed that the redox zone could be identified and delineated through vertical analysis of water storage media, mineral composition, and hydrochemical characteristics. A hydrogeochemical cause model was constructed, revealing that AMD formation primarily occurs in oxidative and transition zones. Based on the redox zone characteristics of the study area, actual engineering sealing was performed on the oxidation and transition zones of cavity No. 23. As a result, the pH increased from 2.5 before remediation to 4.5, indicating a reduction in acidity. The concentrations of SO42− and Fe significantly decreased, reducing from 1360.0 mg/L and 147.0 mg/L before treatment to 726.0 mg/L and 23.6 mg/L after treatment; the total decrease amounting to 46.6 % and 84.0 %, respectively. The concentrations of Mn and Cu similarly, decreased by 10.7 % and 15.6 %, respectively. This study provides a novel approach and valuable reference for the refined identification and classification of redox zones after metal mine exploitation, as well as for the targeted plugging and treatment of cavities that produce AMD.

Synergistic promotion of antimony transformation in the interaction of Acidithiobacillus ferrooxidans and pyrite by driving the formation of reactive oxygen species and secondary minerals

As one of the important microorganisms in the mining area, the role of iron-sulfur oxidizing microorganisms in antimony (element symbolized as Sb) migration and transformation in mining environments has been largely neglected for a long time. Therefore, the processes of the typical iron-sulfur oxidizing bacterium Acidithiobacillus ferrooxidans (A. ferrooxidans) and pyrite interaction coupled with the migration and transformation of Sb were investigated in this paper. The bio-oxidation process of pyrite by A. ferrooxidans not only accelerates the oxidation rate of Sb(III) to Sb(V) (62.93% of 10 mg L−1 within 4 h), but also promotes the adsorption and precipitation of Sb (32.89 % of 10 mg L−1 within 96 h), and changes in the dosage of minerals, Sb concentration, and pH value affect the conversion of Sb. The characterization results show that the interaction between A. ferrooxidans and pyrite produces a variety of reactive species, such as H2O2 and •OH, resulting in the oxidation of Sb(III). In addition, A. ferrooxidans mediates the formation of stereotyped iron-sulfur secondary minerals that can act as a major driver of Sb (especially Sb(V)) adsorption or co-precipitation. This study contributes to the further understanding of the diversified biogeochemical processes of iron-sulfur oxidizing bacteria-iron-sulfur minerals-toxic metals in mining environments and provides ideas for the development of in-situ treatment technologies for Sb.

Analysis of Factors Affecting Emergency Response Linkage in Coal Mine Gas Explosion Accidents

To analyze the influencing factors of the emergency linkage of gas explosion accidents and their causal relationships, a method for analyzing the influencing factors of the emergency linkage of gas explosion accidents is proposed based on a hierarchical holographic model and Bayesian networks. Firstly, based on the hierarchical holographic model to determine the main influencing factors of the accident emergency linkage, we constructed the topological structure model of accident control, secondary disaster, and emergency rescue, and used the triangular fuzzy number to assess the a priori probability and conditional probability of the influencing factors. Next, the most likely factors affecting the accident emergency linkage are quickly identified by combining Bayesian diagnostic reasoning. Finally, sensitivity analysis is conducted to identify the key factors affecting the accident emergency linkage. The results show that the probability of normal operation of gas explosion accident emergency linkage is 78.1%, but when the coal mine environment changes, especially when multiple influencing factors occur simultaneously, the probability of normal operation of accident emergency linkage decreases significantly. Through causal analysis, the degree of influence on the operation of the accident emergency linkage in different situations can be deduced. Through diagnostic analysis, it can be seen that the emergency linkage operation is more sensitive to the two factors of the ventilation and smoke extraction system response and gas over limit, so it is necessary to pay attention to its important role in accident treatment. Meanwhile, the sensitivity analysis shows that the response of the ventilation and smoke extraction system, the accuracy of disaster sharing, the gas over limit, the technical level of the operators, and the team rescue experience are the key factors affecting the emergency response linkage in accidents. This study can provide theoretical guidance for the improvement of the emergency response linkage mechanism of coal mine gas explosion accidents as well as the decision-making of the accidents, minimize the losses of the accidents, and promote the sustainable development of the coal mining industry.

Research on Path Planning of a Mining Inspection Robot in an Unstructured Environment Based on an Improved Rapidly Exploring Random Tree Algorithm

To ensure the safe production of mines, the intelligent trend of underground mining operations is gradually advancing. However, the operational environment of subterranean mining is intricate, making the conventional path-planning algorithm used by mining inspection robots frequently inadequate for real requirements. To safeguard the mining inspection robot, targeting the problem of low search efficiency and path redundancy in the path planning of the existing rapidly exploring random tree (RRT) algorithm in the narrow and complex unstructured environment, a path-planning algorithm combining improved RRT and a probabilistic road map (PRM) is proposed. Initially, the target area is efficiently searched according to the fan-shaped goal orientation strategy and the adaptive step size expansion strategy. Subsequently, the PRM algorithm and the improved RRT algorithm are combined to reduce the redundant points of the planning path. Ultimately, considering the kinematics of the vehicle, the path is optimized by the third-order Bessel curve. The experimental simulation results show that the proposed path-planning algorithm has a higher success rate, smoother path, and shorter path length than other algorithms in complex underground mining environments, which proves the effectiveness of the proposed algorithm.

Assessment of Regional Development Using the Unit Genetic Area (GSW) Method in the Mining Environment Area of Palu City, Central Sulawesi Province

Introduction: The growth of the mining industry in Central Sulawesi is currently growing rapidly, starting from excavations A, and B to C. The Buluri area currently has many active C excavation mines, but does the area have the potential for mining area development? This research was conducted with the aim of knowing the level of potential or constraints on the development of mining areas. Method: The location of this research is located in Buluri Village, Ulujadi District, Palu City, Central Sulawesi. The method used in this research is direct mapping in the field to determine the genetic unit of the region and scoring on each subfactor of the genetic unit of the region to determine the development of mining areas. Results and Discussion: The results showed that in the Buluri area, there are two regional genetic units, namely the genetic unit of the moderately deformed porphyry andesite plain area (1221) and the genetic unit of the moderately deformed porphyry andesite hills area (1222). Conclusion: Based on the results of subfactor calculations in each regional genetic unit, it is found that the genetic unit of the moderately deformed porphyry andesite plain area (1221) is included in the low-level mining area development category, and the genetic unit of the moderately deformed porphyry andesite hills area (1222) is included in the medium- level mining area development category.

Study on the change of miners' psychological state under different illuminance levels

The poor lighting environment in the underground coal mine is easy to cause the miners to have psychological irritability, which leads to the occurrence of accidents. In order to reduce the incidence of accidents and ensure the personal safety of miners. In this paper, different illumination levels are used as control variables. With the help of cognitive ability tests commonly used in psychology, accuracy(AC), reaction time(RT)and performance indicators(PI) are selected to describe how different illumination levels affect the psychological state of miners. The results show that: (1) In the two selected cognitive ability test tasks, when the illumination level is very low, the AC is not high and the RT is longer. As the illumination increases, the AC in the cognitive test task becomes higher and the RT becomes faster. The optimal value is reached at 200lux–300lux.At this time, the illumination level increases again, the AC value decreases, and the RT value increases. When the illuminance is lower than 200Lux, the results of the two tasks are not the same, but when 200Lux∼300Lux, the PI values are larger, and then increase the illuminance, the PI value decreases. (2)The regression analysis of three indicators and illuminance level was carried out, and the binary linear regression equation of different illuminance levels and PI/RT was established to monitor the influence of illuminance on the psychological state of miners. (3) Reasonable control of lighting environment can effectively promote the cognitive ability of miners in the work, and minimize the risk of coal mine accidents.

Assessing the hazard of diesel particulate matter (DPM) in the mining industry: A review of the current state of knowledge

In the confined spaces of underground mines, the exposure of over 10,000 miners in the U.S. to diesel exhaust and diesel particulate matter (DPM) is an occupational inevitability, particularly in metal and nonmetal mineral extraction. These workers routinely operate amidst diesel-powered equipment, often outdated and highly polluting, extracting resources such as limestone, gold, and salt. The acute health effects of such exposure are significant, leading to symptoms like headaches and flu-like conditions, with the impact being more pronounced in these closed work environments. This review scrutinizes DPM’s hazard in the mining sector, consolidating the extant knowledge and exploring ongoing research. It encapsulates our understanding of DPM’s physicochemical properties, existing sampling methods, health ramifications, and mitigation technologies. Moreover, it underscores the necessity for further study in areas such as the evolution of DPM’s physicochemical attributes, from its genesis at high-pressure, high-temperature conditions within diesel engines to its emission into the mine atmosphere. A key research gap is the intricate interaction of DPM with specific characteristics of the mine environment—such as relative humidity, ambient temperature, the presence of other mineral dust, and the dynamics of ventilation air. These factors can significantly alter the physicochemical profile of DPM, influencing both its in-mine transport and its deposition behavior. Consequently, this can affect the respiratory health of miners, modifying the toxicity and the respiratory deposition of DPM particles. Identified research imperatives include (1) the advancement of instrumentation for accurate number measurement of DPM to replace or supplement traditional gravimetric methods; (2) the development of long-lasting, cost-effective control technologies tailored for the mining industry; (3) an in-depth investigation of DPM interactions within the unique mine microclimate, considering the critical components like humidity and other aerosols; and (4) understanding the differential impact of DPM in mining compared to other industries, informing the creation of mining-specific health and safety protocols. This review’s findings underscore the urgency to enhance emission control and exposure prevention strategies, paving the way for a healthier underground mining work environment.

Coagulation tests of waste pulp from copper mineral processing

The sustainable use of water in mineral processing is essential for maintaining the ecosystem that supports the mining environment and, consequently, for the operation itself that uses water resources. As an area that has such a finite resource as a basic operating condition and that uses this resource on a large scale, it is necessary to constantly seek to optimize its use, having as pillars quality and economy in the treatment of effluents generated. It is in stages like this that coagulating reagent work. In the processing unit in question, more than 90% of the water is recirculated and reused, a process that relies on the support of a coagulant to accelerate the sedimentation of solids and guarantee the reuse of water of sufficient quality to provide operations with the solvent necessary for the environment. physicochemical. The coagulant currently used in tailings dam operations is aluminum sulfate. Due to the high use and cost spent on this reagent, tests were conducted with two other alternative coagulants (iron III chloride and iron III sulfate), comparing the cost-benefit between the reagents assessed. To this end, a cost-benefit factor was used, calculated using the cost of the reagent, dosage, residual turbidity of the clarified liquid and the sedimentation speed of the solids. After the tests, it was found that aluminum sulfate, the reagent used in the operation until then, was the best option among the reagents assessed. However, a reduction of 21.43% in the dosage currently used of this reagent by the company, maintaining the final turbidity target is possible, thus generating cost reduction.

Research on Coal Flow Visual Detection and the Energy-Saving Control Method Based on Deep Learning

In this paper, machine vision technology is used to recognize the coal flow on a conveyor belt and control the running speed of a motor according to the coal flow on the conveyor belt to achieve an energy-saving effect and provide technical support for the sustainable development of energy. In order to improve the accuracy of coal flow recognition, this paper proposes the color gain-enhanced multi-scale retina algorithm (AMSRCR) for image preprocessing. Based on the YOLOv8s-cls improved deep learning algorithm YOLO-CFS, the C2f-FasterNet module is designed to realize a lightweight network structure, and the three-dimensional weighted attention module, SimAm, is added to further improve the accuracy of the network without introducing additional parameters. The experimental results show that the recognition accuracy of the improved algorithm YOLO-CFS reaches 93.1%, which is 4.8% higher, and the detection frame rate reaches 32.68 frame/s, which is 5.9% higher. The number of parameters is reduced by 28.4%, and the number of floating-point operations is reduced by 33.3%. These data show that the YOLO-CFS algorithm has significantly improved the accuracy, lightness, and reasoning speed in the coal mine environment. Furthermore, it can satisfy the requirements of coal flow recognition, realize the energy-saving control of coal mine conveyor belts, and achieve the purpose of sustainable development of the coal mining industry.

The effect of bacteria on uranium sequestration stability by different forms of phosphorus

ABSTRACT Immobilisation of uranium (U (VI)) by direct precipitation of uranyl phosphate (U-P) exhibits a great potential application in the remediation of U (VI)-contaminated environments. However, phosphorus, vital element of bacteria’s decomposition, absorption and transformationmay affect the stability of U (VI) with ageing time. The main purpose of this work is to study the effect of bacteria on uranium sequestration mechanism and stability by different forms of phosphorus in a water sedimentary system. The results showed that phosphate effectively enhanced the removal of U (VI), with 99.84%. X-Ray Diffraction (XRD), Scanning Electron Microscopy and Energy Dispersive Spectrometer (SEM-EDS), and X-ray Photoelectron Spectroscopy (XPS) analyses imply that U (VI) and U (IV) co-exist on the surface of the samples. Combined with BCR results, it demonstrated that bacteria and phosphorus have a synergistic effect on the removal of U (VI), realising the immobilisation of U (VI) from a transferable phase to a stable phase. However, from a long-term perspective, the redissolution and release of uranium immobilisation of U (VI) by pure bacteria with ageing time are worthy of attention, especially in uranium mining environments rich in sensitive substances. This observation implies that the stability of the uranium may be impacted by the prevailing environmental conditions. The novel findings could provide theoretical evidence for U (VI) bio-immobilisation in U (VI)-contaminated environments.

Characteristics of deformation and damage of surrounding rock along the top roadway in the working face of an isolated island and its evolution law

This study investigates the deformation and damage characteristics of the surrounding rock along the top return mining roadway of an isolated island working face at different stages and reveals its damage mechanism and evolution law. Utilizing a mine in Yangquan City, Shanxi Province, China, as the engineering background, this research employs FLAC 3D numerical simulation and on-site measurements. The findings suggest that the evolution of the plastic zone along the top roadway of the 15,106 island face is largely similar during both the excavation and mining periods. The plastic zones on either side of the roadway are expanding asymmetrically and gradually merging into the plastic zone of the coal pillar. In the destructive stage, the sub-gangs of the roadway are penetrated, indicating the progression into the plastic zone. The investigation points to extensive damage on the larger side of the roadway, the development of fissures, and the significant depth of damage as primary causes of roadway deformation. Moreover, the extent of the plastic zones on both sides of the roadway correlates positively with their relative distance. Continuous monitoring reveals an ongoing increase in roadway displacement, consistent with general observations in coal mining. The results provide valuable insights for optimizing support structures in similar mining environments.

Numerical studies on the effects of the hybrid cooling and dust suppression solution in hot fully-mechanized mining face

With the increasing depth of coal mining, the hot and humid environment at the mining faces is becoming more severe. Mining in these conditions, coupled with the hazardous effects of coal dust, poses a significant risk to the health of coal miners. To improve the working conditions in underground coal mines, this study proposes a hybrid solution that combines evaporative cooling and dust suppression in fully mechanized working faces. Numerical models of the mining face are also created to simulate the cooling effects of the proposed solution. Additionally, the migration laws of water droplets from the spray system are also studied. The results indicate that the proposed solution can effectively improve thermal environments and suppress coal dust. This research can enhance the workplace safety in underground coal mines and provide valuable insights for addressing high airflow temperatures and concentrated dust levels.

Unveiling Soil Microbiome Adaptation and Survival Strategy Under Vanadium Stress in Nationwide Mining Environments

Unveiling Soil Microbiome Adaptation and Survival Strategy Under Vanadium Stress in Nationwide Mining Environments

Оценка хозяйственных рисков при реализации технологий угледобычи в современных условиях недропользования

Introduction. This paper presents research in the field of methodology of assessment and monitoring of associated under ground coalmining risks in order to level their impact on the resulting technical and economic indicators of production and economic activities in modern conditions of subsoiluse. The functioning of technological systems of coal mining enterprises at the present stage of subsurface use occurs in a highly dynamic and highly variable functional environment with a fair degree of uncertainty, which is generated by a significant variety of parameters and characteristics of the initial mining, geological and mining engineering environment, which, in turn, generates the emergence of various groups and risk factors for subsurface use. The established procedures and methods of risk forecasting currently do not give satisfactory results due to the globalization of world markets and high volatility of prices for coal products. Leveling the negative degree of influence of the risk component on the resulting indicators – indicators of technical and economic activity can be achieved through the introduction of an operational system for assessing and monitoring various groups of risk factors. Materials and methods. For the purpose of evaluation, it is proposed to use the methodological and methodological foundations of the method called “vector norms”, which involves the use of Affine space, the constituent areas of compromises and the introduction of utility estimates. A complete model representation of the assessment and monitoring of the impact of various risk factors of subsurface use, taking into account their clustering and ranking, is presented. The algorithmic support of this method is reduced to the following components-iterations: 1. Formation of criteria-based assessment matrices of various factors of subsurface use risk groups. 2. Assignment of optima to evaluation criteria. 3. In order to ensure the legality of the use and implementation of mathematical procedures and operations, the reduction of multi-dimensional evaluation criteria to a relative form, taking into account the assigned optima. 4. Formation of the objective function of the “norm of the vector” (integral indicator) and the development of a procedure for selecting the optimal option. Since the use of the methodological and methodological foundations of the method called “vector norms” allows us to form quantitative estimates of the presented factors-types of risk of subsurface use, this makes it possible to implement the clustering procedure or ranking of a selected set of coal mining enterprises in conjunction with existing risk areas. Results. Quite high values of correlation coefficients were obtained with a significant closeness of the relationship of inversely proportional dependencies of generalizing integral indicators of the degree of risk and the level of achievement of planned indicators and development of production capacity with the level of operational profitability from the conduct of production and economic activities of coal mining enterprises with a directly proportional dependence on the operating costs of mining 1t of coal. Discussion. Сomplete model representation of the assessment and monitoring of the impact of various risk factors of subsurface use, taking into account their clustering and ranking, is presented. As a practical component of the research, variable series of areas of integral degree of risk in the functional environment of Kuzbass coal mines are presented. The use of software modules for correlation and regression analysis, taking into account three-year retrospective dynamics, made it possible to establish the legality and objectivity of the proposed methodological apparatus for integrated risk assessment of the implementation of coal mining technologies in modern conditions of subsurface use. Conclusion. The results of the implementation of the theoretical components of the methodology and model representations of the developed conceptual foundations for the integrated risk assessment of the implementation of coal mining technologies in modern conditions of subsurface use, taking into account five-year retrospective dynamics, showed that in the Kuznetsk basin there was a steady tendency to reduce the cluster of coal mines, which is characterized by high risks of carrying out production and economic activities in the presence of a disproportion of resource potential (the emergent part). The accompanying processes of formation of this trend are manifested in a quantitative increase in the functional units of the rating cluster of group 2B with an average resource potential and inherent moderate risk. It is within this cluster that strategies for prioritizing investments for the development and renewal of technological systems and structures of coal mining are being formed, since only they are able to provide the fastest possible return on invested funds. Resume. The article presents the results of research in the field of methodology for assessing and monitoring the risks associated with underground coal mining in order to level out their impact on the resulting technical and economic indicators of production and economic activity in modern conditions of subsoil use. The research results can be useful in the implementation of coal mining technology in modern conditions of subsoil use.

A new network model for multiple object detection for autonomous vehicle detection in mining environment

AbstractConsidering the challenges of low multi‐object detection accuracy and difficulty in identifying small targets caused by challenging environmental conditions including irregular lighting patterns and ambient noise levels in the mining environment with autonomous electric locomotives. A new network model based on SOD−YOLOv5s−4L has been proposed to detect multi‐objects for autonomous electric locomotives in underground coal mines. Improvements have been applied in YOLOv5s to construct the SOD−YOLOv5s−4L model, by introducing the SIoU loss function to address the mismatch between real and predicted bounding box directions, facilitating the model to learn target position information more efficiently. This research introduces a decoupled head to enhance feature fusion and improve the positioning precision of the network model, enabling rapid capture of multi‐scale target features. Furthermore, the detection capability of the model has been increased by introducing the small target detection layer which is developed by increasing the number of detection layers from three to four. The experimental results on multiple object detection dataset show that the proposed model achieves significant improvement in mean average precision (mAP) of almost 98% for various types of targets and an average precision (AP) of nearly 99% for small targets on the other hand it achieves 5.19% (mAP) and 9.79% (AP) compared to the YOLOv5s model. Furthermore, comparative analysis with other models like YOLOv7 and YOLOv8 shows that the proposed model has superior performance in terms of object detection.

Energy and deformation field evolution characteristics of layered cemented paste backfill under cyclic loading and unloading

Due to the mining environment, layered cemented paste backfill (LCPB) is usually subjected to the cyclic pressure. Therefore, it is of great significance to investigate the mechanical behavior, failure mode and energy evolution characteristics. LCPB samples were prepared and subjected to constant lower limit cyclic loading and unloading test. The digital image correlation (DIC) technology was applied to monitor deformation field of LCPB. The obtained results indicate that: (1) The area of the hysteresis loops increases sequentially with increasing unloading stress level, while the spacing between the hysteresis loops gradually increases, showing the typical “dense-sparse” two-stage variation law. (2) Energy density and the unloading stress level is in agreement with the power function. The limiting elastic energy density (uemax) shows a linear decrease with the increase of h. The exponential function can well characterize the quantitative relationship between uemax and c/t ratio. (3) The damage mode of LCPB gradually tends to x-shape shear-dominated damage with the increase of h. The damage mode of LCPB is gradually dominated by shear-type damage with the decrease of c/t ratio. Ultimately, the findings of this work can provide a reference for the design of LCPB.