2023 Vol. 49, No. 10

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Overview
Research on state perception and analysis technology of hydraulic support in fully mechanized working face
LI Jian, REN Huaiwei, GONG Shixin
2023, 49(10): 1-7, 103. doi: 10.13272/j.issn.1671-251x.2023040075
<Abstract>(437) <HTML> (112) <PDF>(98)
Abstract:
The intelligence of fully mechanized working face is a key link in the intelligence of coal mines. The perception and analysis of hydraulic support state is the premise and foundation of intelligent control of fully mechanized working face. The pressure and posture of hydraulic supports are key state data that can be directly monitored. The fusion analysis of the two is the basis for intelligent control and execution of hydraulic supports. Taking the pressure and posture of hydraulic supports as the research object, an state perception architecture for intelligent fully mechanized working face is introduced. The current status of hydraulic support pressure perception and analysis technology is summarized from two perspectives: hydraulic support stress and overlying rock pressure. It is pointed out that the current big data based mine pressure analysis has not been applied, the mine pressure and roadway pressure data at the working face have not been synchronously measured, the full face data analysis of the entire mining area has not been achieved, and there is insufficient attention paid to advanced hydraulic support. The paper elaborates on the principles and methods of hydraulic support posture perception, and summarizes the existing hydraulic support posture analysis methods. The necessity of pressure-posture fusion analysis for hydraulic support is analyzed. The existing methods for pressure-posture fusion analysis of hydraulic supports are summarized. The paper explores the development trend of hydraulic support state perception and analysis technology in fully mechanized working face. It is suggested to do in-depth research on big data technology, multidimensional data fusion perception and analysis technology, and digital twin technology in the application of hydraulic support state perception and analysis, so as to achieve the precise analysis of hydraulic support state data, intelligent control and decision-making.
Special of Intelligent Power Supply and Distribution Technology in Coal Mines
Recognition method of the squeezing force of shearer dragging cable based on improved deep forest
SHI Gang, LEI Zhipeng
2023, 49(10): 8-16, 51. doi: 10.13272/j.issn.1671-251x.2023050042
<Abstract>(233) <HTML> (77) <PDF>(27)
Abstract:
The dragging cable of shearer is often subjected to external squeezing pressure during operation, which causes partial discharge of the cable insulation and affects the service life of the cable. The existing research focuses on the analysis of partial discharge law and severity, and cannot evaluate the magnitude of stress borne by ethylene propylene rubber insulated cables. This results in the inability to grasp the operating status of mining ethylene propylene rubber insulated cables. In order to solve the above problems, a method based on improved Stacking-deep forest (S-DF) is proposed for recognizing the squeezing force of shearer dragging cables. The partial discharge of shearers dragging cables under different squeezing pressures is measured through experiments. The variation law of partial discharge spectra, average discharge current, maximum discharge amount, and breakdown field strength with the applied squeezing pressure and voltage are analyzed. The statistical feature parameters of partial discharge are calculated. Based on statistical feature parameters, the S-DF model is used to recognize the magnitude of squeezing pressures. The S-DF model introduces Stacking ensemble algorithm in deep forest (DF) to improve recognition accuracy. The research results indicate that under different voltages, the maximum discharge capacity and average discharge current decrease with the increase of extrusion pressure. The breakdown field strength shows a trend of first increasing and then decreasing with the increase of squeezing pressure. When the squeezing pressure is greater than 2 000 N, the breakdown field strength is lower than that of the non squeezing one. The statistical feature parameters of partial discharge under different squeezing pressures can be used as discharge fingerprints. The S-DF model can accurately recognize the magnitude of squeezing pressure on cables, and the recognition rate is higher than other traditional classification algorithms.
Research on the application of modulated model predictive control in coal mine power quality management based on STATCOM
ZHANG Baojun, MENG Qinglin, LIU Peng, JI Xiang, LIU Wei, ZHANG Dezheng, LU Weiqiang
2023, 49(10): 17-25. doi: 10.13272/j.issn.1671-251x.18087
<Abstract>(608) <HTML> (64) <PDF>(18)
Abstract:
A large number of power electronic devices and nonlinear loads are connected to the coal mine power grid, causing a large amount of current harmonics and reactive power in the coal mine power grid. It seriously endangers the power quality of the coal mine power grid. The traditional coal mine power quality control strategies mostly use proportional integral (PI) regulators to control static synchronous compensator (STATCOM) to achieve harmonic suppression and reactive power compensation. But their parameters are difficult to adjust and their dynamic response is slow. In order to solve the above problems, a STATCOM control strategy based on modulated model predictive control (M2PC) is proposed. Firstly, the ip-iq method is used to detect the harmonic current and reactive current in the power grid as the reference current for M2PC. Secondly, based on the reference current and STATCOM mathematical model, the duty cycle and sector cost function of the two effective vectors and zero vectors for each sector is calculated. Thirdly, by minimizing the cost function, the optimal sector and the duty cycle of the two optimal effective vectors and zero vectors corresponding to that sector are obtained. Finally, according to the space vector modulation (SVM) method, switching pulses are allocated to achieve a fixed switching frequency. It thereby controls STATCOM to emit compensation current to offset harmonic and reactive currents in the power grid. The simulation and experimental results show that before the adopting of M2PC based STATCOM, the grid side current distortion is severe, the reactive power fluctuation on the grid side is large. The power factor on the grid side fluctuates and is less than 1. After the adopting of M2PC based STATCOM, the total harmonic distortion rate (THD) of the grid side current is significantly reduced due to STATCOM compensating for the harmonic current on the grid side. Moreover, due to STATCOM compensating for the required reactive power of the load, the reactive power on the grid side remains basically 0. The power factor on the grid side remains stable at 1, effectively improving power quality.
Non-communication protection of coal mine DC distribution lines based on transient current derivation
WEI Zhaoyang, DUAN Jiandong
2023, 49(10): 26-34. doi: 10.13272/j.issn.1671-251x.2022120024
<Abstract>(497) <HTML> (42) <PDF>(14)
Abstract:
The fault current of coal mine DC power supply and distribution lines has the features of large amplitude and high rise rate, which is an important factor threatening the safety and stability of the power supply system. The method of using electrical features of DC distribution systems to achieve fault recognition rarely considers the actual situation of protective equipment. It makes it difficult to handle equipment errors and disturbances, and it does not meet the reliability requirements of relay protection. The active protection methods based on power electronic converters rarely utilize fault electrical information and rely solely on equipment action features to achieve fault removal. It often fails to meet the quick action requirements of relay protection. In order to solve the above problems, a non-communication protection scheme for coal mine DC distribution lines based on transient current derivation is proposed. The second derivative of the discharge current of the parallel capacitor on the DC side is used as the protection acceleration criterion. If the acceleration criterion is met, it will start the acceleration action. If the acceleration criterion is not met, it will act according to the established delay of the circuit breaker. When a fault occurs, the current is directed towards the fault point. The change in power flow direction can be used to preliminarily determine the direction of the fault, forming a non-communication protection. It will accelerate the tripping of the circuit breakers at both ends of the fault line, thereby shortening the fault removal time. The simulation results show that under different fault positions, transition resistors, and fault types, if the acceleration action can effectively start, the non-communication protection scheme of coal mine DC distribution lines based on transient current derivation can quickly remove faults and reduce fault time. If the acceleration action cannot be started, the protection scheme can also cooperate with the established delay to determine the fault type and section and remove the fault.
Degradation monitoring and fault diagnosis of mining cables based on current harmonic features
LU Runge, XU Tao, ZHOU Zhuobei, LI Mao, HUANG Chaocan
2023, 49(10): 35-42. doi: 10.13272/j.issn.1671-251x.18144
<Abstract>(802) <HTML> (56) <PDF>(22)
Abstract:
Mining cables are affected by the harsh environment of coal mines, and are prone to insulation degradation and sheath damage. The traditional offline diagnostic methods such as low-voltage pulse method and partial discharge method are often used for detecting mining cables. The methods are complex to operate and have low accuracy, making it difficult to meet the needs of modern coal mine production. However, the existing harmonic based cable fault diagnosis methods have problems such as bulky detection devices, low detection precision, and difficulty in application in coal mines. In order to solve the above problems, a degradation monitoring and diagnosing method of mining cables based on current harmonic features is proposed. The method extracts high-order harmonic content information in cables as fault feature vectors, normalize the feature vectors, and then import them into extreme gradient boost tree (XGBoost) model. Combined with known cable fault degradation value data, a training sample set is formed to train the XGBoost model. Finally, the method uses the constructed XGBoost model to monitor and diagnose cable degradation in real-time. The simulation results show that the relative energy of the extracted high-order harmonic vectors from different parts of the cable is significantly different. The extracted high-order harmonic vectors can characterize the operating status of different parts of the cable. The goodness of fit parameter R2 of the XGBoost model is as high as 0.93, and the error is small. The case analysis results verify that the degradation monitoring and fault diagnosis method of mining cables based on current harmonic features can provide real-time and accurate monitoring and diagnosis of the operation status and degradation faults of mining cables.
Risk assessment method for external breakage of overhead lines in mining areas
LIU Zhenguo, YU Hai, FENG Shiguang, ZHANG Yu
2023, 49(10): 43-51. doi: 10.13272/j.issn.1671-251x.2023070004
<Abstract>(170) <HTML> (87) <PDF>(18)
Abstract:
The operating environment of overhead lines in mining areas is harsh. The lines are easily affected by external factors, leading to line breakage. It is necessary to accurately evaluate the risk level of external breakage of overhead lines in mining areas. However, existing qualitative evaluation methods have shortcomings such as strong subjectivity and poor comparability of evaluation results. Although quantitative evaluation methods have high objectivity, the accurate evaluation is based on a large amount of high-quality data. In order to balance the objectivity of the evaluation results and the difficulty of obtaining evaluation data, the likelihood exposure consequence (LEC) method in semi quantitative evaluation method is adopted. Based on the actual operating environment of mining area lines, an improved LEC method is proposed for the risk assessment of external breakage of overhead lines in mining areas. Firstly, by analyzing the actual operating environment of overhead lines in mining areas, the main risk factors of external breakage are identified. The risk assessment index system for external breakage of overhead lines in mining areas is constructed. Secondly, using the YOLOv5 based image recognition strategy to identify the sources of external breakage risk in the line environment, real-time acquisition of external breakage risk data of the line is achieved. It overcomes the shortcomings of poor real-time performance and insufficient data volume obtained manually by traditional LEC methods. Thirdly, the element assignment rules of the LEC method are improved. The elements are assigned based on image recognition results to achieve real-time evaluation of the risk of external breakage to the line. It improves the objectivity of the evaluation results and solves the problem of the traditional LEC method's element assignment relying on the personal experience of the evaluator. Finally, in order to measure the superimposed impact of various risks, the analytic hierarchy process is used to determine the weight of each risk evaluation index. Ultimately, the comprehensive assessment of the risk of external breakage to overhead lines in mining areas is achieved. A case study is conducted during the actual operation of an open-pit coal mine. The results show that this method can effectively evaluate the risk level of external breakage of overhead lines in specific scenarios.
Analysis and Research
Research on fault detection of belt conveyor roller based on thermal infrared image
GUO Yanqiu, MIAO Changyun, LIU Yi
2023, 49(10): 52-60. doi: 10.13272/j.issn.1671-251x.2022120051
<Abstract>(845) <HTML> (60) <PDF>(74)
Abstract:
Currently, the inspection robot for belt conveyors equipped with infrared acquisition devices is limited in movement. There are problems such as inability to collect data, process data, upload data to monitoring terminals in real-time and complete remote fault detection, insufficient endurance and so on. A fault detection method of belt conveyor roller based on thermal infrared images has been proposed. The belt conveyor inspection robot is equipped with a roller fault detector and an infrared thermal imager. The infrared thermal imager transmits the collected roller thermal infrared image sequence and temperature data to the roller fault detector for roller fault detection. The WH-L101 wireless transmission module in the roller fault detector is used to send the detection results to the upper computer. A belt conveyor roller fault detection algorithm is proposed. The algorithm uses the YOLOv5s object detection algorithm to extract the region of interest (ROI) of the roller thermal infrared image. The image of the ROI is filtered using Wiener filtering and adaptive median filtering algorithms. The filtered ROI image is enhanced by using adaptive histogram equalization and image sharpening algorithms. The Otsu image segmentation algorithm based on morphology is used to segment the enhanced ROI image, obtaining the roller image to be detected. The Harris corner detection algorithm is used to extract the features of the roller image, and obtain the position information of the roller. The temperature information of the corresponding position is extracted, and a roller fault detection algorithm based on the relative temperature difference method is used to determine the idler fault. The experimental results show: ① The average accuracy of object detection in the roller ROI extracted by YOLOv5s network model is 99.12%. ② The proposed roller fault detection algorithm has an average accuracy of 97.625% and a frame rate of 16 frames per second for detecting roller faults (no faults, bearing rust, roller jamming, and cylinder wear). ③ The detection results are transmitted to the upper computer through a wireless transmission module, which can display the fault type and key area temperature, and provide an alarm.
A deformation monitoring method for coal mine roadway based on 3D laser scanning
DAI Wenxiang, CHEN Lei, YAN Pengfei, WANG Lixin, LI Bo, YUAN Pengzhe
2023, 49(10): 61-67, 95. doi: 10.13272/j.issn.1671-251x.2023010045
<Abstract>(493) <HTML> (63) <PDF>(71)
Abstract:
The traditional monitoring methods for coal mine roadway deformation have problems such as incomplete data collection, non intuitive data format, poor precision, and inability to achieve continuous monitoring of the entire roadway deformation. In order to solve the above problems, a deformation monitoring method for coal mine roadway based on 3D laser scanning is proposed. Firstly, the method uses 3D laser scanning technology to obtain real 3D point cloud data of coal mine roadways. Secondly, the deep learning model VoxelNet is used to detect and denoise 3D laser scanning data, converting unordered point cloud data into high-dimensional feature data. The Alphashape algorithm is used to fit the discrete points of the extracted roadway cross-section. The multi-dimensional difference calculation based on the difference method is used to obtain specific data of roadway deformation, achieving full coverage of roadway deformation monitoring in the mining area. The 3D laser scanning technology is applied to deformation monitoring of the 30507 working face in Tashan Coal Mine. The cross-sectional analysis and 3D overall analysis are conducted on the 3D point cloud data of the roadway. The analysis results indicate that the main deformation in the area can be directly observed through the relative deviation of the section contour of the second stage roadway. If the upper contour deviates inward, the roof will collapse. If the lower contour deviates outward, the floor will bulge. As the distance between the measuring point and the working face gets closer, the color of the attached color model leans towards red and blue. The darker the color, the greater the deformation of the roadway.
Research on image recognition methods for coal rock fractures
HAO Tianxuan, XU Xinge, ZHAO Lizhen
2023, 49(10): 68-74. doi: 10.13272/j.issn.1671-251x.2022120081
<Abstract>(115) <HTML> (97) <PDF>(37)
Abstract:
Coal rock fractures are closely related to gas migration and affect the stability of coal rock. Studying the complex fracture system in coal rock is of great significance for roadway support and gas extraction. At present, the recognition methods for coal rock fracture images fail to comprehensively consider the features of the number, position, morphology, and category of fracture in coal rock images, making it difficult to obtain effective information. Taking the coal rock images of excavation face in the No.8 Coal Mine of Hebi Coal and Electricity Co., Ltd. as the research object, a pixel level intelligent recognition method based on U-Net network for coal rock fractures and categories is proposed. The histogram equalization, Gaussian bilateral filtering, and Laplace operator are used to preprocess coal rock images to improve image quality and extract fracture feature information more effectively. The features of coal rock fractures are recorded by observing and divided into 7 categories, the selected coal rock fracture images are amplified, and the images are annotated at the pixel level using Labelme software to establish a coal rock fracture dataset. The U-Net network is used to construct a coal rock fracture recognition model. After debugging, the network batch size and learning rate parameters are determined. The experiment shows that when the number of iterations reaches 300 or more, the average recognition accuracy of the model is 87%, the average recall rate is 92%, the average intersection to parallel ratio is greater than 85%, and the average pixel accuracy of the category is greater than 80%. The coal rock fracture recognition model is validated by collecting underground coal rock mining fractures and laboratory tensile exogenous fractures. The results show that the model can effectively extract target feature information and distinguish it from background feature information, and can accurately locate and recognize a single fracture.
Research on the health evaluation and prediction system for mine hoists
WANG Chen, YANG An
2023, 49(10): 75-86. doi: 10.13272/j.issn.1671-251x.2023030092
<Abstract>(670) <HTML> (79) <PDF>(42)
Abstract:
In response to the relatively limited research on health evaluation and prediction of the entire system of mine hoists, a health evaluation index system and comment set for mine hoists have been established. The health evaluation and prediction system for mine hoists has been designed. A fuzzy comprehensive evaluation method for the health of mine hoists is proposed to address the issues of insufficient utilization of monitoring data from various components of mine hoists, and the inability of health evaluation results to meet actual production needs. The method introduces relative degradation degree to characterize the health of different types of indicators of the hoist. The method uses health degree to quantify the health of mine hoists. The fuzzy comprehensive evaluation method is used to calculate the health of mine hoists. The analytic hierarchy process (AHP) is improved by replacing the 1-9 scale with an exponential scale to reduce computational complexity. The method uses CRITIC objective weighting method and combines subjective and objective weights to calculate the comprehensive weights of each subsystem and indicator. Based on the fuzzy comprehensive evaluation calculation process and the maximum membership principle, the health evaluation results and fault causes of the mine hoist are obtained. On the basis of the health evaluation results of the mine hoist, the Harris hawks (HHO) algorithm is used to optimize the important parameters of the support vector regression (SVR) model. The HHO-SVR model is constructed to predict the health of the mine hoist, improving the accuracy of the health prediction results. The experimental results show that the fuzzy comprehensive evaluation method can accurately evaluate the health of the hoist. Compared with particle swarm optimization support vector regression (PSO-SVR), genetic algorithm optimization support vector regression (GA-SVR), and grey wolf algorithm optimization support vector regression (GWO-SVR) models, the prediction results of the HHO-SVR model are closer to the actual values and have better prediction performance.
Forward simulation of electromagnetic waves in coal gangue model based on improved bidirectional peak-valley search algorithm
SHI Xiangyu, SI Lei, WANG Zhongbin, WEI Dong, GU Jinheng
2023, 49(10): 87-95. doi: 10.13272/j.issn.1671-251x.18090
<Abstract>(194) <HTML> (48) <PDF>(18)
Abstract:
Realizing automatic recognition of coal gangue content during the top coal caving process is an important goal of fully mechanized mining automation. The existing methods for automatic recognition of coal gangue content have problems such as low accuracy and real-time performance. The coal gangue mixture generated during the top coal caving process is a three-phase medium formed by coal, gangue, and air. The electrical parameters of each phase medium are different. The propagation features of electromagnetic waves are also different in different components of the mixed three-phase medium. There is a significant difference in the dielectric constant between coal blocks and gangue. By studying the electrical parameters of coal gangue mixtures with different gangue contents, new ideas and methods can be provided for automatic recognition of gangue content in top coal caving working faces. In order to explore the electrical differences of coal gangue mixtures with different gangue contents, a bidirectional peak-valley search algorithm based on the divide and conquer strategy is proposed. Based on this algorithm, a multiphase discrete random medium model of coal gangue is established. Based on the Maxwell equations and their constitutive relationship equations, the electromagnetic wave forward simulation of the established model is performed using the finite difference time domain method. The analysis shows that after improving the bidirectional peak-valley search algorithm based on the divide and conquer strategy, there is a clear phase interface between the coal, gangue, and air phases in the coal gangue multiphase discrete random medium model. Moreover, there is a greater degree of dispersion of each phase and no aggregation phenomenon. Therefore, the local medium can also reflect the overall electrical parameters, which can meet the requirements of the medium model for electromagnetic wave forward modeling. The forward simulation results indicate the following points. ① The frequency of the excitation signal will affect the amplitude of the transmitted wave. In the 12 GHz range, the higher the frequency of the excitation signal, the greater the amplitude of the transmitted wave. Low frequency will reduce the robustness of the signal, and the excitation frequency should be higher than 2 GHz. ② The gangue content of the coal gangue mixture is positively correlated with the overall equivalent dielectric constant of the medium. The higher the gangue content, the greater the propagation loss of the electromagnetic wave signal. The smaller the amplitude of the signal received by the receiving plane, the longer the time it takes for the electromagnetic wave signal to penetrate the medium. There is a significant difference between different gangue contents, which can be used as a basis for the gangue content recognition of fully mechanized top coal caving.
The influence of buried pipe extraction position and negative pressure change on the dangerous area ofcoal spontaneous combustion in the goaf
ZHANG Zhongqing
2023, 49(10): 96-103. doi: 10.13272/j.issn.1671-251x.2022080016
<Abstract>(171) <HTML> (44) <PDF>(16)
Abstract:
Gas extraction is one of the commonly used methods for controlling the mine disasters. But during the extraction process, it will increase the amount of air leakage in the goaf, thereby increasing the risk of coal spontaneous combustion and directly affecting the distribution of coal spontaneous combustion dangerous areas in the goaf. Taking the 30503 working face of Tashan Coal Mine of China Coal Datong Energy Co., Ltd. as the research object, according to the actual situation of the goaf, a geometric model is established. The numerical simulation methods is used to analyze the impact of different buried pipe extraction positions and extraction negative pressure on the dangerous area of coal spontaneous combustion in the goaf. The results show the following points. ① With the deepening of the extraction position of the buried pipe on the inlet side, the oxygen volume fraction on the return side shows an increasing trend. The width of the oxidation zone does not change much. The overall oxygen volume fraction on the inlet side shows a decreasing trend, and the width of the oxidation zone first decreases and then increases. The oxidation zone area in the goaf first decreases and then increases. ② In the inlet side of the fixed buried pipe extraction position, the change of the negative pressure of extraction has a greater effect on the oxygen distribution on the inlet side of the extraction zone, while it has almost no effect on the return side. ③ As the negative pressure of extraction increases, the width of the oxidation zone on the inlet side first decreases and then increases, while the width of the oxidation zone on the return side remains almost unchanged. The area of the oxidation zone in the goaf first decreases and then increases. The relationship between the oxidation zone area and the extraction negative pressure is a quadratic function. ④ The optimal position for buried pipe extraction is at a distance of 20 m from the air inlet side of the goaf to the working face. The optimal negative pressure for extraction is 5 000 Pa. At this time, the oxidation zone area of the goaf is the smallest, that is, the coal spontaneous combustion danger area is the smallest.
Research on vertical air leakage law of surface in goaf of shallow coal seams under different seasonal conditions
ZHU Xingpan, WANG Yang, REN Xiaowei, YAN Li, ZHANG Linjiang, LIU Wenyong, JIN Yongfei, CHEN Yuliang
2023, 49(10): 104-109. doi: 10.13272/j.issn.1671-251x.2023010035
<Abstract>(123) <HTML> (33) <PDF>(16)
Abstract:
Under the influence of mining, the overlying strata of shallow coal seam fully mechanized top coal caving face collapses and forms cracks that connect with the surface. The vertical air leakage caused by these cracks has a significant impact on the spontaneous combustion of coal in the goaf. In order to study the vertical air leakage law of surface in goaf of shallow coal seam under different seasonal conditions, SF6 gas tracing method is used to measure the vertical air leakage on the 122108 working face of Shaanxi Coal Caojiatan Mining Co., Ltd. in four seasons: winter, spring, summer, and autumn. The temperature, atmospheric pressure, and air leakage rate changes on the surface and underground goaf during different seasons are analyzed. The results show the following points. ① In winter, the temperature difference between the surface of the working face and the underground goaf is relatively large, with a maximum temperature difference of 37.7 ℃. In summer, the temperature difference between the surface of the working face and the underground goaf is relatively small, with a minimum temperature difference of only 0.9 ℃. The maximum pressure difference between the surface of the working face and the underground goaf in winter is 40.37 hPa. The maximum pressure difference between the surface of the working face and the underground goaf in summer is 22.47 hPa. The temperature difference and pressure difference between the surface and underground goaf of the working face in spring and autumn are not significantly different. ② The winter air leakage rate is relatively high, with an average maximum air leakage rate of 8.364 m/min. The air leakage rate in summer is relatively small, with an average maximum air leakage rate of 6.918 m/min. The air leakage rates in spring and autumn are not significantly different. ③ When close to the working face, the air leakage rate is relatively high. According to the vertical air leakage law on the surface, measures such as underground pressure equalization, sealing of inlet and outlet air corners, and surface crack coverage can be taken to ensure the safe mining of 122108 working face.
Research on the prediction of liquid CO2 phase transition cracking radius in coal seams
WANG Changlu, PENG Ran, ZHENG Yi, LI Wei, YAO Haifei
2023, 49(10): 110-117. doi: 10.13272/j.issn.1671-251x.2023040076
<Abstract>(169) <HTML> (54) <PDF>(10)
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Predicting cracking radius is a prerequisite for determining the holes spacing of gas extraction technology by liquid CO2 phase transition cracking and permeability improvement, which directly affects the gas extraction effect. Most existing prediction methods are based on single factor analysis. In order to grasp the influence of multiple factors on the radius of liquid CO2 phase transition cracking and effectively predict the spacing between holes, ANSYS/LS-DYNA numerical simulation software is used to carry out the research on predicting the radius of coal seam liquid CO2 phase transition cracking combing with orthogonal experiments. The numerical simulation results indicate that the order of factors affecting the radius of liquid CO2 phase transition cracking is ground stress>gas pressure>coal solidity coefficient. The cracking radius decreases with the increase of stress, and increases with the increase of gas pressure and coal solidity coefficient with a linear relationship. A multiple regression analysis is conducted on the numerical simulation results. A prediction model for the radius of liquid CO2 phase transition cracking is established based on three different coupling conditions of ground stress, gas pressure, and coal solidity coefficient. Industrial experiments are conducted on the coal mine site. Extraction boreholes are set up based on the predicted model calculation results. The pressure index method is used to test and analyze the gas extraction effect. The results show the following points. The gas pressure in the observation holes on both sides of the liquid CO2 phase transition cracking hole shows a decreasing trend with time. The farther away from the cracking hole in the initial stage of extraction, the greater the gas pressure. It is consistent with theoretical analysis and numerical simulation results. The effective cracking range of liquid CO2 phase transition is basically consistent with the predicted results. The gas volume fraction in the observation hole is 73.4% higher than that in the natural extraction hole, and the gas extraction efficiency is significantly improved.
Design of high-resolution electrical monitoring system for mining
WANG Bingchun
2023, 49(10): 118-126. doi: 10.13272/j.issn.1671-251x.18101
<Abstract>(192) <HTML> (56) <PDF>(21)
Abstract:
The resistivity method is an important means for identifying, monitoring, and warning potential risks of coal mine water hazards, and also an important data source for transparency of mine geological information. When conducting underground electrical monitoring, the positioning precision of single roadway electrical profiling method or double roadway electrical perspective method for water rich areas is not high. In addition, due to the increasingly strong electromagnetic interference generated by large-scale electrical equipment, traditional electrical monitoring equipment is difficult to obtain effective data. In order to solve the above problems, a high-resolution electrical monitoring system for mining has been designed. The system can automatically collect data from single roadway electrical profile method and double roadway electrical perspective method in real-time during the mining process. The system uses two types of observation data for constrained inversion imaging, improving the imaging resolution of low resistance anomalous bodies. A two-stage amplification and power frequency filtering circuit is designed to configure different sampling timing, sampling frequency, and digital filters during the collection of electrical profile and perspective data. It will suppress the interference of large-scale electrical equipment on electrical response signals. The performance test results show that the high-resolution electrical monitoring system for mining can effectively distinguish 1 µV target signal in noisy environments. The power frequency suppression ratio is not less than 35 dB and 80 dB in the electric perspective mode and electric profile mode, respectively. The results of the physical simulation test in the water tank indicate that the system can effectively distinguish low resistance anomalous bodies with a size of approximately 10 m3 at a depth of 60 meters below the floor when the working face is inclined towards about 300 meters. The test and experimental results have verified that the system has strong power frequency interference and random interference suppression capabilities. The system can obtain reliable and effective data under limited observation space and strong interference conditions in coal mines, improving the imaging resolution of abnormal bodies in inversion results.
Research on the application of inter hole resistivity monitoring in grouting effect detection
WANG Cheng, LI Bofan, WU Zhang, LU Jingjin
2023, 49(10): 127-132, 159. doi: 10.13272/j.issn.1671-251x.2022110089
<Abstract>(175) <HTML> (55) <PDF>(20)
Abstract:
The main technical means for preventing and controlling karst water damage in the coal seam floor of North China type coal fields are grouting transformation of the water-bearing rock layer. Currently, the main method for testing the grouting effect is to analyze the lithological features before and after grouting. There is a lack of tracking and dynamic monitoring of the entire grouting process, making it difficult to accurately evaluate the grouting effect. In order to solve the above problems, an inter hole resistivity monitoring system is introduced to monitor the entire process of resistivity changes in grouting transformed rock layers, in order to achieve precise detection of the slurry diffusion range. Firstly, an improved electrode and cable device is used to place the resistivity monitoring system in a long directional borehole on the coal seam floor, achieving resistivity monitoring between boreholes. Secondly, a geological model of slurry diffusion is constructed, and the simulated data is processed and interpreted using three-dimensional resistivity inversion. Finally, engineering tests are conducted on the inter hole resistivity monitoring of the entire grouting process at the injection layer underground in the coal mine. The simulation results indicate that inter hole resistivity monitoring can identify the diffusion range of slurry anomalies. Based on the trend of resistivity changes over time, the diffusion range of slurry can be inferred. As the slurry gradually diffuses, the range of anomalous areas gradually increases and the intensity of anomalies gradually increases. The engineering test results show that the resistivity monitoring system is arranged on the grouting layer through drilling for dynamic monitoring. After three-dimensional inversion imaging of the monitoring data, the features of resistivity changes in the grouting layer caused by slurry diffusion can be successfully captured. It provides a feasible technical solution for detecting the grouting effect in coal mines.
Research on prediction of support parameters for coal roadways
CHEN Pan, MA Xinmin, XIANG Junjie, CHEN Liying, LIANG Tinghao
2023, 49(10): 133-141. doi: 10.13272/j.issn.1671-251x.2022120047
<Abstract>(171) <HTML> (20) <PDF>(41)
Abstract:
Currently, algorithms such as support vector machine (SVM) and random forest (RF) are less applied in the field of coal mine roadway support. The paper studies the applicability of different machine learning models for support parameter design.Thus a higher performance model would be established to achieve reasonable and scientific design of anchor bolt support. Firstly, it is suggested to establish an intelligent prediction database for coal mine roadway support. Through on-site research, questionnaire survey, and literature search, the coal mine roadway samples are collected. The data is processed using methods such as filling in missing values, modifying outliers in box charts, and removing local abnormal factors to establish a coal roadway support database. The paper proposes a coal roadway support parameter prediction model based on synthetic minority oversampling technique (SMOTE) - genetic algorithm (GA) - SVM. The data in the database is divided into training and testing sets. The SMOTE technology is used to balance training samples, and improve the model's fitting capability for minority class samples. The training process uses GA to globally optimize the hyperparameters of SVM, further improving the overall performance of the model. The test results show that the classificaton precision of the SMOTE-GA-SVM model reaches 83.8%, which is 21.8% higher than the traditional SVM model. The machine learning methods such as SVM, artificial neural network (ANN), RF, AdaBoost (ADA), and naive Bayesian classifier (NBC) are introduced into the prediction of coal roadway anchor support parameters. The corresponding support parameter prediction models are established. The comparison results showed that the best to worst prediction models are ranked as SMOTE-GA-SVM, RF, GA-ANN, SVM, NBC, and ADA, with an average classificaton precision of 69.9%. The result verifies the feasibility of machine learning methods in predicting the parameters of coal roadway bolt support. The SMOTE-GA-SVM model is applied in Shanxi Huobaoganhe Coal Mine Co., Ltd., with a precision of 87.5% and strong applicability and reliability.
Research on the influence of cyclic stress damage on coal bursting liability
YANG Yongliang, REN Jianhui, LI Xuanliang, DU Taotao
2023, 49(10): 142-150. doi: 10.13272/j.issn.1671-251x.2022120064
<Abstract>(72) <HTML> (27) <PDF>(9)
Abstract:
Currently, research on the dynamic behavior features of coal and rock masses only considers the influence of original geological processes such as temperature and confining pressure, without considering the impact of cyclic stress generated during coal mining on the dynamic features of coal. And the determination of the dynamic features of coal is based on the index of coal bursting liability. The impact of cyclic stress damage on coal bursting liability and its dynamic features has not been thoroughly studied. In order to solve the above problems, cyclic stress damage tests are conducted on coal samples. The variation features of coal bursting liability under two cyclic stress damage conditions, namely constant upper and lower limits and variable upper limits, are analyzed. The experimental results show the following points. ① The static compressive strength of coal under the action of constant upper and lower limit cyclic stress and variable upper limit cyclic stress has decreased by 13.86% and 16.00%, respectively. Cyclic stress can degrade the mechanical strength of coal. ② The remaining elastic energy index of the original coal body is 27.34 kJ·m−3. It indicates that the coal body has a weak bursting liability. After constant upper and lower limit cyclic stress damage and variable upper limit cyclic stress damage, the remaining elastic energy index of the coal body has decreased by about 26.30% and 36.14%, respectively. It indicates that cyclic stress has a significant weakening effect on the bursting liability of the coal body. ③ As the remaining elastic energy index of the coal decreases, the dynamic compressive strength and dynamic elastic modulus of the coal decrease, while the dynamic failure deformation continuously increases. It indicates that the bursting liability of the coal will directly affect its dynamic features. The greater the bursting liability of the coal, the higher the degree of degradation of its impact dynamics related parameters. ④ As the remaining elastic energy index of the coal body continues to decrease, the fractal dimension of coal fragmentation after impact decreases. It indicates that cyclic stress leads to insufficient disintegration of the coal body after impact and weakened dynamic response.
Research on the mechanism and prevention of mining induced erosion in the working face affected by fold structures
YANG Zengqiang, LIU Chang, SONG Jie, BAI Yang, JIN Huiwu, WANG Dawei
2023, 49(10): 151-159. doi: 10.13272/j.issn.1671-251x.2022070073
<Abstract>(148) <HTML> (59) <PDF>(4)
Abstract:
The changes in dip angles of different working faces in the area affected by folding structures cause the variability of mining pressure features. In order to solve the above problem, with the seventh mining area of Baojishan Coal Mine as the engineering background, a combination of on-site research, theoretical analysis, numerical simulation, and on-site industrial experiments is used. The dynamic and static loads during mining of different working faces in coal seams with varying dip angles are studied. The results indicate the following points. ① The accumulated acoustic emission(AE) energy of the coal rock composite system with a stiffness value greater than 0 is smaller than that of the coal rock composite system with a stiffness value less than 0. This indicates that when the stiffness value of the coal rock composite system is less than 0, AE energy is more likely to accumulate. When the stiffness value of the coal rock composite system is less than 0, the larger its absolute value, the higher the AE energy can be accumulated. ② As the dip angle of the coal seam increases, the concentrated static load inside the solid coal side of the goaf roadway decreases, and the concentrated static load inside the coal pillar side increases. The hanging top section required for the cracking of the high and thick hard key layer is longer. ③ When the dip angle of the coal seam is small, the combined system of coal and rock in the two sides of the goaf roadway is prone to inducing dynamic failure type II rock burst under the combined action of dynamic and static loads. When the dip angle of the coal seam is large, the coal rock combination system inside the coal pillar side of the goaf roadway is prone to inducing static or dynamic failure type I rock burst under high concentrated static load. ④ During the mining period of the 705 fully mechanized top coal caving face, the coal pillar side of the goaf roadway is prone to inducing static or dynamic failure type I rock burst. After implementing anti erosion measures, the electromagnetic radiation value decreases by up to 67.3%. The coal rock combination system is not easy to induce rock burst.
Development of sealed pressure maintaining sampling device for deep holes in coal mines
GUO Minggong, ZHANG Pengwei, YU Hong
2023, 49(10): 160-164. doi: 10.13272/j.issn.1671-251x.2023010032
<Abstract>(120) <HTML> (50) <PDF>(15)
Abstract:
When using open core tube sampling to measure the gas content in deep hole coal seams, the coal sample has a long exposure time. It is prone to pollution, and the gas loss is difficult to measure, resulting in large measurement errors. However, most of the existing sealed pressure maintaining sampling requires secondary expansion and complex structure. The sampling success rate is low, making it difficult to promote and apply on a large scale. In order to solve the above problems, a sealed pressure maintaining sampling device for deep holes in coal mines has been developed. The device adopts an overall structural design of "two-stage piston+double-layer casing+coal sample cylinder". By controlling the injection flow rate and injection time of the underground high-pressure water pump into the device, the ball valve switches from being sealed before sampling to being opened during sampling, and then to being sealed after sampling. The goal of sealing the coal sample in the coal sample cylinder is achieved, preventing contamination of the coal sample and gas escape during the sampling process. Four sets of coal samples from the same borehole and depth are collected using the conventional sampling method of an open core tube and a deep hole sealed pressure maintaining sampling device for comparative analysis of gas content. The on-site test results show that the sampling depth of the deep hole sealed pressure maintaining sampling device is close to 350 meters. Compared to conventional sampling methods, the gas content measured by deep hole sealed pressure maintaining sampling is 5.4% to 37%. The degree of deviation increases with the increase of sampling drilling depth. It indicates that the sealed pressure maintaining sampling device can improve the accuracy of deep hole coal seam gas content testing.

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