Mechanized Mining Face Research Articles

Research on the variation law of floor stress information entropy in upper protective layer mining based on Brillouin optical fiber sensing

The characteristics of floor failure and stress changes during the mining process of protective layers are crucial for determining the effectiveness of pressure relief. Three boreholes were designed in the 21104 fully mechanized mining face of Hulusu Coal Mine to implant optical fibers into the floor of the working face. A fiber optic monitoring system was established to monitor the dynamic evolution of stress in the floor rock mass at different mining distances. Based on the information entropy in information theory, the monitoring results in the fiber optic monitoring system are calculated to obtain the stress information entropy at different mining distances. A quantitative dynamic analysis is conducted on the stress change process of the mining floor rock layer, and the stress change law of the protective layer after mining is verified through numerical calculation and similar simulation experiments. The results indicate that the evolution of stress information entropy can be divided into four stages, namely the original rock stress stage, stress concentration stage, stress release stage, and stress recovery stage. The stress information entropy shows a fluctuating upward trend, indicating that coal seam mining leads to a decrease in the orderliness of the overlying rock system and an increase in disorder. In different spatial evolution processes, there are also significant differences in stress information entropy. In the vertical direction, the entropy value of shallow rock layers changes greatly, while the entropy value of deep rock layers changes slightly. Mining leads to a decrease in the orderliness of the entire overlying rock system, an increase in stress information entropy, and a fluctuating upward trend in stress information entropy. The information entropy of overlying rock deformation and re compaction increases, but the degree of change of the former is greater than that of the latter. The Brillouin fiber optic sensing technology provides a new method for monitoring the stress changes in the protective layer mining floor, achieving quantitative analysis of floor rock failure.

An analytical methodology of rock burst with fully mechanized top-coal caving mining in steeply inclined thick coal seam

Rock burst disaster is still one of the most serious dynamic disasters in coal mining, seriously restricting the safety of coal mining. The b value is the main parameter for monitoring rock burst, and by analyzing its changing characteristics, it can effectively predict the dangerous period of rock burst. This article proposes a method based on deep learning that can predict rock burst using data generated from microseismic monitoring in underground mining. The method first calculates the b value from microseismic monitoring data and constructs a time series dataset, and uses the dynamic time warping algorithm (DTW) to reconstruct the established b value time series. A bidirectional short-term and short-term memory network (BiLSTM) loaded with differential evolution algorithm and attention mechanism was used for training, and a prediction model for the dangerous period of rock burst based on differential algorithm optimization was constructed. The study used microseismic monitoring data from the B1+2 fully mechanized mining face and B3+6 working face in the southern mining area of Wudong Coal Mine for engineering case analysis. The commonly used residual sum of squares, mean square error, root mean square error, and correlation coefficient R2 for time series prediction were introduced, which have significant advantages compared to basic LSTM algorithms. This verifies that the prediction method proposed in this article has good prediction results and certain feasibility, and can provide technical support for the prediction and prevention of rock burst in steeply inclined thick coal seams in strong earthquake areas.

Optimization and Application of Coal Pillar in Fully Mechanized Mining Face based on Energy Analysis

Based on the theory of energy dissipation, a numerical model of goaf excavation was established by FLAC3D based on the backflow channel of Heilong Coal Industry 2202. The dissipative energy distribution characteristics of coal pillars with different widths were studied, and the dissipative energy evolution law of surrounding rock of goaf roadway was analyzed. With the increase of the width of coal pillar, the width of elastic core zone is positively correlated with the bearing capacity. The peak value of dissipated energy density decreases with the increase of the width of coal pillar, and the concentration degree and region of dissipated energy density on the side of coal pillar are greater than that on the side of solid coal pillar. The project is applied to Heilong 2201 working face, and the optimum width of coal pillar and its supporting scheme are given. The practice results show that when the width of coal pillar is 5m, the deformation of surrounding rock can be effectively controlled and the demand for safe and efficient production can be met.

Research on an Intelligent Mining Complete System of a Fully Mechanized Mining Face in Thin Coal Seam.

The mining environment of thin coal seam working faces is generally harsh, the labor intensity is high, and the production efficiency is low. Previous studies have shown that thin coal seam mining finds it difficult to follow machines, does not have complete sets of equipment, has a low degree of automation, and has difficult system co-control, which easily causes production safety accidents. In order to effectively solve the problems existing in thin coal seam mining, Binhu Coal Mine has established intelligent fully mechanized mining and actively explored automatic coal cutting, automatic support following, and intelligent control. The combination of an SAC electro-hydraulic control system and SAP pumping station control system has been applied in 16,108 intelligent fully mechanized coal mining faces, which realizes the automatic following of underground support and the control of adjacent support, partition support, and group operation; the automatic coal cutting of the shearer is realized by editing the automatic coal-cutting state of the shearer and adjusting the automatic parameters. A centralized control center is set up, which realizes the remote control and one-button start-stop of working face equipment. Through a comparative analysis of 16,108 intelligent fully mechanized mining faces and traditional fully mechanized mining faces, it is found that intelligent fully mechanized mining faces have obvious advantages in terms of equipment maintenance, equipment operation mode, and working face efficiency, which improve the equipment and technical mining level of thin coal seam. The application of intelligent mining in Binhu Coal Mine has a great and far-reaching impact on the development of thin coal seam mining technology in China.

Development and application of air-coupled GPR antenna for coal-rock interface detection in mines

Rapid and high precision detection of coal-rock interface is one of the key problems in intelligent coal mining. In this paper, an air-coupled ground penetrating radar (GPR) antenna is developed for coal-rock interface detection in fully mechanized mining face, which can realize non-contacting, high precision, high-resolution detection during the mining process. The main features of the air-coupled GPR antenna are ultra-wideband, narrow beam, and high gain. For the vertical polarization pattern at 1200 MHz, the main lobe amplitude is 6.29dBi and the main lobe width (3 dB) is 108.3°, as well as the relative bandwidth of the antenna can reach 51%. For design validations, the novel air-coupled GPR antenna developed in this paper is tested in mine, the detection error and the average error percentage are ±1.2 cm and 8.6%, respectively, which shows the superior detection ability of the novel air-coupled GPR antenna and the applicability in complex geological environment, providing technical support for the identification of coal-rock interface in intelligent coal mining.

Research on Three-Dimensional Shape Curve Reconstruction Technology for a Scraper Conveyor on an Intelligent Working Face.

"Three straight and two flat" is the inevitable demand when realizing the intelligent mining of a fully mechanized mining face. To address the crucial technical issue of lacking accurate perception of the shape of the scraper conveyor during intelligent coal mining, a three-dimensional curvature sensor involving fiber Bragg grating (FBG) is used as a perceptive tool to conduct curve reconstruction research based on different local motion frames and to reconstruct the shape of the scraper conveyor. Firstly, the formation process of the 'S'-shaped bending section of the scraper conveyor during the pushing process is determined. Based on the FBG sensing principle, a mathematical model between the variation in the central wavelength and the strain and curvature is established, and the cubic B-spline interpolation method is employed to continuously process the obtained discrete curvature. Secondly, based on differential geometry, a spatial curve reconstruction algorithm based on the Frenet moving frame is derived, and the shape curve prediction interpolation model is built based on a gated recurrent unit (GRU) model, which reduces the impact of the decrease in curve reconstruction accuracy caused by damage to some grating measuring points. Finally, an experimental platform was designed and built, and sensors with curvature radii of 6 m, 7 m, and 8 m were tested. The experimental results showed that the reconstructed curve was essentially consistent with the actual shape, and the absolute error at the end was about 2 mm. The feasibility of this reconstruction algorithm in engineering has been proven, and this is of great significance in achieving shape curve perception and straightness control for scraper conveyors.

An AGCRN Algorithm for Pressure Prediction in an Ultra-Long Mining Face in a Medium–Thick Coal Seam in the Northern Shaanxi Area, China

Due to the increase in the length of the mining face, the pressure characteristics and spatial distribution in fully-mechanized mining faces are different from those in typical mining faces, which leads to great challenges in roof management and the intelligent control of ultra-long mining faces. Taking the ultra-long mining face of a medium–thick coal seam in the northern Shaanxi mining area as an example and using field monitoring data for the working resistance of the hydraulic supports, a non-linear prediction method was used to extract the features of the dynamic data sequence of the working resistance of the hydraulic supports, and a deep learning method was used to establish a pressure prediction model for ultra-long mining faces based on the adaptive graph convolutional recurrent network (AGCRN) algorithm. In the proposed model, the supports in the fully mechanized mining face were regarded as the logic nodes of a topological structure, while the time-series resistance data for the supports were regarded as data nodes on a graph. The AGCRN model was used to determine the spatiotemporal relationship between the working resistance data of adjacent hydraulic supports, thereby improving the accuracy of the proposed model. The MAE and MAPE were employed as performance evaluation indices. When the node-embedding dimension was set to 10 and the time window was set to 16, the corresponding MAE and MAPE values of the prediction model were the minimum values. Compared with the reference models (i.e., the BP, GRU, and DCRNN models), the MAE and MAPE of the AGCRN model were 38.75% and 23.49% lower, respectively, indicating that the AGCRN model effectively demonstrates high accuracy in predicting the working resistance of supports. The AGCRN model was applied in the prediction of the working resistance of the supports of the ultra-long fully mechanized mining face. The results revealed that the working resistance of the supports in the lower and upper areas was relatively small along the strike, whereas the working resistance of the supports in the middle area was large, exhibiting a zoning pattern of “low-high-low” in terms of the average working resistance. In conclusion, the proposed model provides data references for the state of the hydraulic supports, pressure identification, and intelligent control of the ultra-long mining faces of the medium–thick coal seams in northern Shaanxi.

Research on Dust Migration and Dust Deposition Rules of Breathing Zone in Fully Mechanized Mining Face.

The dust in the breathing zone of the fully mechanized mining face poses a serious threat to the lives and health of the workers, and clarifying the distribution and settlement pattern of the dust in the breathing zone is an important foundation for reducing dust concentrations in the breathing zone and improving the workers' working environment. The dust concentration distribution at the mining face and the settlement results of different dust particle sizes along the breathing zone were analyzed in detail using a combination of computational fluid dynamics simulation and downhole measurements by establishing a highly simulated 3D solid model of the 2302 fully mechanized mining face at the Xinqiao coal mine. The study's findings reveal that dust from advanced support and coal-cutting processes converge within 20-60 m of the coal mining region, generating a high-concentration pollution zone at the height of the sidewalk breathing zone. The particle size of dust in the breathing zone is primarily concentrated between 1 and 40 μm, and the fully mechanized mining face is split into a rapid settling area, a medium settling area, and a slow settling area based on particle size settling speed. Eddy currents in the return airway lead to an increase in dust particles of 20-40 μm in the breathing zone area. The results of the study can provide a theoretical basis for dust management at the fully mechanized mining face for the breathing zone area.

Study on roof breaking mechanism and support stability of steeply dipping seam and large mining height

Taking the steeply dipping and large mining height working face of a mine as the engineering background, through the combination of physical simulation experiment, numerical calculation, theoretical analysis and field monitoring, based on a comprehensive analysis of the deformation and failure characteristics of the macrostructure of surrounding rock, the roof breaking mechanism and support instability characteristics of large mining height working face under the angle effect are studied. The research shows that due to the influence of the dip angle of the coal seam, the roof stress is asymmetrically deflected along the tendency, and the load of the overlying strata is transmitted to the upper and lower coal bodies with the stress-deflection boundary as the boundary, resulting in the deformation and failure of the roof and the filling showing obvious asymmetric characteristics. With the increase of dip angle, the asymmetric characteristics of roof stress transfer are enhanced, the stress release arch is reduced, the height of caving zone is reduced, the deformation and failure area is gradually moved up, and the regional characteristics of roof loading and deformation and failure are more obvious, which leads to the significant increase of unbalanced loading degree and instability probability of supports in different areas. Combined with the actual production, the prevention and control measures of hard roof caving and support crushing in fully mechanized mining face with steeply dipping seam and large mining height are put forward.

Research on gas hazard prevention and control of a high-gas fully mechanized mining face based on ventilation system optimization.

The gas accumulation in the return corner of a high-gas fully mechanized mining face can easily cause the gas volume fraction to exceed the safety limit, threatening the safety of coal mines. In this study, the unit method was used to analyze the gas sources and emissions based on the actual case. The airflow and gas distribution characteristics of the two-inlet-one-outlet (TIOO) ventilation system and the one-inlet-two-outlet (OITO) ventilation system were studied using CFD numerical simulation. The results show that under the TIOO ventilation system, the "U"-type air leakage in the goaf leads deep gas into the return corner, which causes the gas volume fraction in the return corner to rise to 0.4-2.0%. After the mining face is optimized into the OITO ventilation system, the "J"-type air leakage of the goaf suppresses the high concentration of gas in the deep position of the goaf. Combined with the gas extraction measures, the gas volume fraction in the return corner, exhaust roadway's outlet, and retaining roadway's outlet is controlled at 0.28%, 0.34%, and 0.23%. This study will provide new ideas for solving the problem of gas accumulation in the return corner of a high-gas fully mechanized mining face.

Positioning Control Strategy of Hydraulic Support Pushing System in Fully Mechanized Coal Face

At present, the hydraulic support pushing system in coal mines usually uses an electrohydraulic directional valve as the control component. However, the existing control methods based on high-speed on–off valve, servo, and proportional control methods are not suitable for solving such problems because of the nonideal characteristics of the electrohydraulic directional valve, such as discrete input values, low switching frequency, and time delay. This paper proposes a positioning control scheme based on online predictive feedback for the control of hydraulic cylinders by electrohydraulic directional valves. In this scheme, the recursive least-squares estimation algorithm with genetic factors is used to identify the required prediction model in real time, and an improved radial basis function network based on generalized growth and shear is used to realize the online fitting of the target trajectory function. The online learning algorithm provides accurate prediction information for the switching control method, and finally, the hydraulic cylinder can be positioned near the target position using the optimal control method. By using the above methods, a well-designed model can be accurately identified, fundamentally solving the problem of control difficulties caused by the nonideal characteristics of the electrohydraulic directional valve. Finally, the effectiveness of the control scheme is verified through simulation analysis and physical experiment research, which proves that the control strategy can realize accurate and fast positioning control for the hydraulic support pushing system of a fully mechanized mining face.

Influence of aerodynamic pressure on dust removal by supersonic siphon atomization

At present, there are many problems in coal mine operation, such as formation of large amounts of dust, complex dust migration behavior, severe respiratory harm, poor on-site performance of spray dust removal technology under windy conditions, and low collection efficiency of respirable dust. To solve the above problems, the finite element method of computational fluid dynamics (CFD) was used. The Spalart-Allmaras turbulence model of COMSOL software and the tracking module for atomized particles broken by droplets were used. They were combined with the Fraunhofer diffraction principle to study the distributions of the velocity of the airflow field, droplet size, droplet velocity and wind resistance for a supersonic water siphonic atomization device. The influence of the above factors on dust removal at different aerodynamic pressures was studied experimentally. The relationships between spray characteristics, flow field velocity distribution, dust removal effect and spray characteristics were revealed. The research showed that with increasing pressure, the supersonic component accounted for an increased proportion of the flow field inside the nozzle, average velocity of the flow field increased, atomization efficiency increased, droplet particle size decreased, and droplet velocity increased. The particle size of the droplets first increased, then decreased and then increased with increasing spraying distance. Additionally, the range of high-speed fine droplet size fog increased with increasing pressure. At the same transverse wind speed, with increasing pressure, the deflection point of the fog field moved backward, and the wind resistance of the spray was enhanced. With the increase in aerodynamic pressure, the dust isolation and negative pressure effect of spray and the dust collection efficiency increased, and there was an optimal value for dust removal in a limited space. The reason was that when the pressure increased to a certain extent, the air flow reversed in the coil at the bottom of the limited space, which blew the dust that was not aggregated at the bottom away from the area where dust was falling. Thus, the dust was entrained in fog droplets but could not be removed from the air flow. The dust dispersion in the air flow after purification differed greatly at different pressures because the removal efficiency of dust in the 2.5–10 μm particle size range was mainly affected by the pressure. In a field study of a fully mechanized mining face, the fog curtain formed by the device covered the whole section under the condition of airflow disturbance with large transverse velocity, and the comprehensive respirable dust removal efficiency of the working area reached 92.3%. Thus, this method showed good wind resistance and dust removal performance. The study of this technology can provide a clean working environment and theoretical guidance for the safe production of coal in the future, especially for fully mechanized mining faces.

Failure mechanism and stability control of surrounding rock in mining roadway with gentle slope and close distance

In this study, theoretical analysis, numerical simulation and field measurement were adopted to analyze the difficult problem of controlling the stability of surrounding rock in gently inclined and close-distance coal seam mining roadways. The results showed that: (1) According to the properties and stress environment of the roadway roof, to determine the specific spatial range of the original roof stage, transition stage and regeneration roof stage of the roadway, and corresponding to the distribution of plastic zones in the spatial stages, was an important basis for analyzing the deformation mechanism of the roadway and proposing a phased collaborative control plan. (2) Under the influence of mining, the plastic zone of the transportation roadway expanded violently by about 10 m ahead of the working face. Within the range of roadway passing the overlying goaf, the plastic zone of the surrounding rock between the layers runed through, especially extending to the roof and two shoulder corners of the roadway. The roof and two shoulder corners of the roadway became the key parts for the stability control of the surrounding rock. (3) The mechanical mechanism of asymmetric expansion of the plastic zone was obtained as follows: the range was determined by the magnitude of the deviatoric stress and the orientation was dominated by the direction of the principal stress. The combined effect of the magnitude of deviatoric stress and the angle of principal stress caused asymmetric expansion of the plastic zone. (4) A phased collaborative control scheme was proposed, and numerical simulation and industrial verification were carried out on the proposed scheme. The deformation of the surrounding rock of the roadway at the engineering site was less than 150 mm, and the control effect of the surrounding rock was good, ensuring the safe and efficient recovery of the fully mechanized mining face. The present study revealed the mechanical mechanism of failure and instability of the surrounding rock of the gently inclined close distance coal seam mining roadway and proposed a phased collaborative control scheme, which could provide valuable information for mining research.

Measurement of displacement and top beam attitude angle of advanced hydraulic support based on visual detection

We constructed an advanced hydraulic support test bench and proposed a visual detection-based approach for measuring the displacement and attitude angle of the advanced hydraulic support. Firstly, our methodology involved using a binocular camera for image acquisition and stereo rectification of the advanced hydraulic support. Then, we employed the ORB algorithm to detect feature points and the SGBM matching algorithm to determine the disparity value. Finally, the attitude angle solution algorithm and the triangulation method are written to calculate the support displacement and the top beam attitude angle. Results showed that the advanced hydraulic support had an average absolute error of 8 mm in displacement measurement and 0.4° in attitude angle measurement, meeting the accuracy requirements for fully mechanized mining face operations.

Research and Application of Support in Triangle Area of Underground Withdrawal Working Face in Coal Mine

Aiming at the rapid withdrawal of temporary support technology at the fully mechanized mining face in the Shendong mining area, a temporary support bracket group in the triangle area is designed according to the current geological mining conditions, and the working principle of the temporary support bracket in the triangle area is explained and analyzed. The key technical parameters of the triangular support are analyzed, and the stress of its key structure is analyzed. Field practice shows that the developed triangular area temporary support bracket group has a reasonable structural design, improves the withdrawal efficiency based on effective roof support, and meets the requirements for the use of temporary support for rapid withdrawal of fully mechanized mining faces.

An open dataset for intelligent recognition and classification of abnormal condition in longwall mining

The underground coal mine production of the fully mechanized mining face exists many problems, such as poor operating environment, high accident rate and so on. Recently, the intelligent autonomous coal mining is gradually replacing the traditional mining process. The artificial intelligence technology is an active research area and is expect to identify and warn the underground abnormal conditions for intelligent longwall mining. It is inseparable from the construction of datasets, but the downhole dataset is still blank at present. This work develops an image dataset of underground longwall mining face (DsLMF+), which consists of 138004 images with annotation 6 categories of mine personnel, hydraulic support guard plate, large coal, towline, miners’ behaviour and mine safety helmet. All the labels of dataset are publicly available in YOLO format and COCO format. The availability and accuracy of the datasets were reviewed by experts in coal mine field. The dataset is open access and aims to support further research and advancement of the intelligent identification and classification of abnormal conditions for underground mining.

Robust Output Feedback Position Control of Hydraulic Support with Neural Network Compensator

Hydraulic support is important equipment in the fully mechanized mining face, and the control performance of the hydraulic support multi-cylinder system directly affects the smooth progress of coal mining process, which is the basis for the continuous advancement of the coal face. However, the friction force of the hydraulic support in the process of pulling the frame is complex due to the underground environmental load. Moreover, the parameters of the moving cylinder are uncertain, and the state of the system cannot be fully measured, which increases the difficulty of control. A proportional-integral-derivative controller is usually used in electro-hydraulic closed-loop control systems because of its computational complexity, but its robustness is poorly adapted to variable load conditions in the coal mine. Therefore, a robust output feedback position controller is proposed in this paper to improve control accuracy and system robustness with only position signal. The multi-cylinder system of hydraulic support is modeled as a standard type, and then a high-order differentiator is proposed to estimate the immeasurable system states using the output position signal. A neural network compensator is applied to estimate and compensate for the external disturbance of the moving cylinder. Furthermore, the parameters of the ZY3200/08/18D hydraulic support are adopted to analyze the effectiveness of the designed controller in simulations. Finally, a real-time control system of hydraulic support is built, and the experimental results show that the novel robust output feedback controller has improved by 47.2% and 30.6% in tracking accuracy compared to PI controller.

Intelligent Identification Method of Shearer Drums Based on Improved YOLOv5s with Dark Channel-Guided Filtering Defogging

In a fully mechanized mining face, there is interference between the hydraulic support face guard and the shearer drum. The two collisions seriously affect coal mine production and personnel safety. The identification of a shearer drum can be affected by fog generated when the shearer drum cuts forward. It is hydraulic support face guard recovery, not the timely block shearer drum, that will also affect the recognition of the shearer drum. Aiming at the above problems, a shearer drum identification method based on improved YOLOv5s with dark channel-guided filtering defogging is proposed. Aiming at the problem of fog interference affecting recognition, the defogging method for dark channel guided filtering is proposed. The optimal value of the scene transmittance function is calculated using guided filtering to achieve a reasonable defogging effect. The Coordinate Attention (CA) mechanism is adopted to improve the backbone network of the YOLOv5s algorithm. The shearer drum features extracted by the C3 module are reallocated by the attention mechanism to the weights of each space and channel. The information propagation of a shearer drum’s features is enhanced by such improvements. Thus, the detection of shearer drum targets in complex backgrounds is improved. S Intersection over Union (SIoU) is used as a loss function to improve the speed and accuracy of the shearer drum. To verify the effectiveness of the improved algorithm, multiple and improved target detection algorithms are compared. The algorithm is deployed at Huangling II mine. The experimental results present that the improved algorithm is superior to most target detection algorithms. In the absence of object obstruction, the improved algorithm achieved 89.3% recognition accuracy and a detection speed of 48.8 frame/s for the shearer drum in the Huangling II mine. The improved YOLOv5s algorithm provides a basis for identifying interference states between the hydraulic support face guard and shearer drum.

Analysis of CO Source and Prediction Model of Gushing Concentration at the Return Air Corner of Working Face in Shallow Coal Seam Mine

ABSTRACT The production practices in Shendong mining area show that the CO concentration at the return air corner of shallow coal seams often exceeds the limit, but the temperature of the residual coal in the goaf has not significantly increased, and no other indicative gas of spontaneous combustion in coal seams has been detected. In order to provide scientific basis for CO management at the return air corner of the fully mechanized mining face in Shendong mining area and the prevention and control of coal seam spontaneous combustion fires, based on the “three zones” distribution parameters of spontaneous combustion of coal in goaf and the characteristic parameters of spontaneous combustion of coal, and based on the mechanism of CO production in shallow buried mining area, the source and influencing factors of CO in working face were analyzed, and the calculation model of CO concentration at the return air corner in working face was established. The concentrations of CO at the return air corner in different working faces in Shendong mining areas were calculated by using the model. The results showed that the relative error between the observed and measured values remained between 0.32% and 6.92%. The quantitative analysis of the proportion of CO production from each source to the total production of CO in the return air corner is of great significance to the effective control of CO concentration in the air return corner of the working face.

Study on Height Development Characteristics of Water-Conducting Fracture Zone in Fully Mechanized Mining of Shallow Thick Coal Seam under Water

The height of water-conducting fracture zone (HWCFZ) is one of the important technical parameters for water-preserved coal mining. The purpose of this paper is to acquire information about the height development characteristics of water-conducting fracture zone (WCFZ) in fully mechanized mining of shallow thick coal seam under water body in western mining area of China. The 91,105 fully mechanized mining face of Daheng coal mine under composite water body was taken as the research object, the development height, morphological characteristics, development and evolution process of WCFZ in working face mining were studied through underground up-hole water injection method by intervals, borehole TV and numerical simulation. The results show that the HWCFZ in 91,105 fully mechanized mining face is 52.7~53.6 m, and the fracture mining ratio is 12.55~12.76. The final development form is saddle-shaped with “large at both ends and small in the middle”. It is accurate and reliable to determine the development characteristics of overburden fractures and the HWCFZ by the field measurement of the combination of underground upward hole segmented water injection method and borehole TV. The development height of the water-conducting fracture zone obtained by numerical simulation is consistent with the field measured results. The development and evolution of the height of WCFZ presents four stages: “development–slow increase–sudden increase–stability”. When the WCFZ develops to a certain layer, the cracks generated by the weak strata in the fracture zone of overlying strata on the working face will automatically close with the advancement of the working face, resulting in “bridging phenomenon”, which inhibits the further development of the WCFZ. That is, the existence of soft rock with a certain thickness in overburden will become the key inhibiting layer for the development of WCFZ, effectively blocking the communication between water-conducting fracture and overlying aquifer. The research results are intended to provide guidance for the implementation of water preserving mining and ecological environment protection in ecologically fragile areas in western China.