Mining method for three-soft coal seam

Abstract

The present application provides a kind of three soft coal seam mining method, by designing return air roadway is straight wall arch, transport roadway and open cut is rectangle, and based on real-time stress monitoring dynamic adjustment section size;The upper working face is not collapsed transport roadway as part of return air roadway, along the goaf direction stage tilt arrangement inclined return air roadway;Along the end of inclined return air roadway arrangement flat return air roadway, interval dynamic regulation is 1.5 times of transport roadway width;Using support parameter optimization algorithm dynamic adjustment anchor density;In solid coal seam arrangement transport roadway, use telescopic support to realize dynamic width adjustment.The present application is monitored by fiber bragg grating sensor in real time stress and deformation of surrounding rock, combined with digital twin system to verify the reliability of support scheme, significantly reduce the risk of surrounding rock instability, reduce support material waste, improve coal recovery, extend the service life of roadway.The method is suitable for three soft coal seam mining, with the characteristics of strong process dynamic adaptability, high resource utilization.

Description

Technical Field

[0001] This invention relates to a method for mining soft coal seams, belonging to the field of mining technology. Background Technology

[0002] Mining of soft coal seams (where the roof, coal seam, and floor all have low strength) has long faced technical bottlenecks, including large deformation of the surrounding rock in the mining roadways, high support costs, and waste of coal resources. Traditional methods often place mining roadways within solid coal seams, relying on large coal pillars to maintain surrounding rock stability, resulting in insufficient coal extraction and low support efficiency. Although goaf-side roadway retention and goaf-side excavation techniques attempt to reduce reliance on coal pillars, they still struggle to effectively avoid stress concentration zones, leading to non-uniform roadway deformation and easy failure of support structures. For example, the fixed spacing design of transport and return airway in existing processes easily leads to stress superposition, and a single cross-sectional shape cannot adapt to complex geological changes. Furthermore, the fixed angle arrangement of inclined return airway (e.g., a 15° angle) lacks dynamic response capability, further exacerbating the difficulty of surrounding rock control. Therefore, a mining roadway layout method that balances surrounding rock stability, efficient resource utilization, and dynamic process adaptation is urgently needed. Summary of the Invention

[0003] The technical problem to be solved by this invention is to provide a method for mining three soft coal seams to overcome the shortcomings of the existing technology.

[0004] The technical solution of this invention is: to provide a method for mining soft coal seams, comprising the following steps:

[0005] Step 1: Design the return airway cross-section as a straight-walled arch, and the cut-out and transport airway cross-sections as rectangles, and dynamically adjust the cross-sectional dimensions to match real-time stress monitoring data;

[0006] Step 2: The uncollapsed transport roadway of the upper working face is used as part of the return air roadway. The inclined return air roadway is arranged in stages along the closed end of the stop line of the uncollapsed transport roadway of the upper working face towards the goaf area. The included angle is dynamically adjusted to 15° in the front section, 10° in the middle section and 5° in the end section.

[0007] Step 3: Along the inner end of the inclined return airway, arrange a horizontal return airway parallel to the collapse transport airway of the upper working face, with the spacing dynamically adjusted to 1.5 times the width of the transport airway.

[0008] Step 4: Vertically arrange the working face opening at the end of the horizontal return airway, pass through the upper working face collapse tunnel opening and transport roadway to enter the solid coal seam, and use the support parameter optimization algorithm to dynamically adjust the anchor bolt density.

[0009] Step 5: Arrange a transport level in the solid coal seam, use a telescopic support to achieve dynamic width adjustment, and connect it with the prepared roadway. The width of the transport level is equal to the width of the transport level of the upper working face collapse.

[0010] Furthermore, the dynamic adjustment of cross-sectional dimensions to match real-time stress monitoring data includes the following steps:

[0011] 1) Fiber optic grating sensors are pre-embedded on the surface and inside the surrounding rock of the return airway, transport airway and cut-out to collect data on surrounding rock stress, displacement and deformation in real time;

[0012] 2) The collected data is filtered and denoised using edge computing devices to extract the stress concentration factor and deformation rate of key sections of the surrounding rock and generate a dynamic stress field distribution map.

[0013] 3) Based on a preset cross-sectional dimension adjustment rule library, dynamically adjust the roadway cross-sectional dimensions according to the real-time stress field distribution:

[0014] When the stress concentration factor is ≥1.5 or the deformation rate is ≥0.5mm / d, a cross-sectional expansion command is triggered, increasing the width of the straight-walled arch cross-section by 10%-15%.

[0015] When the stress field is stable and the deformation rate is ≤0.1mm / d, the section shrinkage command is triggered to restore the foundation section size;

[0016] 4) Simulate the stability of the surrounding rock of the adjusted section using a digital twin system, verify that the safety factor of the support structure is ≥1.3, and generate construction instructions;

[0017] 5) The optimized cross-sectional dimension parameters are fed back to the tunneling machine control system in real time to dynamically adjust the tunneling and cutting trajectory and realize closed-loop control of cross-sectional dimensions.

[0018] Furthermore, the method of dynamically adjusting the anchor bolt density using the support parameter optimization algorithm includes the following steps:

[0019] S1, during the tunnel excavation process, uses distributed sensors to collect real-time data on surrounding rock stress, displacement and anchor bolt force, and constructs a multi-dimensional support parameter database;

[0020] S2 is a support parameter optimization model built based on deep learning algorithm. The input parameters include the surrounding rock strength index, the roadway cross-sectional shape, and the real-time stress field distribution. The output parameters include the anchor bolt length, diameter, spacing, and preload.

[0021] S3, Based on the model output results from step S2, dynamically adjust the anchor bolt density:

[0022] When the surrounding rock deformation rate is detected to exceed the threshold, the denser anchor bolt arrangement is triggered, increasing the density by 20%-30%.

[0023] When the stress field tends to stabilize, reduce the anchor density to the base value to reduce material consumption;

[0024] S4 uses a digital twin system to simulate roadway stability under different anchor bolt densities, verify the reliability of the optimization scheme, and generate construction instructions.

[0025] Furthermore, the method for dynamically adjusting the spacing to 1.5 times the width of the transport lane in step three is as follows:

[0026] a. Distributed fiber optic grating sensors are pre-embedded in the roof and sidewalls of the horizontal return airway and the upper working face collapse transport roadway to monitor the surrounding rock stress, displacement and plastic zone expansion data in real time.

[0027] b. Calculate the surrounding rock stability index (RSI) based on monitoring data. When the RSI is lower than the threshold of 0.7, trigger the spacing adjustment command to dynamically adjust the spacing between the horizontal intake return airway and the transport airway to 1.5 times the width of the transport airway.

[0028] c. Using segmented tunneling technology, the horizontal return airway is divided into multiple adjustment units. Each unit independently adjusts the distance between itself and the transport roadway according to the real-time RSI. The length of the unit is 2-3 times the width of the transport roadway.

[0029] d. The stress distribution of the surrounding rock under different spacings is simulated using a digital twin system to verify that the safety factor of the adjusted spacing is ≥1.3, and construction instructions are generated.

[0030] e. The optimized spacing parameters are fed back to the tunneling machine control system to dynamically adjust the cutting trajectory and achieve a spacing adjustment accuracy error of ≤±5cm.

[0031] Further, in step b, the surrounding rock stability index RSI is calculated using the following method: ,

[0032] in, Indicates the uniaxial compressive strength of the surrounding rock. Indicates the real-time maximum principal stress. Indicates the allowable displacement threshold. This represents the measured displacement rate.

[0033] The beneficial effects of this invention are: compared with the prior art,

[0034] 1) This invention reduces the risk of surrounding rock deformation by arranging the return airway within the goaf of the upper working face and utilizing the stress release characteristics of the goaf. Combined with the phased inclined design (15°→10°→5°) of the inclined return airway, stress concentration is dispersed. The equal width design of the transport roadway and the upper working face caving transport roadway reduces the need for coal pillars. Combined with expandable supports to adapt to changes in coal seam thickness, pillarless mining is achieved and coal extraction is improved. Dynamically optimized anchor bolt density enhances support effectiveness. The combination design of straight wall arch and rectangular cross-sections matches different stress distribution requirements. A digital twin model simulates surrounding rock deformation in real time, ultimately achieving low-stress uniform distribution, improved dynamic process adaptability, and efficient resource utilization.

[0035] 2) This invention uses fiber optic grating sensors to monitor surrounding rock stress and deformation in real time. Combined with a dynamic cross-section adjustment rule base and digital twin verification, it solves the response lag problem caused by traditional passive support. When the stress concentration factor is ≥1.5 or the deformation rate is ≥0.5mm / d, the cross-section automatically expands by 10%-15% to prevent surrounding rock instability; when stable, it shrinks back to the foundation size, saving support materials. The closed-loop control accuracy error is ≤±5cm, ensuring precise matching between cross-section adjustment and surrounding rock stability, improving support efficiency by 30%.

[0036] 3) This invention solves the problems of material waste and localized insufficient support caused by traditional uniform support by dynamically adjusting the anchor bolt density (increasing the density by 20%-30% or reducing it to the base value) through a support parameter optimization algorithm. By using multi-dimensional data (surrounding rock strength, stress field, cross-sectional shape) to drive the model, the anchor bolt length, spacing, and preload are adapted to real-time working conditions, thus reducing the risk of support failure. Digital twin simulation verification ensures the reliability of the solution, thereby reducing support costs.

[0037] 4) This invention monitors the Resilience Stability Index (RSI) of the surrounding rock using distributed sensors and dynamically adjusts the distance between the horizontal entry / exit airway and the transport airway to 1.5 times their width, solving the stress superposition problem caused by traditional fixed spacing. The segmented tunneling technology (unit length 2-3 times the width of the transport airway) combined with digital twin verification ensures a spacing adjustment accuracy error of ≤±5cm, reducing the expansion of the plastic zone in the surrounding rock. Real-time verification with a safety factor ≥1.3 ensures construction safety and extends the service life of the tunnels. Attached Figure Description

[0038] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings.

[0040] refer to Figure 1 This provides a method for mining soft coal seams, including the following steps:

[0041] Step 1: Design the return airway cross-section as a straight-walled arch, and the cut-out and transport airway cross-sections as rectangles, and dynamically adjust the cross-sectional dimensions to match real-time stress monitoring data;

[0042] Step 2: The uncollapsed transport roadway of the upper working face is used as part of the return air roadway. The inclined return air roadway is arranged in stages along the closed end of the stop line of the uncollapsed transport roadway of the upper working face towards the goaf area. The included angle is dynamically adjusted to 15° in the front section, 10° in the middle section and 5° in the end section.

[0043] Step 3: Along the inner end of the inclined return airway, arrange a horizontal return airway parallel to the collapse transport airway of the upper working face, with the spacing dynamically adjusted to 1.5 times the width of the transport airway.

[0044] Step 4: Vertically arrange the working face opening at the end of the horizontal return airway, pass through the upper working face collapse tunnel opening and transport roadway to enter the solid coal seam, and use the support parameter optimization algorithm to dynamically adjust the anchor bolt density.

[0045] Step 5: Arrange a transport level in the solid coal seam, use a telescopic support to achieve dynamic width adjustment, and connect it with the prepared roadway. The width of the transport level is equal to the width of the transport level of the upper working face collapse.

[0046] Furthermore, the dynamic adjustment of cross-sectional dimensions to match real-time stress monitoring data includes the following steps:

[0047] 1) Fiber optic grating sensors are pre-embedded on the surface and inside the surrounding rock of the return airway, transport airway and cut-out to collect data on surrounding rock stress, displacement and deformation in real time;

[0048] 2) The collected data is filtered and denoised using edge computing devices to extract the stress concentration factor and deformation rate of key sections of the surrounding rock and generate a dynamic stress field distribution map.

[0049] 3) Based on a preset cross-sectional dimension adjustment rule library, dynamically adjust the roadway cross-sectional dimensions according to the real-time stress field distribution:

[0050] When the stress concentration factor is ≥1.5 or the deformation rate is ≥0.5mm / d, a cross-sectional expansion command is triggered, increasing the width of the straight-walled arch cross-section by 10%-15%.

[0051] When the stress field is stable and the deformation rate is ≤0.1mm / d, the section shrinkage command is triggered to restore the foundation section size;

[0052] 4) Simulate the stability of the surrounding rock of the adjusted section using a digital twin system, verify that the safety factor of the support structure is ≥1.3, and generate construction instructions;

[0053] 5) The optimized cross-sectional dimension parameters are fed back to the tunneling machine control system in real time to dynamically adjust the tunneling and cutting trajectory and realize closed-loop control of cross-sectional dimensions.

[0054] Furthermore, the method of dynamically adjusting the anchor bolt density using the support parameter optimization algorithm includes the following steps:

[0055] S1, during the tunnel excavation process, uses distributed sensors to collect real-time data on surrounding rock stress, displacement and anchor bolt force, and constructs a multi-dimensional support parameter database;

[0056] S2 is a support parameter optimization model built based on deep learning algorithm. The input parameters include the surrounding rock strength index, the roadway cross-sectional shape, and the real-time stress field distribution. The output parameters include the anchor bolt length, diameter, spacing, and preload.

[0057] S3, Based on the model output results from step S2, dynamically adjust the anchor bolt density:

[0058] When the surrounding rock deformation rate is detected to exceed the threshold, the denser anchor bolt arrangement is triggered, increasing the density by 20%-30%.

[0059] When the stress field tends to stabilize, reduce the anchor density to the base value to reduce material consumption;

[0060] S4 uses a digital twin system to simulate roadway stability under different anchor bolt densities, verify the reliability of the optimization scheme, and generate construction instructions.

[0061] Furthermore, the method for dynamically adjusting the spacing to 1.5 times the width of the transport lane in step three is as follows:

[0062] a. Distributed fiber optic grating sensors are pre-embedded in the roof and sidewalls of the horizontal return airway and the upper working face collapse transport roadway to monitor the surrounding rock stress, displacement and plastic zone expansion data in real time.

[0063] b. Calculate the surrounding rock stability index (RSI) based on monitoring data. When the RSI is lower than the threshold of 0.7, trigger the spacing adjustment command to dynamically adjust the spacing between the horizontal intake return airway and the transport airway to 1.5 times the width of the transport airway.

[0064] c. Using segmented tunneling technology, the horizontal return airway is divided into multiple adjustment units. Each unit independently adjusts the distance between itself and the transport roadway according to the real-time RSI. The length of the unit is 2-3 times the width of the transport roadway.

[0065] d. The stress distribution of the surrounding rock under different spacings is simulated using a digital twin system to verify that the safety factor of the adjusted spacing is ≥1.3, and construction instructions are generated.

[0066] e. The optimized spacing parameters are fed back to the tunneling machine control system to dynamically adjust the cutting trajectory and achieve a spacing adjustment accuracy error of ≤±5cm.

[0067] Further, in step b, the surrounding rock stability index RSI is calculated using the following method: ,

[0068] in, Indicates the uniaxial compressive strength of the surrounding rock. Indicates the real-time maximum principal stress. Indicates the allowable displacement threshold. This represents the measured displacement rate.

[0069] All aspects not detailed herein are well-known to those skilled in the art. Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of this invention and not intended to limit it. Although the invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this invention without departing from the spirit and scope of the invention, and all such modifications and substitutions should be covered within the scope of the claims of this invention.

Claims

1. A method for mining three soft coal seams, characterized in that, Includes the following steps: Step 1: Design the return airway cross-section as a straight-walled arch, and the cut-out and transport airway cross-sections as rectangles, and dynamically adjust the cross-sectional dimensions to match real-time stress monitoring data; Step 2: The uncollapsed transport roadway of the upper working face is used as part of the return air roadway. The inclined return air roadway is arranged in stages along the closed end of the stop line of the uncollapsed transport roadway of the upper working face towards the goaf area. The included angle is dynamically adjusted to 15° in the front section, 10° in the middle section and 5° in the end section. Step 3: Along the inner end of the inclined return airway, arrange a horizontal return airway parallel to the collapse transport airway of the upper working face, with the spacing dynamically adjusted to 1.5 times the width of the transport airway. Step 4: Vertically arrange the working face opening at the end of the horizontal return airway, pass through the upper working face collapse tunnel opening and transport roadway to enter the solid coal seam, and use the support parameter optimization algorithm to dynamically adjust the anchor bolt density. Step 5: Arrange a transport roadway in the solid coal seam, use a telescopic support to achieve dynamic width adjustment, and connect it with the prepared roadway. The width of the transport roadway is equal to the width of the caving transport roadway of the upper working face. The dynamic adjustment of cross-sectional dimensions to match real-time stress monitoring data includes the following steps: 1) Fiber optic grating sensors are pre-embedded on the surface and inside the surrounding rock of the return airway, transport airway and cut-out to collect data on surrounding rock stress, displacement and deformation in real time; 2) The collected data is filtered and denoised using edge computing devices to extract the stress concentration factor and deformation rate of key sections of the surrounding rock and generate a dynamic stress field distribution map. 3) Based on a preset cross-sectional dimension adjustment rule library, dynamically adjust the roadway cross-sectional dimensions according to the real-time stress field distribution: When the stress concentration factor is ≥1.5 or the deformation rate is ≥0.5mm / d, a cross-sectional expansion command is triggered, increasing the width of the straight-walled arch cross-section by 10%-15%. When the stress field is stable and the deformation rate is ≤0.1mm / d, the section shrinkage command is triggered to restore the foundation section size; 4) Simulate the stability of the surrounding rock of the adjusted section using a digital twin system, verify that the safety factor of the support structure is ≥1.3, and generate construction instructions; 5) The optimized cross-sectional dimension parameters are fed back to the tunneling machine control system in real time to dynamically adjust the tunneling and cutting trajectory and realize closed-loop control of cross-sectional dimensions; The method of dynamically adjusting anchor bolt density using the support parameter optimization algorithm includes the following steps: S1, during the tunnel excavation process, uses distributed sensors to collect real-time data on surrounding rock stress, displacement and anchor bolt force, and constructs a multi-dimensional support parameter database; S2 is a support parameter optimization model built based on deep learning algorithm. The input parameters include the surrounding rock strength index, the roadway cross-sectional shape, and the real-time stress field distribution. The output parameters include the anchor bolt length, diameter, spacing, and preload. S3, Based on the model output results from step S2, dynamically adjust the anchor bolt density: When the surrounding rock deformation rate is detected to exceed the threshold, the denser anchor bolt arrangement is triggered, increasing the density by 20%-30%. When the stress field tends to stabilize, reduce the anchor density to the base value to reduce material consumption; S4 uses a digital twin system to simulate roadway stability under different anchor bolt densities, verify the reliability of the optimization scheme, and generate construction instructions.

2. The method for mining three soft coal seams according to claim 1, characterized in that, The method for dynamically adjusting the spacing to 1.5 times the width of the transport lane in step three is as follows: a. Distributed fiber optic grating sensors are pre-embedded in the roof and sidewalls of the horizontal return airway and the upper working face collapse transport roadway to monitor the surrounding rock stress, displacement and plastic zone expansion data in real time. Step 2: Calculate the surrounding rock stability index (RSI) based on monitoring data. When the RSI is lower than the threshold of 0.7, trigger the spacing adjustment command to dynamically adjust the spacing between the horizontal intake return airway and the transport airway to 1.5 times the width of the transport airway. b. Using segmented tunneling technology, the horizontal return airway is divided into multiple adjustment units. Each unit independently adjusts the distance between itself and the transport roadway according to the real-time RSI. The length of the unit is 2-3 times the width of the transport roadway. c. Simulate the stress distribution of surrounding rock under different spacings using a digital twin system, verify that the safety factor of the adjusted spacing is ≥1.3, and generate construction instructions. d. The optimized spacing parameters are fed back to the tunneling machine control system to dynamically adjust the cutting trajectory and achieve a spacing adjustment accuracy error of ≤±5cm.

3. The method for mining three soft coal seams according to claim 2, characterized in that, In step b, the surrounding rock stability index (RSI) is calculated using the following method: ， in, Indicates the uniaxial compressive strength of the surrounding rock. Indicates the real-time maximum principal stress. Indicates the allowable displacement threshold. This represents the measured displacement rate.

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