Three-soft coal seam stoping method

Abstract

The invention provides a three-soft coal seam stoping method which comprises the following steps: designing an air return gate to be in a straight wall arch shape, designing a haulage gate and an open-off cut to be rectangular, and dynamically adjusting the section size based on real-time stress monitoring; an upper working face non-caving haulage roadway serves as a part of an air return roadway, and an oblique air inlet and return roadway is obliquely arranged in a staged mode in the goaf direction; a flat air inlet and return gate way is arranged along the inner end of the inclined air inlet and return gate way, and the distance is dynamically adjusted to be 1.5 times of the width of the haulage gate way; dynamically adjusting the anchor rod density by adopting a support parameter optimization algorithm; a haulage roadway is arranged in a solid coal seam, and dynamic width adjustment is achieved through a telescopic support. The surrounding rock stress and deformation are monitored in real time through the fiber bragg grating sensor, the reliability of the supporting scheme is verified in combination with a digital twin system, the surrounding rock instability risk is remarkably reduced, supporting material waste is reduced, the coal recovery rate is increased, and the service life of a roadway is prolonged. The method is suitable for three-soft coal seam mining, and has the characteristics of high process dynamic adaptability and high resource utilization rate.

Description

Technical Field

[0001] The invention relates to a three-soft coal seam mining method and belongs to the technical field of mining. Background Art

[0002] The mining of three soft coal seams (the strength of the roof, coal seam and floor are all low) has long faced technical bottlenecks such as large deformation of the surrounding rock of the mining tunnel, high support costs and waste of coal resources. In traditional methods, mining tunnels are mostly arranged in solid coal seams, relying on large-sized coal pillars to maintain the stability of the surrounding rock, resulting in insufficient coal recovery rate and low support efficiency. Although the goaf-side tunnel retention and goaf-side tunneling technologies attempt to reduce the reliance on coal pillars, it is still difficult to effectively avoid stress concentration areas, causing non-uniform deformation of the tunnel and easy failure of the support structure. For example, the fixed spacing design of the transport tunnel and the return air tunnel in the existing process is prone to stress superposition, and the single cross-sectional shape cannot adapt to complex geological changes. In addition, the fixed angle arrangement of the oblique return air tunnel (such as a 15° angle) lacks dynamic response capabilities, further exacerbating the difficulty of surrounding rock control. Therefore, there is an urgent need for a mining tunnel layout method that takes into account the stability of the surrounding rock, efficient resource utilization and dynamic process adaptation. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a method for recovering three-soft coal seams to overcome the shortcomings of the prior art.

[0004] The technical solution of the present invention is to provide a method for recovering three-soft coal seams, comprising the following steps:

[0005] Step 1: Design the cross section of the return air lane to be a straight wall arch, the cross section of the opening eye and the transport lane to be a rectangle, and dynamically adjust the cross section size to match the real-time stress monitoring data;

[0006] Step 2: The uncollapsed transport lane on the upper working face is taken as part of the return air lane, and the return air lane is arranged in stages along the closed end of the stop mining line toward the goaf, with the angle dynamically adjusted to 15° in the front section, 10° in the middle section, and 5° in the end section;

[0007] Step 3: Arrange a horizontal return air lane parallel to the upper working face collapsed transport lane along the inner end of the oblique return air lane, and dynamically adjust the spacing to 1.5 times the width of the transport lane;

[0008] Step 4: vertically arrange the working face opening eye at the end of the horizontal return air tunnel, cross the upper working face cave-in opening eye and the transport tunnel to enter the solid coal seam, and use the support parameter optimization algorithm to dynamically adjust the anchor density;

[0009] Step five, arrange the transport tunnel in the solid coal seam, use retractable brackets to achieve dynamic width adjustment, and connect it with the preparation tunnel. The width of the transport tunnel is equal to the width of the collapsed transport tunnel on the upper working face.

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

[0011] 1) Pre-embed fiber grating sensors on the surface and inside of the surrounding rock of the return air tunnel, transport tunnel and cut hole to collect surrounding rock stress, displacement and deformation data in real time;

[0012] 2) Use edge computing equipment to filter and reduce noise on the collected data, extract the stress concentration factor and deformation rate of the key cross-section of the surrounding rock, and generate a dynamic stress field distribution map;

[0013] 3) Based on the preset cross-section size adjustment rule library, dynamically adjust the tunnel cross-section size 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, the section expansion instruction is triggered to expand the width of the straight wall arch section by 10%-15%;

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

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

[0017] 5) Feedback the optimized cross-sectional dimension parameters to the tunnel boring machine control system in real time, dynamically adjust the tunneling and cutting trajectory, and realize closed-loop control of the cross-sectional dimension.

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

[0019] S1, during the tunnel excavation process, the surrounding rock stress, displacement and anchor force data are collected in real time through distributed sensors to build a multi-dimensional support parameter database;

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

[0021] S3, dynamically adjust the anchor density according to the output results of the model in step S2:

[0022] When the deformation rate of the surrounding rock exceeds the threshold, the anchor bolt arrangement is triggered, and the density is increased by 20%-30%;

[0023] When the stress field tends to be stable, reduce the density of anchor bolts to the basic value to reduce material consumption;

[0024] S4, simulates the tunnel stability under different bolt densities through the digital twin system, verifies the reliability of the optimization scheme, and generates construction instructions.

[0025] Furthermore, the method for dynamically adjusting the spacing in step 3 to 1.5 times the width of the transport lane is:

[0026] Step 1: pre-embed distributed fiber grating sensors in the roof and side walls of the horizontal return air tunnel and the upper working face collapsed transport tunnel to monitor the surrounding rock stress, displacement and plastic zone expansion data in real time;

[0027] Step 2: Calculate the surrounding rock stability index RSI based on the 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 inlet and return air lane and the transport lane to 1.5 times the width of the transport lane.

[0028] Step 3: Use segmented excavation technology to divide the horizontal return air tunnel into multiple adjustment units. Each unit independently adjusts the distance with the transport tunnel according to the real-time RSI. The unit length is 2-3 times the width of the transport tunnel.

[0029] Step 4: Use the digital twin system to simulate the surrounding rock stress distribution at different spacings, verify that the safety factor of the adjusted spacing is ≥ 1.3, and generate construction instructions;

[0030] Step 5: Feedback the optimized spacing parameters to the tunnel boring machine control system, dynamically adjust the cutting trajectory, and achieve a spacing adjustment accuracy error of ≤±5cm.

[0031] Furthermore, in the step 2, the surrounding rock stability index RSI is calculated by the following method:

[0032]

[0033] Among them, σ c represents the uniaxial compressive strength of surrounding rock, σ max represents the real-time maximum principal stress, d allow represents the allowable displacement threshold, d means Represents the measured displacement rate.

[0034] The beneficial effects of the present invention are: compared with the prior art,

[0035] 1) The present invention arranges the return air lane in the goaf of the upper working face, utilizes the stress release characteristics of the goaf to reduce the risk of surrounding rock deformation, and disperses stress concentration with the phased inclination design (15°→10°→5°) of the oblique return air lane; the transport lane and the upper working face collapse transport lane are designed to be equal in width to reduce the number of coal pillars, and the retractable bracket is combined to adapt to the change in coal seam thickness, so as to achieve pillar-free mining and improve coal extraction; the anchor density is dynamically optimized to enhance the effectiveness of support; the combination design of straight wall arch and rectangular section matches different stress distribution requirements, and the digital twin model simulates the surrounding rock deformation in real time, ultimately achieving low stress uniform distribution, improved process dynamic adaptability and efficient resource utilization;

[0036] 2) The present invention uses fiber grating sensors to monitor the stress and deformation of the surrounding rock in real time, and combines the dynamic section adjustment rule library with digital twin verification to solve 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 section automatically expands by 10%-15% to prevent the surrounding rock from becoming unstable; when stable, it shrinks to the basic size to save support materials. The closed-loop control accuracy error is ≤±5cm, ensuring that the section adjustment is accurately matched with the stability of the surrounding rock, and the support efficiency is improved by 30%;

[0037] 3) The present invention uses a support parameter optimization algorithm to dynamically adjust the anchor density (increase by 20%-30% or reduce to the basic value), thus solving the problems of material waste and insufficient local support caused by traditional uniform support. The model is driven by multi-dimensional data (surrounding rock strength, stress field, cross-sectional shape), and the anchor length, spacing, and preload force are adapted to the real-time working conditions, reducing the risk of support failure. Digital twin simulation verification ensures the reliability of the solution and reduces support costs;

[0038] 4) The present invention monitors the surrounding rock stability index (RSI) through distributed sensors, dynamically adjusts the spacing between the horizontal return air tunnel and the transport tunnel to 1.5 times the width, and solves the stress superposition problem caused by the traditional fixed spacing. The segmented excavation technology (unit length 2-3 times the width of the transport tunnel) is combined with digital twin verification, and the spacing adjustment accuracy error is ≤±5cm, which reduces the expansion of the surrounding rock plastic zone. Real-time verification of the safety factor ≥1.3 ensures construction safety and extends the service life of the tunnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0040] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings of this specification.

[0041] refer to Figure 1 , a three-soft coal seam mining method is provided, comprising the following steps:

[0042] Step 1: Design the cross section of the return air lane to be a straight wall arch, the cross section of the opening eye and the transport lane to be a rectangle, and dynamically adjust the cross section size to match the real-time stress monitoring data;

[0043] Step 2: The uncollapsed transport lane on the upper working face is taken as part of the return air lane, and the return air lane is arranged in stages along the closed end of the stop mining line toward the goaf, with the angle dynamically adjusted to 15° in the front section, 10° in the middle section, and 5° in the end section;

[0044] Step 3: Arrange a horizontal return air lane parallel to the upper working face collapsed transport lane along the inner end of the oblique return air lane, and dynamically adjust the spacing to 1.5 times the width of the transport lane;

[0045] Step 4: vertically arrange the working face opening eye at the end of the horizontal return air tunnel, cross the upper working face cave-in opening eye and the transport tunnel to enter the solid coal seam, and use the support parameter optimization algorithm to dynamically adjust the anchor density;

[0046] Step five, arrange the transport tunnel in the solid coal seam, use retractable brackets to achieve dynamic width adjustment, and connect it with the preparation tunnel. The width of the transport tunnel is equal to the width of the collapsed transport tunnel on the upper working face.

[0047] Furthermore, the dynamic adjustment of the cross-sectional dimensions to match the real-time stress monitoring data comprises the following steps:

[0048] 1) Pre-embed fiber grating sensors on the surface and inside of the surrounding rock of the return air tunnel, transport tunnel and cut hole to collect surrounding rock stress, displacement and deformation data in real time;

[0049] 2) Use edge computing equipment to filter and reduce noise on the collected data, extract the stress concentration factor and deformation rate of the key cross-section of the surrounding rock, and generate a dynamic stress field distribution map;

[0050] 3) Based on the preset cross-section size adjustment rule library, dynamically adjust the tunnel cross-section size according to the real-time stress field distribution:

[0051] When the stress concentration factor is ≥1.5 or the deformation rate is ≥0.5mm / d, the section expansion instruction is triggered to expand the width of the straight wall arch section by 10%-15%;

[0052] When the stress field is stable and the deformation rate is ≤0.1mm / d, the section contraction instruction is triggered to restore the basic section size;

[0053] 4) Use the digital twin system to simulate the stability of the surrounding rock of the adjusted section, verify that the safety factor of the support structure is ≥1.3, and generate construction instructions;

[0054] 5) Feedback the optimized cross-sectional dimension parameters to the tunnel boring machine control system in real time, dynamically adjust the tunneling and cutting trajectory, and realize closed-loop control of the cross-sectional dimension.

[0055] Furthermore, the method of dynamically adjusting the anchor density using the support parameter optimization algorithm includes the following steps:

[0056] S1, during the tunnel excavation process, the surrounding rock stress, displacement and anchor force data are collected in real time through distributed sensors to build a multi-dimensional support parameter database;

[0057] S2, builds a support parameter optimization model based on deep learning algorithm. The input parameters include surrounding rock strength index, tunnel cross-section shape, and real-time stress field distribution. The output parameters include anchor length, diameter, spacing, and preload.

[0058] S3, dynamically adjust the anchor density according to the output results of the model in step S2:

[0059] When the deformation rate of the surrounding rock exceeds the threshold, the anchor bolt arrangement is triggered, and the density is increased by 20%-30%;

[0060] When the stress field tends to be stable, reduce the density of anchor bolts to the basic value to reduce material consumption;

[0061] S4, simulates the tunnel stability under different bolt densities through the digital twin system, verifies the reliability of the optimization scheme, and generates construction instructions.

[0062] Furthermore, the method for dynamically adjusting the spacing in step 3 to 1.5 times the width of the transport lane is:

[0063] Step 1: pre-embed distributed fiber grating sensors in the roof and side walls of the horizontal return air tunnel and the upper working face collapsed transport tunnel to monitor the surrounding rock stress, displacement and plastic zone expansion data in real time;

[0064] Step 2: Calculate the surrounding rock stability index RSI based on the 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 inlet and return air lane and the transport lane to 1.5 times the width of the transport lane.

[0065] Step 3: Use segmented excavation technology to divide the horizontal return air tunnel into multiple adjustment units. Each unit independently adjusts the distance with the transport tunnel according to the real-time RSI. The unit length is 2-3 times the width of the transport tunnel.

[0066] Step 4: Use the digital twin system to simulate the surrounding rock stress distribution at different spacings, verify that the safety factor of the adjusted spacing is ≥ 1.3, and generate construction instructions;

[0067] Step 5: Feedback the optimized spacing parameters to the tunnel boring machine control system, dynamically adjust the cutting trajectory, and achieve a spacing adjustment accuracy error of ≤±5cm.

[0068] Furthermore, in the step 2, the surrounding rock stability index RSI is calculated by the following method:

[0069]

[0070] Among them, σ c represents the uniaxial compressive strength of surrounding rock, σ max represents the real-time maximum principal stress, d allow represents the allowable displacement threshold, d means Represents the measured displacement rate.

[0071] The parts not described in detail in the present invention are all known technologies to those skilled in the art. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for recovering three soft coal seams, characterized in that: The following steps are involved: Step 1: Design the cross section of the return air lane to be a straight wall arch, the cross section of the opening eye and the transport lane to be a rectangle, and dynamically adjust the cross section size to match the real-time stress monitoring data; Step 2: The uncollapsed transport lane on the upper working face is taken as part of the return air lane, and the return air lane is arranged in stages along the closed end of the stop mining line toward the goaf, with the angle dynamically adjusted to 15° in the front section, 10° in the middle section, and 5° in the end section; Step 3: Arrange a horizontal return air lane parallel to the upper working face collapsed transport lane along the inner end of the oblique return air lane, and dynamically adjust the spacing to 1.5 times the width of the transport lane; Step 4: vertically arrange the working face opening eye at the end of the horizontal return air tunnel, cross the upper working face cave-in opening eye and the transport tunnel to enter the solid coal seam, and use the support parameter optimization algorithm to dynamically adjust the anchor density; Step five, arrange the transport tunnel in the solid coal seam, use retractable brackets to achieve dynamic width adjustment, and connect it with the preparation tunnel. The width of the transport tunnel is equal to the width of the collapsed transport tunnel on the upper working face.

2. The three-soft coal seam mining method according to claim 1 is characterized in that: The dynamic adjustment of the cross-section size to match the real-time stress monitoring data comprises the following steps: 1) Pre-embed fiber grating sensors on the surface and inside of the surrounding rock of the return air tunnel, transport tunnel and cut hole to collect surrounding rock stress, displacement and deformation data in real time; 2) Use edge computing equipment to filter and reduce noise on the collected data, extract the stress concentration factor and deformation rate of the key cross-section of the surrounding rock, and generate a dynamic stress field distribution map; 3) Based on the preset cross-section size adjustment rule library, dynamically adjust the tunnel cross-section size according to the real-time stress field distribution: When the stress concentration factor is ≥1.5 or the deformation rate is ≥0.5mm / d, the section expansion instruction is triggered to expand the width of the straight wall arch section by 10%-15%; When the stress field is stable and the deformation rate is ≤0.1mm / d, the section contraction instruction is triggered to restore the basic section size; 4) Use the digital twin system to simulate the stability of the surrounding rock of the adjusted section, verify that the safety factor of the support structure is ≥1.3, and generate construction instructions; 5) Feedback the optimized cross-sectional dimension parameters to the tunnel boring machine control system in real time, dynamically adjust the tunneling and cutting trajectory, and realize closed-loop control of the cross-sectional dimension.

3. The three-soft coal seam mining method according to claim 1 is characterized in that: The method of dynamically adjusting the anchor density using the support parameter optimization algorithm comprises the following steps: S1, during the tunnel excavation process, the surrounding rock stress, displacement and anchor force data are collected in real time through distributed sensors to build a multi-dimensional support parameter database; S2, builds a support parameter optimization model based on deep learning algorithm. The input parameters include surrounding rock strength index, tunnel cross-section shape, and real-time stress field distribution. The output parameters include anchor length, diameter, spacing, and preload. S3, dynamically adjust the anchor density according to the output results of the model in step S2: When the deformation rate of the surrounding rock exceeds the threshold, the anchor arrangement is triggered to increase the density by 20%-30%; when the stress field tends to be stable, the anchor density is reduced to the basic value to reduce material consumption; S4, simulates the tunnel stability under different bolt densities through the digital twin system, verifies the reliability of the optimization scheme, and generates construction instructions.

4. The three-soft coal seam mining method according to claim 3 is characterized in that: The method for dynamically adjusting the spacing in step 3 to 1.5 times the width of the transport lane is: Step 1: pre-embed distributed fiber grating sensors in the roof and side walls of the horizontal return air tunnel and the upper working face collapsed transport tunnel 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 the 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 inlet and return air lane and the transport lane to 1.5 times the width of the transport lane. Step 3: Use segmented excavation technology to divide the horizontal return air tunnel into multiple adjustment units. Each unit independently adjusts the distance with the transport tunnel according to the real-time RSI. The unit length is 2-3 times the width of the transport tunnel. Step 4: Use the digital twin system to simulate the surrounding rock stress distribution at different spacings, verify that the safety factor of the adjusted spacing is ≥ 1.3, and generate construction instructions; Step 5: Feedback the optimized spacing parameters to the tunnel boring machine control system, dynamically adjust the cutting trajectory, and achieve a spacing adjustment accuracy error of ≤±5cm.

5. The three-soft coal seam mining method according to claim 3 is characterized in that: In the step 2, the surrounding rock stability index RSI is calculated by the following method: Among them, σ c represents the uniaxial compressive strength of surrounding rock, σ max represents the real-time maximum principal stress, d allow represents the allowable displacement threshold, d means Represents the measured displacement rate.

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