Intelligent gangue filling control system for extra-thick coal seam

Abstract

The invention belongs to the technical field of coal seam filling control, and particularly discloses an intelligent gangue filling control system for an extra-thick coal seam. Dependence on compaction equipment is reduced on the premise that unified compaction and vibration in advance are not needed, unnecessary compaction procedures are reduced, manpower and material resource investment in the compaction process is saved, filling efficiency is improved, meanwhile, the overall stability and bearing performance of a filling body are enhanced, and meanwhile in the partition filling process, the filling efficiency is improved. By detecting the filling compactness of each area in stages and implementing differentiated compaction control strategies according to the detection result, on-demand compaction in the filling process is realized, the method can be used as a dynamic quality regulation and control supplement means of the filling process, and the pertinence and effectiveness of compaction operation are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of coal seam filling control, and specifically discloses an intelligent gangue filling control system for an extra-thick coal seam. Background Art

[0002] As coal mining progresses toward thicker seams, goafs, if not promptly and effectively filled, can easily lead to ground subsidence, threatening surface structures, farmland, and the ecological environment. Furthermore, large quantities of gangue generated during coal mining are often stored in open-air storage, which not only consumes land resources but also potentially pollutes water bodies through leaching. Using gangue to fill goafs not only effectively supports the roof and controls surface subsidence, but also allows for resourceful utilization of the gangue, reducing environmental pollution.

[0003] Prior art already utilizes coal gangue for goaf filling. For example, Chinese invention patent publication number CN117211864A proposes a method for retaining lanes along the goaf with gangue cementing in fully mechanized caving working faces. This method establishes an underground gangue transportation system and a coal lane grouting and filling system in the mine. Raw coal mined from the working face is sorted underground, then lifted to the surface. The resulting gangue is compacted by a compactor and injected into the filling area to fill gaps between the gangue fillings. This method achieves lane retention along the goaf in extremely thick coal seams while effectively utilizing a large amount of discarded gangue. This reduces tunneling volume, lowers lane retention costs, improves coal resource recovery, and enhances production safety.

[0004] However, the above scheme does not effectively classify the gangue particle size during the gangue screening process, resulting in the gangue of all particle sizes being uniformly compacted and vibrated before entering the filling operation. In fact, during the goaf filling process, not all areas require the gangue to be compacted to an extremely small particle size. Although excessively fine gangue particles can help improve local density, they lack the necessary skeletal support and will reduce the overall bearing capacity of the filling. At the same time, fine particles easily fill pores, causing seepage channels to be blocked, affecting the natural drainage of groundwater, and further causing pore water pressure to accumulate, increasing the risk of mining disasters such as floor heave.

[0005] In addition, since the gangue of mixed particle sizes is not classified and processed according to particle size, the particle grading of the mixed particle size is uneven during the compaction process, resulting in large differences in compaction resistance. This not only increases the compaction difficulty and operation time, but also forces the equipment to frequently operate under high-intensity working conditions, thereby exacerbating equipment wear and increasing maintenance frequency and operating costs. Summary of the Invention

[0006] In view of this, the present invention aims to propose an intelligent gangue filling control system for extra-thick coal seams. By constructing a gangue particle size matching mechanism based on geological zoning characteristics, implementing graded screening and differentiated filling strategies, the problems raised by the background technology are effectively solved.

[0007] The purpose of the present invention can be achieved through the following technical solutions: an intelligent gangue filling control system for extra-thick coal seams, including: a geological exploration module: obtaining the rock stratum crack distribution, shear stress distribution and pore distribution data of the coal seam goaf area through the geological radar wave reflection signal, and then superimposing and generating a geological structure strength map of the coal seam goaf area.

[0008] Regional division module: divides the goaf into high-pressure bearing area, transition deformation area and low-pressure filling area according to the geological structure strength map, and assigns a unique geological identification code to each area.

[0009] Particle size matching module: Based on the geological identification code, the mean fracture width, shear stress gradient, and porosity of the corresponding area are extracted, and the adaptive filling particle size of different areas is dynamically generated according to the preset particle size association rules.

[0010] Particle size screening and filling module: The gangue conveyor belt is controlled to perform particle size screening according to the adapted filling particle size of different areas, and regional filling is performed after screening.

[0011] Filling detection module: During the regional gangue filling process, a three-dimensional point cloud model of the filling body is generated in real time through a laser scanning array to detect the looseness of the filling.

[0012] Compaction control module: Differentiated compaction control is carried out according to the filling looseness of different areas, and the gangue particle size is re-screened based on the compaction control feedback results and filling progress.

[0013] Compared with the existing technology, the beneficial effects of the present invention are as follows: 1. The present invention conducts geological exploration and regional division of coal seam goaf areas, and matches the gangue of appropriate particle size for filling in combination with the geological characteristics of each area. It reduces the dependence on compaction equipment without the need for pre-uniform compaction and vibration. Since unnecessary compaction processes are reduced, it saves manpower and material resources in the compaction process, improves the filling efficiency, and at the same time enhances the overall stability and bearing performance of the filling body, thereby achieving efficient, energy-saving and adaptable goaf filling.

[0014] 2. During the partitioned filling process, the present invention detects the filling looseness of each area in stages and implements differentiated compaction control strategies based on the detection results, thereby achieving on-demand compaction during the filling process. It can serve as a supplementary means of dynamic quality control of the filling process, improve the pertinence and effectiveness of the compaction operation, and avoid waste of resources and ineffective compaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 Schematic diagram of the system composition of the present invention.

[0017] Figure 2 Schematic diagram of regional particle size screening in the present invention.

[0018] Figure 3 This is a flow chart for implementing the re-screening of gangue particle size based on the compaction control feedback results and filling progress in the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] See also Figure 1 As shown, the present invention proposes an intelligent gangue filling control system for extra-thick coal seams, which includes a geological exploration module, a regional division module, a particle size matching module, a particle size screening and filling module, a filling detection module and a compaction control module. The modules are connected and coordinated in sequence to construct a complete information flow from geological data collection to closed-loop control of the filling process, realizing intelligent, refined and automated management of gangue filling operations.

[0021] Specifically, the geological exploration module is used to obtain the rock fracture distribution, shear stress distribution and pore distribution data of the coal seam goaf area through the geological radar wave reflection signal, and then superimpose to generate the geological structure strength map of the coal seam goaf area.

[0022] As a specific implementation of the above module: a directional pulse radar beam is transmitted to the top and bottom plates of the coal seam goaf to obtain the amplitude attenuation characteristics and phase shift characteristics of the reflected signal.

[0023] In this supplementary implementation of the above solution, due to the weak and susceptible nature of radar reflection signals, the collected analog radar echoes must undergo analog-to-digital conversion, transforming them into digitized radar data suitable for analysis by a digital signal processor. Subsequently, the converted digital signals undergo preprocessing operations such as noise reduction filtering, gain adjustment, and time-depth mapping to eliminate the effects of system noise and propagation medium inhomogeneities. Only after completing this preprocessing process can the amplitude attenuation characteristics and phase offset information in the radar echoes be accurately extracted, providing reliable data support for subsequent goaf structure identification.

[0024] It should be pointed out that geological radar is a non-destructive detection technology that uses high-frequency electromagnetic waves to detect the distribution of underground media. Its working principle is: the radar antenna transmits short pulse electromagnetic waves to the stratum. When the electromagnetic waves encounter the interface of stratum with different dielectric constants or conductivity, they are reflected. The receiver records the time, amplitude, phase and other information of the return signal, and thus infers the underground structure based on the echo characteristics.

[0025] Specifically, the amplitude attenuation feature extracts amplitude sequences at different depths from preprocessed radar echo signals and analyzes their attenuation trends with depth. This feature reflects the extent and spatial distribution of fractures within the rock formation. Because fractures disrupt the continuity of the medium and alter its electromagnetic response, the more fractures there are, the greater the scattering and absorption of electromagnetic waves during propagation, resulting in more significant amplitude attenuation.

[0026] Furthermore, the phase shift characteristic refers to the change in the phase state of radar waves when they pass through or reflect at interfaces between different media. This characteristic primarily reflects the distribution of shear stress fields within the rock mass. Because changes in the dielectric constant of a medium are closely related to the stress state of the rock formation, analyzing phase shift can indirectly reveal information about stress changes within the rock formation.

[0027] The amplitude attenuation characteristics and phase shift characteristics are used to invert and generate the spatial distribution map of rock fractures and the shear stress distribution map respectively.

[0028] In one feasible implementation of the above scheme, a method for inverting the spatial distribution of rock fractures based on amplitude attenuation characteristics includes: establishing an empirical relationship model between amplitude attenuation and fracture width, and processing radar echo data from each measurement point using a numerical inversion algorithm to quantitatively identify fracture width. Subsequently, the identified fracture parameters are mapped to a three-dimensional geological coordinate system, and spatial interpolation and visualization techniques are used to generate a spatially continuous rock fracture distribution map.

[0029] In another possible implementation, the process of inverting the shear stress distribution in rock formations using phase shift characteristics involves extracting phase shift information for each region from the preprocessed radar signal. This information is then combined with the coupling relationship between the dielectric constant of the rock medium and the ground stress state to construct a physical mapping relationship between phase response and stress change. Based on this, the phase shift inversion method is used to deduce the shear stress distribution characteristics of the corresponding region, and a shear stress distribution map of the rock formation in the goaf is further generated.

[0030] The relative dielectric constant of the medium is calculated by combining the radar operating frequency and phase offset, and then the relative dielectric constant is inverted to generate a porosity spatial distribution map.

[0031] It's important to note that, based on the operating principle of radar, the electromagnetic waves it transmits experience a phase shift when passing through different media. The extent of this phase shift is closely related to the relative permittivity of the medium. Relative permittivity is a key physical quantity that describes a medium's response to electric fields and determines the propagation speed and attenuation of electromagnetic waves within it. Specifically, when radar waves pass through a medium with a specific porosity, the presence of pores changes the effective relative permittivity of the medium. Therefore, the porosity of the medium can be indirectly inferred by analyzing the phase shift of the radar signal.

[0032] The process first utilizes the radar system's ability to operate at different frequencies. By precisely measuring the phase offset of the radar echo signal and combining it with the known radar operating frequency, the relative dielectric constant of the medium can be calculated. Furthermore, based on the established empirical relationship between relative dielectric constant and porosity, an inversion algorithm is used to process the acquired data. Ultimately, this porosity data is mapped into a three-dimensional coordinate system to generate a spatial distribution map of the porosity.

[0033] It should be pointed out that the above-mentioned inversion of crack distribution, shear stress distribution, and porosity based on radar reflection signals all fall within the scope of existing technologies, and the specific inversion process will not be described here.

[0034] The fracture distribution map, shear stress distribution map and porosity distribution map generated above are fused and superimposed on multiple layers to construct a geological structure strength map of the coal seam goaf area.

[0035] The above-mentioned selection of fracture distribution, shear stress distribution and porosity as key geological characteristics of goaf during geological exploration is because these parameters can effectively reflect the physical and mechanical properties of underground rock formations and their structural stability, providing a scientific basis for subsequent regional division and gangue particle size matching.

[0036] Fracture distribution is a key indicator of rock mass integrity. Areas with developed fractures often exhibit high permeability and structural discontinuities, which can easily lead to rock deformation and even localized collapse. Such areas present a high risk of geological instability. Therefore, the use of fine-grained waste rock is a priority in backfill design to fully fill the fracture network, improve overall density and sealing performance, and prevent further damage caused by groundwater infiltration.

[0037] Shear stress distribution reflects the stress redistribution in the rock strata surrounding the goaf due to mining disturbances. Due to mining, stress concentration may occur in some areas, inducing shear slip deformation in the rock mass. When backfilling in these areas, attention should be paid to the shear strength and deformation adaptability of the backfill material. Selecting a waste rock particle size combination with good skeletal support capacity, while balancing load-bearing performance and deformation coordination, will enhance rock stratum stability.

[0038] Porosity indicates the degree of pore space development within a rock, directly affecting its permeability and water holding capacity. Using too small a particle size of waste rock during the filling process can clog existing seepage channels, hindering the normal drainage of groundwater. This can lead to increased pore water pressure and increase the risk of mining disasters such as floor heave.

[0039] The area division module is used to divide the goaf into a high-pressure bearing area, a transition deformation area and a low-pressure filling area according to the geological structure strength map, and assign a unique geological identification code to each area.

[0040] Optionally, the specific contents of the above module are as follows: extracting areas where the crack width is greater than a set threshold from the geological structure strength map, and expanding outward by a set buffer distance with the boundary coordinates of the area as the center to form a high-pressure bearing area.

[0041] The threshold for setting the crack width can be determined by plotting a crack width frequency distribution histogram based on the frequency information of crack widths in each region of the crack distribution map. Specifically, the crack width value corresponding to the median of the cumulative frequency in the histogram can be selected as the crack width threshold.

[0042] It should be noted that the above-mentioned method of expanding the influence range outward by a certain distance when dividing the high-pressure bearing area reflects the spatial diffusion effect of the mechanical response of the rock structure and helps to cover the potential risk area more comprehensively.

[0043] High-pressure bearing areas are usually distributed in the core parts of goafs. The cracks in this area are more significantly developed and are often located in high stress concentration zones caused by mining, with higher structural bearing requirements.

[0044] A ring area outside the high-pressure bearing area is marked as the transition deformation zone, which is used to represent the intermediate zone where the rock stratum gradually transitions from a high-stress state to a low-stress state. In this transition zone, the uneven stress redistribution caused by mining leads to mechanical responses such as shear slip, local yielding or micro-fracture inside the rock mass, thereby inducing deformation of varying degrees.

[0045] The remaining unmarked areas are classified as low-pressure filling areas, representing areas with relatively stable overall structures and low bearing capacity. Low-pressure filling areas are usually distributed in the periphery of the goaf and are less affected by mining.

[0046] The crack width data existing in the high-pressure bearing area are statistically analyzed from the rock stratum crack spatial distribution map corresponding to the geological structure strength map, and the arithmetic mean is calculated to obtain the mean crack width of the area.

[0047] It should be noted that in the high-pressure bearing area, the average crack width is used as the main basis for selecting the particle size of the gangue filling, and the shear stress and porosity are not considered separately. The reason is that the cracks in this area are densely developed and the rock integrity is poor. The core engineering demand of this area is to achieve effective sealing of the cracks. Therefore, the crack width directly determines whether the filling material can effectively enter and fully fill the gaps, and is a key factor affecting the filling density and sealing performance.

[0048] The maximum shear stress and the minimum shear stress values ​​in the transition deformation zone are extracted from the shear stress distribution diagram, and the shear stress gradient of the region is obtained based on the difference between the maximum shear stress and the minimum shear stress values ​​divided by the maximum shear stress.

[0049] It should be noted that the reason shear stress gradient is used as the primary basis for selecting waste rock fill particle size in the transition deformation zone, rather than relying solely on fracture distribution and porosity, is that the transition deformation zone is located in the intermediate zone between high stress and low stress. The rock formation undergoes stress redistribution due to mining, which is prone to shear slip and local deformation. The key engineering requirement for this area is that the filling material should have good shear resistance and a certain degree of deformation adaptability to coordinate stress changes and prevent structural instability. The shear stress gradient reflects the severity of stress changes in this area and can comprehensively reflect the mechanical response characteristics of the rock formation, making it a key parameter guiding particle size selection.

[0050] The porosity of the low-pressure filling zone is extracted from the porosity distribution map.

[0051] It should be noted that in low-pressure filling zones, porosity is the primary factor in selecting waste rock fill particle size, rather than solely relying on fracture distribution and shear stress. This is because the overall rock structure in low-pressure filling zones is relatively stable, with low ground stress levels, limited fracture development, and minimal impact from mining. Filling in this area focuses on ensuring adequate filling efficiency and drainage performance to avoid blockage of seepage channels due to excessively small particle size, which can lead to engineering problems such as increased pore water pressure and floor heave. Porosity directly reflects the development of void spaces within the rock and is a key factor in determining whether the filling material can effectively penetrate and maintain good permeability.

[0052] Each region is assigned a geological identification code including location, volume, mean fracture width, shear stress gradient, and porosity.

[0053] The particle size matching module is used to extract the mean value of crack width, shear stress gradient and porosity of the corresponding area based on the geological identification code, and dynamically generate the adaptive filling particle size of different areas according to the preset particle size association rules.

[0054] According to a preferred embodiment of the above module, the particle size association rule is as follows: for the high-pressure bearing area, a decreasing function relationship is established between the particle size of the gangue filling and the average value of the crack width in the area.

[0055] For example, the expression for the particle size correlation in the high-pressure bearing area is: , where Indicates the maximum allowable particle size in the high-pressure bearing area. represents the mean crack width, represents the preset crack filling safety factor, and .

[0056] The physical significance of the particle size correlation in the above-mentioned high-pressure bearing area is to ensure that the particle size of the gangue is smaller than the width of the rock cracks. By selecting small-sized gangue for filling, it can be densely stacked to form a high-density filling body, thereby effectively sealing the cracks and significantly improving the compressive strength.

[0057] In particular, the above relational expression It is used to control the safety margin of the gangue particle size relative to the width of the rock cracks, ensuring that the gangue can effectively enter and fully fill the cracks, and avoid being unable to block due to excessive particle size. The method of determining it is to determine the particle size-crack matching ratio based on similar engineering cases as the crack filling safety factor.

[0058] For the low-pressure filling area, the relationship between the particle size of the gangue filling and the porosity of the area satisfies the square root function.

[0059] For example, the particle size correlation expression of the low-pressure filling area is , where Indicates the minimum allowable particle size in the low-pressure filling area. represents the porosity, Indicates the preset seepage assurance coefficient.

[0060] The physical significance of the particle size correlation in the low-pressure filling zone results in a nonlinear increase in gangue particle size with increasing porosity, preventing blockage of seepage paths caused by selecting an excessively small particle size. This functional form is sensitive to porosity changes without over-magnification, effectively preserving the formation's inherent drainage capacity. Furthermore, by adjusting the seepage assurance factor, the output particle size can be flexibly controlled, ensuring efficient filling while maintaining formation seepage balance.

[0061] In particular, the above relational expression It is used to adjust the degree of protection of the gangue particle size on the original seepage capacity of the formation, to prevent the blockage of the seepage channel due to too small particle size, thereby causing geological disasters such as increased water pressure and bottom heave.

[0062] The method of determining the porosity is to simulate the stacking morphology of gangue particles during the filling process and its influence on porosity and connectivity under experimental conditions. Specifically, the gangue is first graded using screening equipment to obtain a series of samples with different particle size ranges. The bulk density of each particle size combination is measured using a bulk density meter under laboratory conditions, and the corresponding porosity is calculated. The permeability coefficient of different particle size combinations is then determined using a permeameter. By changing the particle size distribution of the sample, the corresponding permeability coefficient change is recorded. Then, a mathematical relationship between particle size, porosity and connectivity is established based on experimental and simulation data. The appropriate seepage assurance coefficient is determined through this mathematical relationship to ensure that the filling body can be filled efficiently and maintain good drainage capacity.

[0063] For the transition deformation zone, a mixed filling method of large-size and small-size gangue is adopted, and the mixing ratio is determined according to the shear stress gradient of the area; among them, the mixed particle size ratio is linearly related to the shear stress gradient.

[0064] For example, the expression for the mixing ratio in the transition deformation zone is: , where The mass ratio of small-sized gangue in the mixture is represented by , represents the shear stress gradient, It represents the pre-mixed gradation shear coefficient, which controls the response sensitivity of the particle size ratio to the stress gradient change. is a bias term used to adjust the basic mixing ratio.

[0065] In the above relational expression It reflects the influence intensity of shear stress gradient on the ratio of mixed particle size gangue, that is, the change in the proportion of fine particles caused by the change of unit stress gradient. It is determined by mixing small-size and large-size gangue in different proportions to make uniform samples, and conducting shear performance tests on each group of samples. The relationship curve between particle size ratio and shear performance parameters is drawn, and the relationship between particle size ratio and shear performance parameters is fitted through linear regression analysis to determine the gradation shear coefficient.

[0066] In the above relational expression It is used to set the basic fine-grained gangue ratio when there is no obvious shear stress difference, to ensure that the fill body has the minimum density and shear resistance to cope with potential ground disturbances. It is determined by referring to the fine-grained gangue ratio that needs to be maintained under the zero stress gradient state in the implemented projects.

[0067] It should be noted that the linear relationship between the mass proportion of small-size gangue and the shear stress gradient is set above because as the shear stress gradient increases, the stress distribution of the rock formation becomes more uneven, and the requirements for shear strength and filling density become higher. Fine-grained gangue helps to improve the friction and inter-particle effect, thereby enhancing the shear resistance, so its proportion should increase accordingly. Compared with the nonlinear relationship, the linear relationship has the advantages of stable output and rapid response, and is more suitable for use in closed-loop control systems.

[0068] The physical meaning of the particle size correlation in the above-mentioned transition deformation zone is that when the shear stress gradient is large, the proportion of small particles is large and the proportion of large particles is small, which enhances the filling compactness; when the shear stress gradient is small, the proportion of small particles is small and the proportion of large particles is large, which improves the shear skeleton strength. Thus, a graded structure is formed by mixed particle size gangue, small particles fill the gaps between large particles, and improve the overall density. Large particles interlock to form a shear skeleton to resist stratum dislocation. The coordinated deformation capacity of the graded filling body is enhanced to avoid delamination cracks in the junction area.

[0069] The above-mentioned particle size association rules construct a dynamic particle size control mechanism driven by geological structure parameters, which can intelligently match the optimal filling particle size or particle size combination according to the geological conditions of different regions, thereby improving the overall supporting performance and adaptability of waste rock filling.

[0070] According to a further preferred embodiment of the above module, the adaptive filling particle size of different areas is dynamically generated according to the preset particle size association rules. See the following process: for the high-pressure bearing area, the mean value of the crack width is input into the decreasing association function to output the maximum allowed particle size value.

[0071] For the transition deformation zone, the shear stress gradient is input into a linear relationship to output the mixing ratio of small and large particle sizes.

[0072] For low-pressure filling areas, the porosity is input into the square root relationship to output the minimum allowable particle size value.

[0073] The particle size screening and filling module is used to control the gangue conveyor belt to perform particle size screening according to the adaptive filling particle size of different areas, and perform regional filling after screening.

[0074] In one possible implementation, the above-mentioned module includes the following contents: the coal gangue to be filled is evenly distributed on the main conveyor belt integrated with a fine screen group and a coarse screen group, wherein the aperture of the fine screen group is set to the maximum allowable particle size value corresponding to the high-pressure bearing area, and the aperture of the coarse screen group is set to the minimum allowable particle size value corresponding to the low-pressure filling area.

[0075] The main conveyor belt first passes through the fine screen group to screen out small-sized gangue with a particle size smaller than the maximum allowable particle size value, and guides it into the fine particle conveying channel.

[0076] The larger particles that are not screened out by the fine screen group continue to move forward with the main conveyor belt and enter the screening area of ​​the coarse screen group, where large-sized gangue with a particle size larger than the minimum allowable particle size value is retained and introduced into the coarse particle conveying channel.

[0077] The fine particle conveying channel and the coarse particle conveying channel are respectively provided with branch outlets and connected to a common intersection.

[0078] The fine particle conveying channel branches out and conveys directionally to the filling operation point of the low-pressure filling area. The coarse particle conveying channel branches out and conveys directionally to the filling operation point of the low-pressure filling area. The two branch materials from the fine particle conveying channel and the coarse particle conveying channel converge at a common intersection point and are mixed according to the mixing ratio of small particle size to large particle size, and then conveyed to the transition deformation zone through the mixing conveying channel.

[0079] See the above-mentioned medium-area particle size screening Figure 2 shown.

[0080] The present invention further configures a screening conveyor belt on the basis of matching appropriate gangue particle size for different geological areas, which can simultaneously complete the particle size screening operation during the gangue transportation process, ensuring that the gangue particle size transported to each filling area meets the adaptation requirements, thereby improving the filling accuracy and construction efficiency.

[0081] It needs to be explained that the reason why the main conveyor belt passes through the fine screen group first and then the coarse screen group during particle size screening is that small-particle materials have strong fluidity and are easy to clog the screen holes; if they pass through the coarse screen first, the subsequent accumulation of small particles may cause the fine screening efficiency to decrease. Fine screening first can avoid such problems. In addition, if large-particle gangue is left behind by coarse screening first, fine particles may be mixed in during fine screening, affecting the high-pressure bearing area's requirements for particle size consistency. Fine screening first can better ensure the purity of materials in different channels.

[0082] The filling detection module is used to generate a three-dimensional point cloud model of the filling body in real time through a laser scanning array during the regional gangue filling process, thereby detecting the filling looseness.

[0083] It should be understood that the gangue particle size parameters set for the high-pressure bearing area and the low-pressure filling area at the front end when performing particle size distribution are usually the boundary values ​​allowed by the design. Under this boundary condition, the gangue particle size obtained by screening may fluctuate within a certain range, resulting in uneven particle grading, high porosity and other problems during the filling process, causing loose filling. Therefore, it is necessary to implement loose filling detection during the filling operation. By dynamically monitoring the filling quality, filling deviations can be discovered and corrected in a timely manner.

[0084] In a preferred embodiment, the specific implementation process of the filling detection module is as follows: during the filling operation, the gangue transportation volume of each area is accumulated in real time, and a trigger threshold based on the filling volume is set. When the accumulated filling volume reaches the preset trigger threshold, multiple groups of linear array lasers installed on the filling working surface are triggered to scan the surface of the filling body from different perspectives at a set frequency, and the multi-angle scanning results are fused through point cloud registration to construct a three-dimensional point cloud model of the filling body.

[0085] For example, the above accumulation of the gangue transport volume can be estimated by converting the volume equivalent according to the particle size of the transported gangue to obtain the gangue transport volume.

[0086] The trigger threshold based on the filling volume can be set according to the regional volume. During implementation, the accumulated gangue transport volume is compared with the preset trigger threshold. When the threshold is reached, the looseness detection of the filling body at that stage is automatically triggered. After each detection is completed, the accumulation of the gangue transport volume for the next stage is restarted.

[0087] The Euclidean distance between adjacent points in the point cloud model is calculated, and the mean and standard deviation of the distance distribution are calculated.

[0088] The coefficient of variation was obtained by calculating the ratio of the standard deviation to the mean as the filling looseness.

[0089] When performing the loose filling analysis based on the point cloud model, it is considered that the Euclidean distance between adjacent points in the point cloud model reflects the spatial distribution density of the gangue particles, the mean of the spacing distribution reflects the density of the overall filling structure, the standard deviation of the spacing distribution reflects the discreteness of the point spacing distribution, and the ratio of the standard deviation to the mean, that is, the coefficient of variation, reflects the relative discreteness of the filling structure. This ratio comprehensively considers the density and uniformity of the filling. The larger the ratio, the looser the filling, and the smaller the ratio, the tighter the filling.

[0090] The compaction control module is used to perform differentiated compaction control according to the filling looseness of different areas, and to re-screen the gangue particle size based on the compaction control feedback results and filling progress.

[0091] In the implementation of the above scheme, differentiated compaction control is implemented according to the filling looseness of different areas as follows: the filling looseness detected each time during the filling process of each area is compared with the critical threshold of the area. If the actual filling looseness of an area is higher than the critical threshold, the pre-configured compaction mode is called to trigger the compactor to perform the compaction operation.

[0092] The pre-configured compaction mode is as follows: the high-pressure bearing area triggers the high-frequency and low-amplitude compaction mode, the transition deformation area triggers the medium-frequency alternating amplitude compaction mode, and the low-pressure filling area triggers the low-frequency and high-amplitude compaction mode.

[0093] The critical filling looseness thresholds corresponding to the different areas mentioned above show the following relationship: high-pressure bearing area < transition deformation area < low-pressure filling area. This is because the high-pressure bearing area requires minimum looseness to ensure structural density; the transition deformation area allows moderate looseness to enhance adaptability; the low-pressure filling area focuses on construction efficiency, and the looseness limit is relatively higher.

[0094] Specifically, the critical threshold value of filling looseness in each area can be extracted and set according to the relevant standards in the technical specifications for goaf filling.

[0095] It's important to understand that high-frequency, low-amplitude compaction is used in the high-pressure bearing zone. Because this area requires high rock structural stability and strict deformation control, high-amplitude vibration is not suitable to prevent secondary disturbances or damage to the integrity of the surrounding rock mass. High-frequency vibration effectively stimulates the microscopic rearrangement of gangue particles, reduces porosity, and improves contact between particles, thereby ensuring high density and load-bearing capacity of the fill in this area.

[0096] The transition deformation zone adopts a medium-frequency variable amplitude compaction mode, that is, the amplitude is dynamically adjusted based on the medium-frequency vibration. This mode helps to achieve a uniform distribution of the stress field in the filling body while ensuring a certain compaction effect, adapting to the local shear deformation or stress adjustment needs that may exist in the area, and enhancing the compatibility and adaptability of the filling body to rock deformation.

[0097] The low-pressure filling area uses a low-frequency, high-amplitude compaction mode. Because this area requires relatively low filling density and high-frequency vibrations can easily waste energy or over-disturbing the loose material, a low-frequency, high-impact energy approach is used. This allows the gangue particles to naturally settle under the effects of gravity and impact, achieving initial compaction and improving construction efficiency while ensuring basic stability.

[0098] In a further embodiment of the above scheme, see Figure 3 As shown, the gangue particle size re-screening based on the compaction control feedback results and filling progress refers to the following process: after the compaction is completed, a secondary laser scan is started to generate a post-compaction point cloud model to obtain the filling looseness, and at the same time, the completed gangue transportation volume in the current area is accumulated.

[0099] Compare the looseness of the filling after compaction with the critical threshold of the area. If the looseness of the filling after compaction is less than or equal to the critical threshold, continue the filling operation. If the looseness after compaction is still higher than the critical threshold, compare the current cumulative waste rock transportation volume with the volume of the area to determine whether the current filling progress has reached the predetermined completion progress.

[0100] The above judgment operation method is: divide the cumulative conveying volume by the volume of the area to calculate the percentage value of the current filling progress, and then compare it with the predetermined completion progress, where the completion progress reflects that the filling has entered the end.

[0101] If the current filling progress reaches the completion progress, the supplementary compaction operation will continue.

[0102] The current filling progress mentioned above has reached the completion progress, indicating that the filling operation has entered the final stage. During this stage, it was found that the looseness after compaction was still relatively high, indicating that the particle size of the gangue has limited influence on the overall compaction effect during the entire filling process. At this time, the engineering conditions and time window for re-screening and adjusting the particle size are no longer available. In order to ensure the filling quality, additional compaction measures should be taken to increase the local density and improve the overall stability and bearing capacity of the filling body.

[0103] If the current filling progress has not reached the completion progress, a particle size screening instruction is sent to the particle size screening filling module.

[0104] The fact that the current filling progress has not reached the completion progress mentioned above indicates that the filling operation is still in progress. At this time, if the test finds that the looseness of the compacted filling body is too high, it means that the current gangue particle size is not compatible with the geology of the area, and the unreasonable particle grading may lead to poor compaction effect. Since the filling process has not been completed, there is still operating space and time window for adjusting material properties. Therefore, it is necessary to start the particle size screening mechanism in time to optimize the gangue particle size matching, so as to fundamentally improve the filling quality. In addition, if the density is improved by simply increasing the number of compactions at this stage, it may not only aggravate the disturbance of the rock formation in the goaf due to frequent vibration, induce the risk of structural instability, but also lead to increased equipment wear and a significant increase in energy consumption.

[0105] In particular, the particle size screening is implemented as follows: when the particle size screening instructions from the high-pressure bearing area and the low-pressure filling area are triggered, the gangue in the same particle size group is screened out from the existing gangue in the fine-grained conveying channel and the coarse-grained conveying channel through particle size clustering for filling.

[0106] When the particle size screening instruction from the transition deformation zone is triggered, the particle size screening of the high-pressure bearing zone and the low-pressure filling zone is triggered synchronously.

[0107] This particle size screening process selects consistent-sized waste rock for filling, ensuring that the boundary conditions for waste rock particle size in the high-pressure bearing zone and the low-pressure filling zone are met. This optimizes the distribution of waste rock particles and effectively mitigates the uneven gradation caused by significant regional particle size differences. This strategy helps reduce the internal porosity of the filling and improves its overall density, fundamentally resolving the problem of loose filling through material matching.

[0108] The parameters involved in the above formula are all dimensionless and calculated numerically. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0109] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0110] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0111] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0112] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0113] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An intelligent gangue filling control system for extra-thick coal seams, characterized in that: include: Geological exploration module: obtains the rock fracture distribution, shear stress distribution and pore distribution data of the coal seam goaf area through the geological radar wave reflection signal, and then generates the geological structure strength map of the coal seam goaf area by superposition; Regional division module: divides the goaf into high-pressure bearing area, transition deformation area and low-pressure filling area according to the geological structure strength map, and assigns a unique geological identification code to each area; Particle size matching module: extracts the mean fracture width, shear stress gradient, and porosity of the corresponding area based on the geological identification code, and dynamically generates the adaptive filling particle size for different areas according to the preset particle size association rules; Particle size screening and filling module: controls the gangue conveyor belt to perform particle size screening according to the adapted filling particle size of different areas, and performs regional filling after screening; Filling detection module: During the regional gangue filling process, a three-dimensional point cloud model of the filling body is generated in real time through a laser scanning array to detect the looseness of the filling; Compaction control module: Differentiated compaction control is carried out according to the filling looseness of different areas, and the gangue particle size is re-screened based on the compaction control feedback results and filling progress.

2. The intelligent gangue filling control system for extra-thick coal seams according to claim 1, characterized in that: The geological exploration module includes the following contents: Directional pulse radar beams are emitted toward the roof and floor of the coal seam goaf to obtain the amplitude attenuation and phase shift characteristics of the reflected signals. The amplitude attenuation characteristics and phase shift characteristics are used to invert and generate the spatial distribution map of rock fractures and the shear stress distribution map respectively; The relative dielectric constant of the medium is calculated by combining the radar operating frequency and phase offset, and then the porosity spatial distribution map is generated by inverting the relative dielectric constant. The fracture distribution map, shear stress distribution map and porosity distribution map generated above are fused and superimposed on multiple layers to construct a geological structure strength map of the coal seam goaf area.

3. The intelligent gangue filling control system for extra-thick coal seams according to claim 1, characterized in that: The content of the area division module is as follows: Extract the area with crack width greater than the set threshold from the geological structure strength map, and expand the set buffer distance outward with the boundary coordinates of the area as the center to form a high-pressure bearing area; The annular zone around the high-pressure bearing area is marked as the transition deformation zone; The remaining unmarked areas were classified as low-pressure filling areas; From the spatial distribution map of rock fractures corresponding to the geological structure strength map, the fracture width data existing in the high-pressure bearing area are counted, and the arithmetic mean value is calculated to obtain the mean fracture width of the area; Extracting the maximum shear stress and the minimum shear stress values ​​in the transition deformation zone from the shear stress distribution diagram, and obtaining the shear stress gradient of the region based on the difference between the maximum shear stress and the minimum shear stress values ​​divided by the maximum shear stress; Extract the porosity of the low-pressure filling zone from the porosity distribution map; Each region is assigned a geological identification code including location, volume, mean fracture width, shear stress gradient, and porosity.

4. The intelligent gangue filling control system for extra-thick coal seams according to claim 1, characterized in that: The particle size association rules include the following: For the high-pressure bearing area, a decreasing function relationship is established between the particle size of the gangue filling and the mean value of the crack width in the area; For low-pressure filling areas, the relationship between the particle size of the gangue filling and the porosity of the area satisfies the square root function; For the transition deformation zone, a mixed filling method of large-size and small-size gangue is adopted, and the mixing ratio is determined according to the shear stress gradient of the area; among them, the mixed particle size ratio is linearly related to the shear stress gradient.

5. The intelligent gangue filling control system for extra-thick coal seams according to claim 4, characterized in that: The process of dynamically generating the adaptive filling particle sizes for different regions according to the preset particle size association rules is as follows: For the high-pressure bearing area, the mean value of the crack width is input into the decreasing correlation function to output the maximum allowed particle size value; For the transition deformation zone, the shear stress gradient is input into a linear relationship to output the mixing ratio of small particle size and large particle size; For low-pressure filling areas, the porosity is input into the square root relationship to output the minimum allowable particle size value.

6. The intelligent gangue filling control system for extra-thick coal seams according to claim 5, characterized in that: The particle size screening and filling module is specifically implemented as follows: The coal gangue to be filled is evenly distributed on the main conveyor belt integrated with a fine screen group and a coarse screen group. The aperture of the fine screen group is set to the maximum allowable particle size value corresponding to the high-pressure bearing area, and the aperture of the coarse screen group is set to the minimum allowable particle size value corresponding to the low-pressure filling area. The main conveyor belt first passes through the fine screen group to screen out the small-sized gangue with a particle size smaller than the maximum allowable particle size value, and then guides it into the fine particle conveying channel; The gangue particles that are not screened out by the fine screen group continue to move forward along the main conveyor belt into the screening area of ​​the coarse screen group. The large-sized gangue particles with a particle size larger than the minimum allowable particle size are retained and introduced into the coarse particle conveying channel. The fine particle conveying channel and the coarse particle conveying channel are respectively provided with branch outlets and connected to a common intersection; The fine particle conveying channel branches out and conveys directionally to the filling operation point of the low-pressure filling area. The coarse particle conveying channel branches out and conveys directionally to the filling operation point of the low-pressure filling area. The two branch materials from the fine particle conveying channel and the coarse particle conveying channel converge at a common intersection point and are mixed according to the mixing ratio of small particle size to large particle size, and then conveyed to the transition deformation zone through the mixing conveying channel.

7. The intelligent gangue filling control system for extra-thick coal seams according to claim 1, characterized in that: The specific implementation process of the filling detection module is as follows: During the filling process, the volume of waste rock transported in each area is accumulated in real time, and a trigger threshold based on the filling volume is set. When the accumulated filling volume reaches the preset trigger threshold, multiple groups of linear array lasers installed on the filling working surface are triggered to scan the filling body surface from different perspectives at a set frequency. The multi-angle scanning results are fused through point cloud registration to construct a 3D point cloud model of the filling body. Calculate the Euclidean distance between adjacent points in the point cloud model, and then calculate the mean and standard deviation of the distance distribution; The coefficient of variation was obtained by calculating the ratio of the standard deviation to the mean as the filling looseness.

8. The intelligent gangue filling control system for extra-thick coal seams according to claim 7, characterized in that: The differentiated compaction control according to the filling looseness of different areas is implemented as follows: The filling looseness detected at each trigger during the filling process of each area is compared with the critical threshold of the area. If the actual filling looseness of a certain area is higher than the critical threshold, the pre-configured compaction mode is called to trigger the compactor to perform the compaction operation; The pre-configured compaction mode is as follows: the high-pressure bearing area triggers the high-frequency and low-amplitude compaction mode, the transition deformation area triggers the medium-frequency alternating amplitude compaction mode, and the low-pressure filling area triggers the low-frequency and high-amplitude compaction mode.

9. The intelligent gangue filling control system for extra-thick coal seams according to claim 1, characterized in that: The gangue particle size re-screening based on the compaction control feedback results and filling progress is as follows: After compaction is completed, a secondary laser scan is started to generate a point cloud model after compaction to obtain the filling looseness, and at the same time, the completed waste rock transportation volume in the current area is accumulated; Compare the looseness of the filling after compaction with the critical threshold of the area. If the looseness of the filling after compaction is less than or equal to the critical threshold, continue the filling operation. If the looseness of the filling after compaction is still higher than the critical threshold, compare the current cumulative waste rock transport volume with the volume of the area to determine whether the current filling progress has reached the predetermined completion progress. If the current filling progress reaches the completion progress, the supplementary compaction operation will continue; If the current filling progress has not reached the completion progress, a particle size screening instruction is sent to the particle size screening filling module.

10. The intelligent gangue filling control system for extra-thick coal seams according to claim 8, characterized in that: The particle size screening is specifically implemented as follows: When the particle size screening instructions from the high-pressure bearing area and the low-pressure filling area are triggered, the gangue in the same particle size group is selected from the existing gangue in the fine-grained conveying channel and the coarse-grained conveying channel through particle size clustering for filling; When the particle size screening instruction from the transition deformation zone is triggered, the particle size screening of the high-pressure bearing zone and the low-pressure filling zone is triggered synchronously.

Images