Fully mechanized coal mining face coal rock interface simulation identification method and intelligent coal mining machine

Abstract

The invention discloses a fully mechanized coal mining face coal-rock interface simulation identification method and an intelligent coal mining machine. The method comprises the following steps: 1, constructing a coal-rock interface inversion model based on a radiation field characteristic value; 2, when the thickness h of the coal seam is equal to 0, the radiation intensity measured by the gamma-ray detector at the P point in the rock stratum is J0, and the radiation intensity is substituted into the inversion model of the coal-rock interface to calculate related parameter values; 3, setting the span delta in the horizontal direction, setting i to be 1, and detecting the corresponding radiation intensity Ji by taking the point Xi as a detection starting point; 4, substituting the radiation intensity Ji into the inversion model of the coal-rock interface to calculate the fluctuation slope tau of the coal-rock interface of the next prediction section; 5, determining the position of the next detection point Xi + 1 according to the position of the current detection point Xi, the predicted fluctuation slope tau of the coal-rock interface and the horizontal span delta; and 6, judging whether simulation is finished or not. Dynamic tracking of the coal-rock interface situation is realized, coal-rock interface simulation identification of a fully mechanized coal mining face is realized, and a coal mining machine is guided to intelligently cut coal.

Description

Technical Field

[0001] The invention relates to a coal-rock interface simulation identification method for a fully mechanized mining working face and an intelligent coal mining machine. Background Art

[0002] The "unmanned" or "less-manned" fully mechanized mining face is of great significance to the safe and efficient production of coal mines. As one of the key electromechanical equipment of modern fully mechanized mining faces, the intelligent level of the coal mining machine directly affects the safe production and mining efficiency of the entire fully mechanized mining face. As the key technology of intelligent mining of coal mining machines, the intelligent recognition technology of coal-rock interface is the core of realizing intelligent coal cutting technology.

[0003] The existing coal-rock identification technologies for fully mechanized mining working faces mainly include coal-rock image recognition technology, process signal monitoring and identification technology, and electromagnetic wave identification technology, among which:

[0004] Coal rock image recognition technology must be based on artificial design to work properly, and each method can usually only solve specific problems, with the disadvantages of singleness and repetitiveness, and cannot meet the requirements of intelligent and efficient production efficiency. In practical applications, due to the differences in coal and rock types and characteristics of different coal mining faces, the robustness and generalization ability of image processing technology in coal and rock recognition are limited, especially in machine learning algorithms, the problem of gradient disappearance often occurs, affecting the stability of recognition.

[0005] Process signal monitoring and identification technology is a technology for evaluating the cutting status of coal and rock. It realizes intelligent control, safe production and improves coal mining efficiency by real-time monitoring and analysis of various signals of the working face, such as electrical signals, mechanical signals, coal and rock deformation signals, etc. However, the vibration signal has requirements on the hardness of coal and rock, the cutting force signal has the disadvantage of large multi-axis data volume, the acoustic emission signal has a large data volume and is easily interfered by noise, the temperature signal is difficult to collect due to the obstruction of the roller, and the current signal is easily interfered by complex signals.

[0006] Electromagnetic wave identification technology uses the physical properties of coal and rock, such as dielectric constant, electrostatic conductivity, etc., as well as differences in chemical properties such as chemical composition, to perceive the coal-rock interface morphology. It does not destroy the stratum structure and stratum morphology, and can perform geological transparency and stratum analysis. Natural gamma rays are emitted from radioactive substances in rocks and coal seams. The content of radioactive substances in rocks is generally dozens of times that of radioactive substances in coal seams. Therefore, the gamma ray radiation of rock formations is usually much greater than that of coal seams. The existence of coal seams has a penetrating effect on gamma rays in rock formations, so by measuring the radiation of gamma rays passing through coal seams, the thickness of the current coal seam can be determined, and the intelligent coal cutting of coal mining machines can be guided. Summary of the invention

[0007] In view of the above problems, the present invention provides a method for simulating and identifying the coal-rock interface in a fully-mechanized mining face and an intelligent coal mining machine. Based on the difference in radiation characteristics between coal and direct roof rock, a radiation intensity detection method is adopted to establish an inversion model of the coal-rock interface based on the characteristic values ​​of the radiation field, and the undulating characteristics of the coal-rock interface are intelligently analyzed to achieve dynamic tracking of the coal-rock interface situation, realize simulation and identification of the coal-rock interface in the fully-mechanized mining face, and guide the coal mining machine to intelligently cut coal.

[0008] Name explanation:

[0009] Coal-rock interface undulation slope: the slope of several line segments that the coal-rock interface is divided into under the simulated interface.

[0010] In order to achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions:

[0011] A method for simulating and identifying the coal-rock interface of a fully mechanized mining face comprises the following steps:

[0012] Step 1: construct an inversion model of the coal-rock interface based on the characteristic value of the radiation field;

[0013] Step 2: When the coal seam thickness h=0, the radiation intensity measured by the gamma-ray detector at point P in the rock layer is J0, which is brought into the inversion model of the coal-rock interface to calculate the relevant parameter values;

[0014] Step 3: Set the horizontal span Δ, set i = 1, and use X i Point is the detection starting point and its corresponding radiation intensity is J i ;

[0015] Step 4: Set the radiation intensity J i Bring it into the inversion model of coal-rock interface to calculate the slope τ of the coal-rock interface fluctuation in the next section;

[0016] Step 5: According to the current detection point X i The next detection point X is determined by the position, predicted coal-rock interface undulation slope τ and horizontal span Δ i+1 Location;

[0017] Step 6: Determine whether the simulation is finished:

[0018] If the simulation is not over, then i+1, the next detection point determined in step 5 is detected and its corresponding radiation intensity J is detected. i , and go to step 4;

[0019] When the simulation is finished, all detection points are connected in sequence with straight lines and output as the simulation interface.

[0020] Preferably, at point X i The radiation intensity detected at is J i , construct Ji The calculation model is:

[0021]

[0022] Assuming μ(τw+Δh)=x, the inversion model of coal-rock interface is constructed as follows:

[0023]

[0024] In the formula, K' is the proportionality coefficient, q is the concentration of radioactive substances in rocks, ρ is the density of gangue, k is the attenuation coefficient of γ-rays of radioactive substances in rocks, and Φ(x) is the ratio e -x The Jin Ge function with a faster decrease, μ is the attenuation coefficient of the radioactive material gamma ray in the coal seam, τ is the i The slope of the next coal-rock interface is predicted at the location, w is the actual slope of the coal-rock interface, Δh is the thickness of a thin coal seam left between the predicted simulated interface and the actual coal-rock interface, is the maximum angle that the gamma-ray detector can detect, and l is the thickness of the direct top.

[0025] Preferably, in step 2, when the coal seam thickness h=0, then x=0, Substitute into the calculation to get The value of .

[0026] Preferably, the horizontal span Δ is the horizontal distance traveled by the intelligent coal mining machine in 0.1 seconds.

[0027] Correspondingly, an intelligent coal mining machine includes a coal mining machine body, and the coal mining machine body adopts any of the above-mentioned coal-rock interface simulation identification methods for the comprehensive mining working face to identify the coal-rock interface and mine coal.

[0028] Preferably, the gamma-ray detector is arranged just above or in front of the coal mining machine drum.

[0029] The beneficial effects of the present invention are:

[0030] First, the present invention forms a characterization of the coal-rock interface by analyzing the characteristics of the coal-rock interface, and on this basis, provides a model formula for calculating the radiation value formed at a certain point on the working surface, and determines the parameters affecting the distribution of the radiation field. Then, through the inversion model, a cross-correlation space-time model of the characterization parameters such as the undulation slope of the coal-rock interface and the change of the radiation field intensity is established, and the identification characteristic parameters of the morphological change of the coal-rock interface are determined. A method for inverting the radiation intensity into the coal-rock interface is established, and the final coal-rock simulation interface is formed by continuously and continuously predicting the undulation slope of the next section of the coal-rock interface.

[0031] Second, the inversion mathematical model of the coal-rock interface based on the radiation field characteristic values ​​established by the present invention can intelligently analyze the undulating characteristics of the coal-rock interface, realize dynamic tracking of the coal-rock interface situation, and form an intelligent recognition method of the coal-rock interface morphology based on natural gamma rays.

[0032] Third, the present invention realizes the identification of the coal-rock interface of the fully mechanized mining face, which can be used to guide the intelligent coal cutting of the coal mining machine, which is of great significance to the intelligentization of the coal mining machine and the safe and efficient production of coal mines. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the undulating slope of the coal-rock interface of the present invention;

[0034] Figure 2 It is a distribution diagram of the coal-rock interface and the simulated interface of the present invention;

[0035] Figure 3 It is a schematic diagram of the location of sensitive areas of the intelligent coal mining machine of the present invention. DETAILED DESCRIPTION

[0036] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0037] The coal-rock interface mainly includes the natural coal-rock interface (i.e. the coal seam and the direct roof in direct contact with it) and the faults caused by the later crustal movement. According to the survey, in most cases, the distribution of the coal-rock interface has the characteristics of gentle changes and nonlinear surface. According to the distribution characteristics of the coal-rock interface, it is necessary to find its characterization parameters to describe the coal-rock interface.

[0038] First, the characterization parameters should be easy to obtain by monitoring the intensity of the natural gamma-ray radiation field.

[0039] Secondly, the characterization parameters should be concise, and the description of the coal-rock interface needs to be simple and clear.

[0040] Based on this, the present invention chooses to use the coal-rock interface undulation slope to describe the characterization of the coal-rock interface. Figure 1 The simulation interface shown is formed by several straight lines. The length of each straight line is a detection range. The detection range requirement is determined according to the measurement accuracy achieved. The smaller the detection range, the higher the measurement accuracy, and vice versa.

[0041] The present invention defines the undulating slope of the coal-rock interface as follows: the slope of a number of line segments into which the coal-rock interface is divided under the simulated interface. Obviously, a gamma-ray detector needs to be installed under the coal-rock interface, and the gamma-ray detector can detect the intensity of the natural gamma-ray radiation field in real time, and the undulating slope of the coal-rock interface can be measured according to the intensity of the natural gamma-ray radiation received by the gamma-ray detector.

[0042] The undulation slope of the coal-rock interface can be positive or negative, such as Figure 1 If the horizontal height of point B is higher than that of point A, the ups and downs slope between points AB is positive. On the contrary, the ups and downs slope between points DE is negative. In addition to positive and negative, the ups and downs slope can also be large or small. Figure 1 The horizontal height difference between point B and point A is greater than the horizontal height difference between point C and point B, and their detection ranges are the same, so the slope between points AB is greater because it is steeper. Similarly, between points DE and EF, it is obvious that the ups and downs slope between DE is greater (their ups and downs slopes are all negative).

[0043] A method for simulating and identifying the coal-rock interface of a fully mechanized mining working face of the present invention comprises the following steps:

[0044] Step 1: Construct an inversion model of the coal-rock interface based on the radiation field characteristic value. Preferably, at point X i The radiation intensity detected at is J i , construct J i The calculation model is:

[0045]

[0046] Since the angle of the coal-rock interface is greater than 70° or even 80° in most cases, To perform the analysis:

[0047] In the above formula:

[0048] (1) Φ(x) is the ratio of e -x A function that decreases faster;

[0049] (2) The value of is usually less than 0.25. The value of is usually greater than 4;

[0050] (3) Generally speaking The value of is 1 / 30 of the value of Φ(μ(τw+Δh));

[0051] (4) The absolute value of is generally 1 / 25 of Φ(μ(τw+Δh))-Φ(μ(τw+Δh)+kl), and then multiplied by This coefficient, In most cases, it is 1 / 100 of Φ(μ(τw+Δh))-Φ(μ(τw+Δh)+kl);

[0052] (5) In engineering practice and on-site testing, Ignore.

[0053] Therefore, assuming μ(τw+Δh)=x, the inversion model of the coal-rock interface is constructed as follows:

[0054]

[0055] Where K′ is the proportionality coefficient (this is a consideration of radiation detection efficiency. Different γ-ray detectors have different efficiencies, and the same γ-ray detector is a constant under the same geological conditions. The value of K′ will change under different geological conditions and needs to be measured), q is the concentration of radioactive substances in rocks, ρ is the density of gangue, k is the attenuation coefficient of radioactive γ-rays in rocks, and Φ(x) is the ratio e -x The Jin Ge function with a faster decrease, μ is the attenuation coefficient of the radioactive material gamma ray in the coal seam, τ is the i The slope of the next coal-rock interface is predicted at the location, w is the actual slope of the coal-rock interface, Δh is the thickness of a thin coal seam left between the predicted simulated interface and the actual coal-rock interface, is the maximum angle that the gamma-ray detector can detect, and l is the thickness of the direct top.

[0056] Step 2: When the coal seam thickness h=0, the radiation intensity measured by the gamma-ray detector at point P in the rock layer is J0, which is brought into the inversion model of the coal-rock interface to calculate the relevant parameter values.

[0057] Preferably, in step 2, when the coal seam thickness h=0, then x=0, Substitute into the calculation to get The value of .

[0058] Step 3: Set the horizontal span Δ, set i = 1, and use X i Point is the detection starting point and its corresponding radiation intensity is J i Preferably, the horizontal span Δ is the horizontal distance traveled by the intelligent coal mining machine in 0.1 seconds.

[0059] Step 4: Set the radiation intensity J i The coal-rock interface inversion model is brought into the calculation to predict the next section of the coal-rock interface fluctuation slope τ.

[0060] Step 5: According to the current detection point X i The next detection point X is determined by the position, predicted coal-rock interface undulation slope τ and horizontal span Δ i+1Location.

[0061] Step 6: Determine whether the simulation is finished:

[0062] If the simulation is not over, then i+1, the next detection point determined in step 5 is detected and its corresponding radiation intensity J is detected. i , and go to step 4;

[0063] When the simulation is finished, all detection points are connected in sequence with straight lines and output as the simulation interface.

[0064] by Figure 2 For example, point A is the detection starting point. The position of the next detection point B is determined based on the undulation slope of the coal-rock interface and the horizontal span Δ obtained by the inversion model. The position of the next detection point C is determined based on point B, and so on until the end of the simulation. The detection points are then connected in sequence with straight lines and output as the simulation interface.

[0065] Correspondingly, an intelligent coal mining machine includes a coal mining machine body, and the coal mining machine body adopts any of the above-mentioned coal-rock interface simulation identification methods for the comprehensive mining working face to identify the coal-rock interface and mine coal.

[0066] When the sensitive area meets the basic conditions, the closer it is to the coal mining machine drum, the more sensitive it is, and the more accurate the data obtained. Therefore, the present invention preferably sets the gamma-ray detector just above or in front of the coal mining machine drum (the drum is located at the end of the rocker arm, and the drum crushes and transports the gangue by rotating to speed up the mining progress of the coal mine) (the sensitive area is a relative position, which changes with the change of the drum position). Figure 3 shown.

[0067] The beneficial effects of the present invention are:

[0068] First, the present invention forms a characterization of the coal-rock interface by analyzing the characteristics of the coal-rock interface, and on this basis, provides a model formula for calculating the radiation value formed at a certain point on the working surface, and determines the parameters affecting the distribution of the radiation field. Then, through the inversion model, a cross-correlation space-time model of the characterization parameters such as the undulation slope of the coal-rock interface and the change of the radiation field intensity is established, and the identification characteristic parameters of the morphological change of the coal-rock interface are determined. A method for inverting the radiation intensity into the coal-rock interface is established, and the final coal-rock simulation interface is formed by continuously and continuously predicting the undulation slope of the next section of the coal-rock interface.

[0069] Second, the inversion mathematical model of the coal-rock interface based on the radiation field characteristic values ​​established by the present invention can intelligently analyze the undulating characteristics of the coal-rock interface, realize dynamic tracking of the coal-rock interface situation, and form an intelligent recognition method of the coal-rock interface morphology based on natural gamma rays.

[0070] Third, the present invention realizes the identification of the coal-rock interface of the fully mechanized mining face, which can be used to guide the intelligent coal cutting of the coal mining machine, which is of great significance to the intelligentization of the coal mining machine and the safe and efficient production of coal mines.

[0071] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for simulating and identifying the coal-rock interface in a fully mechanized mining face, characterized in that: The steps include: Step 1: construct an inversion model of the coal-rock interface based on the characteristic value of the radiation field; Step 2: When the coal seam thickness h=0, the radiation intensity measured by the gamma-ray detector at point P in the rock layer is J0, which is brought into the inversion model of the coal-rock interface to calculate the relevant parameter values; Step 3: Set the horizontal span Δ, set i = 1, and use X i Point is the detection starting point and its corresponding radiation intensity is J i ; Step 4: Set the radiation intensity J i Bring it into the inversion model of coal-rock interface to calculate the slope τ of the coal-rock interface fluctuation in the next section; Step 5: According to the current detection point X i The next detection point X is determined by the position, predicted coal-rock interface undulation slope τ and horizontal span Δ i+1 Location; Step 6: Determine whether the simulation is finished: If the simulation is not finished, then i+1, the next detection point determined in step 5 is detected and its corresponding radiation intensity J is detected. i , and go to step 4; When the simulation is finished, all detection points are connected in sequence with straight lines and output as the simulation interface.

2. The method for simulating and identifying the coal-rock interface of a fully mechanized mining face according to claim 1 is characterized in that: At point X i The radiation intensity detected at is J i , construct J i The calculation model is: Assuming μ(τw+Δh)=x, the inversion model of coal-rock interface is constructed as follows: In the formula, K' is the proportionality coefficient, q is the concentration of radioactive substances in rocks, ρ is the density of gangue, k is the attenuation coefficient of γ-rays of radioactive substances in rocks, and Φ(x) is the ratio e -x The Jin Ge function with a faster decrease, μ is the attenuation coefficient of the radioactive material gamma ray in the coal seam, τ is the i The slope of the next coal-rock interface is predicted at the location, w is the actual slope of the coal-rock interface, Δh is the thickness of a thin coal seam left between the predicted simulated interface and the actual coal-rock interface, is the maximum angle that the gamma-ray detector can detect, and l is the thickness of the direct top.

3. A method for simulating and identifying the coal-rock interface of a fully mechanized mining face according to claim 2, characterized in that: In step 2, when the coal seam thickness h = 0, then x = 0, Substitute into the calculation to get The value of .

4. The method for simulating and identifying the coal-rock interface of a fully mechanized mining face according to claim 1 is characterized in that: The horizontal span Δ is the horizontal distance that the intelligent coal mining machine travels in 0.1 seconds.

5. An intelligent coal mining machine, comprising a coal mining machine body, characterized in that: The coal mining machine body adopts the coal-rock interface simulation identification method of the comprehensive mining working face described in any one of claims 1-4 to identify the coal-rock interface and mine coal.

6. The intelligent coal mining machine according to claim 5, characterized in that: The gamma-ray detector is arranged just above or in front of the coal mining machine drum.

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