Fire source position and intensity inversion method based on spring oscillator motion

Abstract

The invention discloses a fire source position and intensity inversion method based on spring oscillator motion, and the method comprises the steps: obtaining n judgment points in a fire source environment, generating a three-dimensional grid according to the parameters of the judgment points, randomly selecting a fire source point in the three-dimensional grid, and employing a finite difference method or a finite volume method, discretizing the heat conduction differential equation corresponding to the fire source point to complete forward modeling; obtaining forward modeling results of n judgment points in the three-dimensional grid, and comparing the forward modeling results with the actual temperatures of the n judgment points; when a first difference value exists between the forward modeling result and the actual temperature, parameters of the randomly selected fire source points are adjusted according to the first difference values of the n judgment points and the influence of the fire source points of the n judgment points; and performing forward modeling on the adjusted fire source point again, and when the forward modeling reaches a stop condition, acquiring the parameters of the fire source point at the moment as the parameters of the real fire source point. According to the method, the number of forward modeling times needing to be repeated is small, efficiency can be improved, and positioning of a fire source point is more accurate.

Description

Technical Field

[0001] The invention relates to a calculation method for locating the source of underground coal mine fire or coal field fire, and in particular to a coal fire position and intensity inversion method based on spring oscillator motion. Background Art

[0002] For example, the Chinese patent with the publication number CN114818505B discloses a method for predicting the temperature distribution of steel billets in a heating furnace based on a particle swarm optimization algorithm. It is a typical method for solving the inverse problem of heat conduction. By establishing a one-dimensional non-steady-state heat conduction differential equation for representing the temperature distribution model of steel billets in a heating furnace, and determining its initial conditions and boundary conditions; replacing the particle values ​​in the particle swarm optimization algorithm with random initial values ​​of the boundary conditions, solving the one-dimensional non-steady-state heat conduction differential equation to obtain the solved temperature value; using the mean square error between the solved temperature value and the temperature measurement value as the objective function of the inverse problem of heat conduction, and returning the mean square error as the fitness value to the particle swarm optimization algorithm, inverting the boundary conditions in chronological order, and updating the boundary conditions based on the inversion; using the updated boundary conditions to calculate the heat conduction forward problem, and outputting the temperature value at the specified time and the specified position. This method can only be used for one-dimensional inverse problems of heat conduction, and each iteration requires a forward process of the number of particles.

[0003] The Chinese patent with the publication number CN113946963A discloses a method for inverting the location of the fire source in the coal mine goaf based on optical fiber temperature measurement. It is a typical inverse problem of coal mine fire source search. Based on the two-dimensional mathematical model of heat transfer of the point ignition source in the goaf, the analytical expression of the temperature field in the goaf is derived; the area in the goaf is divided into grids, and the two-dimensional coordinates corresponding to the position of the optical fiber measurement point are determined; the nodes on the grid are respectively used as heat source points, and the node coordinates are brought into the temperature field analytical function to obtain different temperature analytical values ​​of the same point under different heat source coordinates; the least squares model is used to minimize the difference between the analytical value and the measured value of the temperature measurement point to locate the fire source area. This method is only applicable to the calculation of two-dimensional goafs, and a forward modeling process is required for each node.

[0004] In the related technology, when searching for the source of coal fire, the intelligent optimization algorithm is mainly used to optimize the fire source location and obtain the fire source location and intensity with the highest probability. However, when using the swarm optimization algorithm, each iteration requires "particle swarm number" forward modeling or forward modeling for "each node". The number of forward modeling times is large, the calculation process is complicated, and it is impossible to search for the three-dimensional fire source location through inversion, which is easy to fall into the local optimal solution. Summary of the invention

[0005] In view of the above analysis, the present invention aims to provide a fire source position and intensity inversion method based on spring oscillator motion, so as to solve the problems that the existing coal fire source finding method is easy to fall into the local optimal solution and the calculation process is complicated and inefficient.

[0006] In order to solve the above technical problems, in an embodiment of the present invention, a method for inverting the position and intensity of a fire source based on the motion of a spring oscillator is provided, comprising the following steps: obtaining n judgment points in a fire source environment and generating a three-dimensional grid according to the parameters of the judgment points, wherein n is an integer ≥ 1; randomly selecting a fire source point in the three-dimensional grid and using a finite difference method or a finite volume method to discretize the heat conduction differential equation corresponding to the fire source point to complete a forward simulation; obtaining the sum of the difference between the forward modeling results of the n judgment points in the three-dimensional grid and the actual temperatures of the n judgment points as a first difference; when the first difference is greater than a preset threshold, adjusting the parameters of the randomly selected fire source point respectively according to the temperature values ​​of the n judgment points and the temperature gradient affected by the distance between the judgment point and the fire source point and the fire development time; re-forward modeling the adjusted fire source point, and when the forward simulation reaches the stop condition, obtaining the parameters of the fire source point at this time as the parameters of the real fire source point.

[0007] In addition, adjusting the parameters of the randomly selected fire source points respectively includes: adjusting the temperature value of the fire source point and / or the position coordinates of the fire source point in the three-dimensional grid.

[0008] In addition, the temperature value of the fire source point is adjusted specifically through the following formula:

[0009]

[0010] Among them, T′ o is the adjusted temperature; T o is the temperature before adjustment; k T is the temperature adjustment factor; is the temperature of the i-th judgment point; is the predicted temperature at the coordinates of the i-th judgment point.

[0011] In addition, the position coordinates of the fire source point in the three-dimensional grid are adjusted specifically by the following formula:

[0012]

[0013] Among them, x', y', and z' are the adjusted three-axis coordinates. is the position adjustment coefficient of the i-th judgment point coordinate; k dx , k dy , k dz are the damping coefficients in the x, y, and z directions, respectively, is the temperature of the i-th judgment point; is the predicted temperature at the coordinates of the i-th judgment point; The x, y, and z coordinates of the fire source point before adjustment; are the x, y, and z coordinates of the ith judgment point respectively.

[0014] In addition, the discretized equation in the finite difference method is as follows:

[0015]

[0016] Among them, α is the thermal resistance at the location of the fire source, Δt is the step size of the time difference of the fire source development, Δx, Δy, Δz are the distance difference steps in the x, y, and z directions respectively; T is the temperature; the subscripts m, j, and k represent the differential coordinates in the x, y, and z directions respectively, and the superscript l represents the time.

[0017] In addition, the parameters for obtaining n judgment points in the fire source environment include:

[0018] Through the drilling temperature measurement method, the temperature and location of n judgment points are obtained;

[0019] The thermal rate, specific heat capacity and density of coal samples at the borehole and the surrounding strata are obtained through experiments.

[0020] In addition, the stop conditions include:

[0021] The first difference between the forward modeling result and the actual temperature is within a preset range, or the parameters corresponding to the adjusted fire source point converge.

[0022] Compared with the prior art, the present invention has the following significant effects:

[0023] 1. The coal fire source finding calculation method provided by the present invention takes each judgment point as "each spring", the fire source point as "the pulled object", and uses the difference in temperature between the forward modeling result and the actual judgment point as "the force magnitude and direction of each spring" to simulate the spring adjustment process, so that the "pulled object" can be moved from an unstable position to a stable position, thereby quickly calculating the position and size of the fire source point. The forward modeling time is short, and the number of repeated forward modeling is small. After each adjustment of the fire source point, only one forward modeling is required, which significantly improves efficiency.

[0024] 2. The present invention also performs fire source point inversion and source search in a pre-established three-dimensional grid, and can obtain the three-dimensional position information of the fire source point, making the positioning of the fire source point more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of a method for inverting the position and intensity of a fire source based on the motion of a spring oscillator of the present invention;

[0026] Figure 2 This is a forward modeling result diagram obtained by using the MATLAB platform and theoretical calculations according to one embodiment of the present invention;

[0027] Figure 3 This is a schematic diagram of the iteration results of Example 1 of an implementation manner of the present invention;

[0028] Figure 4 This is a schematic diagram of the iterative results of Example 2 of an implementation manner of the present invention. DETAILED DESCRIPTION

[0029] To make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. However, it will be appreciated by those skilled in the art that in the embodiments of the present invention, many technical details are proposed in order to enable the reader to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present application can be implemented. The division of the following embodiments is for the convenience of description, and should not constitute any limitation on the specific implementation of the present invention. The various embodiments can be combined and referenced with each other without contradiction.

[0030] An embodiment of the present invention relates to a method for inverting the position and intensity of a fire source based on the motion of a spring oscillator, which can be applied to a computing tool such as a computer. The embodiment of the present invention obtains n judgment points in a fire source environment and generates a three-dimensional grid according to the parameters of the judgment points, wherein n is an integer ≥ 1; randomly selects a fire source point in the three-dimensional grid and uses a finite difference method or a finite volume method to discretize the heat conduction differential equation corresponding to the fire source point to complete a forward simulation; obtains the sum of the difference between the forward modeling results of the n judgment points in the three-dimensional grid and the actual temperature of the n judgment points as the first difference; when there is a first difference between the forward modeling result and the actual temperature, the parameters of the randomly selected fire source point are adjusted respectively according to the temperature values ​​of the n judgment points and the temperature gradient affected by the distance between the judgment point and the fire source point and the fire development time; forward simulation is performed again on the adjusted fire source point, and when the forward simulation reaches the stop condition, the parameters of the fire source point at this time are obtained as the parameters of the real fire source point. By taking each judgment point as "each spring", the fire source point as "the pulled object", and using the temperature difference between the forward modeling result and the actual judgment point as "the force magnitude and direction of each spring", the spring adjustment process is simulated to make the "pulled object" reach stability from an unstable position, so as to quickly calculate the position and size of the fire source point. The forward modeling time is short, and the number of repeated forward modeling is small. After each adjustment of the fire source point, only one forward modeling is required, which significantly improves efficiency. The fire source point inversion and source search in the pre-established three-dimensional grid can obtain the three-dimensional position information of the fire source point, and the positioning of the fire source point is more accurate. The following is a specific description of the implementation details of the fire source position and intensity inversion method based on the spring oscillator motion of an embodiment of the present invention. The following content is only the implementation details provided for the convenience of understanding and is not necessary for the implementation of this solution.

[0031] In this embodiment, if Figure 1 As shown in step 101, n judgment points in the fire source environment are obtained and a three-dimensional grid is generated according to the parameters of the judgment points, where n is an integer ≥1.

[0032] Specifically, the parameters of the judgment point in the fire source environment can be obtained by measuring the temperature of the judgment point through the borehole temperature measurement, and the position of the judgment point can be obtained through the borehole position; in addition, the thermal conductivity, specific heat capacity, and density of the coal sample obtained by the borehole and the surrounding strata can be obtained through the steady-state plate method experiment. In this embodiment, 10 judgment points are selected, and n=10 at this time. It should be noted that the selection of judgment points can be formulated according to different selection criteria for different fire source environments, and the number and method of selecting judgment points are not limited here.

[0033] When generating a three-dimensional grid, a three-dimensional grid is generated according to the minimum temperature of the judgment point measured by drilling and the measured relative position, and the distance between the three-dimensional grids and the calculation step length are determined; the position of the judgment point in the grid, i.e., the coordinates of the judgment point, is obtained.

[0034] In step 102, a fire source point is randomly selected in the three-dimensional grid and a finite difference method or a finite volume method is used to discretize the heat conduction differential equation corresponding to the fire source point to complete the forward simulation.

[0035] Specifically, in this embodiment, the discretization of the heat conduction differential equation is implemented based on the MATLAB platform. When the finite difference method is used to discretize the three-dimensional non-steady-state heat conduction differential equation, the initial conditions are set as the position of the randomly selected fire source point and the temperature set at the fire source point. The remaining grid points are 2°C lower than the minimum temperature in the drilling measurement, and the boundary conditions of the grid are set as adiabatic conditions. The finite difference method is then used to discretize the three-dimensional non-steady-state heat conduction differential equation.

[0036] In addition, before discretizing the heat conduction differential equation, we must first understand the distribution characteristics of coal fire development and its theoretical basis, including the following:

[0037] Solve the unsteady three-dimensional heat conduction differential equation:

[0038]

[0039] Among them, T is temperature, t is the fire development time, x, y, z represent the directions of three dimensions, S is the heat source intensity, λ is the thermal conductivity, ρ is the density, c is the specific heat capacity, is the partial differential symbol.

[0040] For the single point (i.e. judgment point) source search problem, the Cartesian coordinate system is transformed into a spherical coordinate system for solution. After the coordinate system transformation, the result is as follows:

[0041]

[0042] in:

[0043]

[0044] Among them, r, γ, and ω are the three parameters of spherical coordinates, and the transformation of the original Cartesian coordinates is as above. It is particularly noted that r is the distance from the judgment point to the origin (i.e., the fire source point); according to the symmetry of homogeneous heat conduction, it can be known that T = f(r), that is, γ is the polar angle, which represents the angle between the point and the z-axis; is the azimuth, which describes the angle between the projection of a point on the xy plane and the x-axis.

[0045] Then the heat conduction differential equation in the spherical coordinate system can be simplified to:

[0046]

[0047] In order to find the temperature field distribution and propagation law of the heat transfer process of the fire source, it is assumed that the physical parameters of the surrounding heat transfer medium are uniform and stable, and the thermal conductivity coefficient is introduced. Then formula (3) can be transformed into:

[0048]

[0049] Using the similarity method, the heat conduction range is proportional to (gradually increasing heat penetration depth), assuming To find the temperature, we can express it as Combining the differential equation of spherical coordinates and transforming the differential terms in the above formula, the result is as follows:

[0050]

[0051] Among them, T0 is the temperature of the fire source, T ∞ is the temperature at infinity, η has no actual physical meaning and is obtained by mathematical calculation, θ has no actual physical meaning and is required for mathematical transformation; substitute it into the solution and get:

[0052]

[0053] make but φ has no actual physical meaning and is obtained by mathematical transformation. By integrally solving the differential equation, the results are as follows:

[0054] lnφ=-η 2 -2 lnη+C1 (9)

[0055] or

[0056] but: Among them, C1 and C2 are unknown parameters, which have no actual physical meaning and are only used for mathematical calculations. By integrating equation (10), we can get:

[0057]

[0058] Transformation of initial conditions:

[0059]

[0060] By solving equation (11) and substituting into initial conditions (12) and (13), the expression of C2 is obtained as follows:

[0061]

[0062] It is easy to see that the right side of (14) contains non-integrable terms, and the Gaussian distribution is as follows:

[0063]

[0064] Where μ is the mean of the Gaussian distribution and σ is the standard deviation of the Gaussian distribution; let μ = 0, According to the symmetry of the Gaussian distribution function, the following integral function can be obtained:

[0065]

[0066] Among them, erf(η) is the error function, which has no numerical solution and can be found by looking up the table; look up the Gaussian distribution table, as shown in Table 1 below, and substitute the data to get C2;

[0067] Table 1 Gaussian distribution table

[0068] η erf(η) η erf(η) η erf(η) 0.05 0.0564 0.55 0.563 1.1 0.88 0.1 0.112 0.6 0.604 1.2 0.91 0.15 0.168 0.65 0.642 1.3 0.934 0.2 0.223 0.7 0.678 1.4 0.952 0.25 0.276 0.75 0.711 1.5 0.966 0.3 0.329 0.8 0.742 1.6 0.96 0.35 0.379 0.85 0.771 1.7 0.984 0.4 0.428 0.9 0.797 1.8 0.989 0.45 0.475 0.95 0.821 1.9 0.993 0.5 0.52 1 0.843 2 0.995

[0069] Substituting the results into equation (5) and equation (6), we can obtain the following relationship:

[0070]

[0071] The above formulas (17) and (18) show that the three-dimensional temperature field at different locations from the fire source has different temperature gradients and temperature values ​​that change with the development time of the fire source (that is, the temperature values ​​and temperature gradients of the n judgment points are determined by the distance between the judgment point and the fire source and the development time of the fire source). After the coordinate system is changed (spherical coordinates -> Cartesian coordinate system), the three-dimensional temperature field in the Cartesian coordinate system can be calculated.

[0072] Then the finite difference method is used to discretize the three-dimensional unsteady heat conduction differential equation. The discretized equation and related procedures are as follows:

[0073] Discrete equations:

[0074]

[0075] Among them, α is the thermal conductivity of the fire source, Δt is the step size of the fire source development time difference, Δx, Δy, Δz are the distance difference steps in the x, y, and z directions respectively; T is the temperature; the subscripts m, j, and k represent the differential coordinates in the x, y, and z directions respectively, and the superscript l represents the time.

[0076] Program commands:

[0077] Tc(i,j,k)=Tc(i,j,k)+rezu*dt*1 / dx^2*(Tc(i+1,j,k)+Tc(i-1,j,k)+Tc(i,j+1,k)+Tc(i,j-1,k)+Tc(i,j,k+1)+Tc(i,j,k-1)-6*Tc(i,j,k)); where rezu is a parameter related to thermal resistance.

[0078] In this embodiment, the temperature of the fire source, i.e., the center temperature, is set to 550°C, and the forward modeling is performed in the MATLAB platform to obtain the temperature results at different positions away from the fire source at time t as follows: Figure 2 As shown by the red line in the middle, the horizontal axis is the position / m from the fire source, and the vertical axis is the temperature / ℃. In addition, through the above explanation that the temperature field around the fire source has a temperature gradient that changes with the development time of the fire source and the derivation formula of the temperature value, the data is selected to draw the temperature results at different positions at the theoretical time t from the fire source, as shown in Figure 2 As shown by the black line in the figure, the horizontal axis is the distance from the fire source / m, and the vertical axis is the temperature / ℃. Figure 2 It can be seen that when the MATLAB program is used, the calculation results are consistent with the theoretical calculation results, and the MATLAB platform can be used for simulation. In addition, the present invention mainly proposes a calculation method for source finding. The accuracy of the forward modeling does not affect the accuracy of the method, but affects the accuracy of the results. By comparing the two sets of data, it is found that when the finite difference method is used for simulation, the change law and temperature distribution have a good fit with the actual data. Therefore, the discrete method is used for inversion, which has a certain verification significance for the coal fire source finding calculation method proposed in the present invention.

[0079] In this embodiment, according to the parameters determined in the above steps, the coordinates of the fire source point are set to (50, 40, 40), and the temperature of the fire source is 550° C. The coordinates of the 10 judgment points and the corresponding temperatures are shown in Table 2 below:

[0080] Table 2 Coordinates of judgment points and corresponding temperatures

[0081]

[0082]

[0083] First, import the coordinates in Table 2 into the data area and record them as Tpdw, and import the temperature value into the work area and record them as Tpd. The minimum temperature value and temperature coordinates are automatically screened out through the following program:

[0084] Tmin=Tpd(find(Tpd==min(Tpd),1,'first'));

[0085] aa=find(Tpd==min(Tpd),1,'first');

[0086] aa1=Tpdw(aa,1);

[0087] aa2=Tpdw(aa,2);

[0088] aa3=Tpdw(aa,3);

[0089] The coordinates of the minimum value are denoted as (aa1, aa2, aa3), and the temperature value is denoted as Tmin. The forward simulation is performed using the finite difference method program command described above.

[0090] In step 103, the sum of the differences between the forward modeling results of the n judgment points in the three-dimensional grid and the actual temperatures of the n judgment points is obtained as the first difference.

[0091] Specifically, according to the results of the preliminary forward modeling performed above, the error function Γ is set to be the first difference:

[0092]

[0093] in, is the temperature of the i-th judgment point; is the predicted temperature under the coordinates of the ith judgment point; when the first difference, that is, the value of the error function, is less than 0.5°C, the result is considered to be credible, that is, the position of the fire source, that is, the temperature, does not need to be adjusted. It should be noted that the 0.5°C set for the first difference in this embodiment is only a value selected for the experimental environment of this embodiment, and the first difference is not limited. The specific value of the first difference can be determined according to the actual situation of the project.

[0094] In step 104, when the first difference is greater than a preset threshold, the parameters of the randomly selected fire source points are adjusted according to the temperature values ​​of the n judgment points and the influence of the distance between the judgment point and the fire source point and the fire source development time on the temperature gradient.

[0095] Specifically, in this embodiment, when the value of the first difference is greater than 0.5°C, the temperature value of the fire source point and / or the position coordinates of the fire source point in the three-dimensional grid can be adjusted. When the temperature value of the fire source point is adjusted, it is specifically adjusted by the following formula:

[0096]

[0097] Among them, T′ o is the adjusted temperature; T o is the temperature before adjustment; k T is the temperature adjustment factor; is the temperature of the i-th judgment point; is the predicted temperature at the coordinates of the i-th judgment point. The program implemented in the MATLAB platform is as follows:

[0098] for i=1:10

[0099] T0=T0+kT*(Tpd(i)-Tc(ai1,ai2,ai3)); end

[0100] In this implementation, kT=7 is taken, and the value of KT can be selected according to the specific implementation scenario.

[0101] The position coordinates of the fire source point in the three-dimensional grid are adjusted specifically by the following formula:

[0102]

[0103] Among them, x', y', and z' are the adjusted three-axis coordinates. is the position adjustment coefficient of the i-th judgment point coordinate; k dx , k dy , k dz are the damping coefficients in the x, y, and z directions, respectively, is the temperature of the i-th judgment point; is the predicted temperature at the coordinates of the i-th judgment point; The x, y, and z coordinates of the fire source point before adjustment; are the x, y, and z coordinates of the ith judgment point respectively.

[0104] In this embodiment, the damping coefficient is selected as 0.25, and combined with the temperature field around the fire source, there is a temperature gradient and temperature value that changes with the development time of the fire source. The fire source position is adjusted to the tail method or the next method through the program to determine the fire source position. Part of the program is as follows (the loop statement and the selection structure are omitted):

[0105] kkz=kkz+abs(Tpd(i)-Tc(ai1,ai2,ai3));

[0106] kkk(i,1)=abs(Tpd(i)-Tc(ai1,ai2,ai3)) / kkz;

[0107] T0xx(i)=kkk(i,1)*(T0x-Tpdw(i,1)); else T0xx(i)=-kkk(i,1)*(T0x-Tpdw(i,1));

[0108] T0xyy=T0xyy+T0xx(i) / 4;

[0109] T0x=ceil(T0xyy); else T0x=fix(T0xyy);

[0110] Among them: kkz is kkk is T0xx is T0xyy is x′, T0x is the x coordinate after adjustment; the adjustment method of y and z coordinates is the same as that of x coordinate.

[0111] In step 105, the forward modeling is performed again on the adjusted fire source point, and when the forward modeling reaches the stop condition, the parameters of the fire source point at this time are obtained as the parameters of the real fire source point.

[0112] Specifically, the stop conditions include: a first difference between the forward modeling result and the actual temperature is within a preset range, which is less than 0.5° C. in this embodiment, or the parameters corresponding to the adjusted fire source point converge.

[0113] In this embodiment, two examples are given to observe the convergence speed when the forward simulation reaches the stop condition.

[0114] Example 1: The initial setting coordinates of the fire source are (40, 60, 50) and the temperature is 750℃; the diagram of the number of iterations is as follows: Figure 3 shown.

[0115] Example 2: The initial setting coordinates of the fire source are (60, 50, 30) and the temperature is 350℃; the diagram of the number of iterations is as follows: Figure 4 shown.

[0116] According to the above results, this method can find the source quickly and the results are accurate. From the two experiments, it can be seen that the setting of the initial value will not affect the final result, but it will affect the convergence speed, especially the setting of the initial temperature value. When the initial temperature value is set to a small value, the convergence speed is fast and the change is relatively stable. This is because when the temperature value is small, the temperature field obtained by the forward modeling result is generally small. According to the theoretical proof in the manual, at this time, in order to achieve the forward modeling end condition, the temperature gradient becomes smaller, so it is easier to adjust in the same direction; when the initial temperature value is large, when the forward modeling end condition is reached, the temperature gradient changes greatly, the errors of the temperatures of different judgment points differ greatly, and the randomness of the adjustment direction increases. Figure 3 and Figure 4 The reasons why the data converge to a smaller fluctuation range are as follows: (1) The forward model uses the finite difference method, which has certain errors and causes fluctuations in the calculation; (2) The damping coefficient is set too small. If the damping coefficient is too small, fluctuations will occur in the data convergence stage. If the damping coefficient is set too large, the convergence speed will slow down; (3) The three coordinates use the same rounding method, which will cause fluctuations around the correct solution.

[0117] Those skilled in the art will appreciate that the above-mentioned embodiments are specific examples for implementing the present invention, and in actual applications, various changes may be made thereto in form and detail without departing from the spirit and scope of the present invention.

Claims

1. A method for inverting the fire source position and intensity based on the motion of a spring oscillator, characterized in that: include: Obtain n judgment points in the fire source environment and generate a three-dimensional grid according to the parameters of the judgment points, where n is an integer ≥ 1; Randomly selecting a fire source point in the three-dimensional grid and using a finite difference method or a finite volume method to discretize the unsteady three-dimensional heat conduction differential equation corresponding to the fire source point to complete the forward simulation; Obtaining a sum of differences between the forward modeling results of the n judgment points in the three-dimensional grid and the actual temperatures of the n judgment points as a first difference; When the first difference is greater than a preset threshold, the parameters of the randomly selected fire source points are adjusted respectively according to the temperature values ​​of the n judgment points, the temperature gradients affected by the distances between the judgment points and the fire source point and the fire source development time; The adjusted fire source point is forward simulated again, and when the forward simulation reaches a stop condition, the parameters of the fire source point at this time are obtained as the parameters of the real fire source point.

2. The method for inverting the fire source position and intensity based on the spring oscillator motion according to claim 1 is characterized in that: The adjusting of the parameters of the randomly selected fire source points respectively comprises: The temperature value of the fire source point and / or the position coordinates of the fire source point in the three-dimensional grid are adjusted.

3. The method for inverting the fire source position and intensity based on the spring oscillator motion according to claim 2 is characterized in that: The temperature value of the fire source point is adjusted specifically by the following formula: Among them, T′ o is the adjusted temperature; T o is the temperature before adjustment; k T is the temperature adjustment factor; is the temperature of the i-th judgment point; is the predicted temperature at the coordinates of the i-th judgment point.

4. The method for inversion of fire source position and intensity based on spring oscillator motion according to claim 2, characterized in that: The position coordinates of the fire source point in the three-dimensional grid are adjusted specifically by the following formula: Among them, x', y', and z' are the adjusted three-axis coordinates. is the position adjustment coefficient of the i-th judgment point coordinate; k dx , k dy , k dz are the damping coefficients in the x, y, and z directions, respectively, is the temperature of the i-th judgment point; T ci is the predicted temperature at the coordinates of the i-th judgment point; The x, y, and z coordinates of the fire source point before adjustment; are the x, y, and z coordinates of the ith judgment point respectively.

5. The fire source position and intensity inversion method based on spring oscillator motion according to claim 1 is characterized in that: The discretized equation in the finite difference method is as follows: Among them, α is the thermal resistance at the location of the fire source, Δt is the step size of the time difference of the fire source development, Δx, Δy, Δz are the distance difference steps in the x, y, and z directions respectively; T is the temperature; the subscripts m, j, and k represent the differential coordinates in the x, y, and z directions respectively, and the superscript l represents the time.

6. The method for inverting the fire source position and intensity based on the spring oscillator motion according to claim 1, characterized in that: The parameters for obtaining n judgment points in the fire source environment include: Obtain the temperatures and locations of the n judgment points by means of a drilling temperature measurement method; The thermal conductivity, specific heat capacity and density of coal samples at the borehole and the surrounding strata are obtained through experiments.

7. The method for inversion of fire source position and intensity based on spring oscillator motion according to claim 1, characterized in that: The stop conditions include: A first difference between the forward modeling result and the actual temperature is within a preset range, or a parameter corresponding to the adjusted fire source point converges.

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