A method for inversion of rock movement parameters in waterlogged subsidence basins

Abstract

The present invention proposes an unconventional rock movement data acquisition and parameter inversion method, which uses UAV LiDAR and small unmanned boats to obtain subsidence data and calculate the deformation parameters of the subsidence and waterlogging area, and uses the probability integral method to predict the subsidence. The elevation information closer to the real ground can not only provide high-resolution and high-precision topographic images, but also penetrate the ground vegetation through multiple echo technology, use filtering algorithms to effectively remove the surface vegetation, and obtain the real ground elevation data information.

Description

Technical Field

[0001] The invention belongs to the field of rock movement deformation monitoring, and in particular relates to a method for unconventional rock movement data acquisition and parameter inversion. Background Art

[0002] As people pay more and more attention to mining safety, deformation monitoring in mining areas has become a hot issue. Each mining area has purposefully carried out on-site monitoring of surface movement, law summary, and estimated parameter calculation to solve the mining subsidence and "three-down" coal mining problems in the mining area. Rock movement parameters are indispensable as the core data in mining area deformation monitoring, and they are the top priority for predicting deformation. For new mining areas, it is relatively easy to invert rock movement parameters by obtaining real-time monitoring data and initial data, while some old mining areas have already formed subsidence basins and lack initial data, resulting in data acquisition and parameter inversion becoming two important problems.

[0003] Nowadays, the data method for obtaining and calculating rock displacement parameters is mainly based on leveling technology and GPS measurement technology to establish trend and dip observation lines, and INSAR technology is used as an auxiliary mode. This mode is relatively mature and is widely used in deformation monitoring in major mining areas. However, contact measurement technologies such as leveling technology and GPS measurement technology are limited by terrain, objects, environment and other conditions. Looking at the data, because the area is too large, it is impossible to cover everything, resulting in discrete data, and the deformation characteristics of space are difficult to be expressed. Airborne LiDAR technology is a technology that has emerged in recent years. The density of the data it obtains is high, which helps to reflect the real ground elevation model, and can effectively overcome the influence of vegetation, buildings and other objects, and then obtain elevation information closer to the real ground. It can not only provide high-resolution and high-precision terrain images, but also penetrate the ground vegetation through multiple echo technology, and use filtering algorithms to effectively remove the surface vegetation to obtain the real ground elevation data information. Moreover, this area data acquisition mode is relatively flexible and can be equipped with different vehicles such as drones, unmanned boats and cars, etc. In complex terrain, data fitting can also be performed to replace missing data. With the data, parameter inversion is the next important issue. In recent years, algorithms such as the probability integral method have become more and more mature in parameter inversion, and the combination of multiple models has made the inverted parameters more and more accurate. There are even more accurate probability integral methods such as wolf pack algorithm, genetic algorithm, quantum particle swarm algorithm and swarm intelligence optimization algorithm. Summary of the invention

[0004] In view of the problem that initial data cannot be obtained due to mining subsidence and a large amount of water is accumulated in the subsidence basin, the present invention proposes an unconventional method for obtaining rock movement data and inverting parameters. The subsidence data is obtained by using UAV LiDAR and a small unmanned boat, and the deformation parameters of the subsidence and water accumulation area are calculated, and the probability integral method is used to predict the settlement.

[0005] A method for inverting rock movement parameters in a waterlogged subsidence basin comprises the following steps:

[0006] Step 1: Perform UAV LiDAR measurement to obtain point cloud data of the subsidence and waterlogging area and its surroundings, and obtain standard ground point cloud through point cloud solution, point cloud filtering, coordinate conversion and other steps. The subsidence and waterlogging area cannot reflect laser, resulting in the inability to obtain point cloud data. The point cloud of the waterlogging area is filled by interpolation fitting method to generate a DEM model.

[0007] Step 2: Use a small intelligent unmanned boat to perform underwater RTK measurement, obtain underwater three-dimensional coordinate data with a certain point density, measure the water depth, and interpolate the obtained three-dimensional coordinates to generate an underwater DEM model.

[0008] Step 3: Calculate and analyze the subsidence deformation, inclination deformation and curvature deformation based on the known mining data, various known parameters and measured data of the mining area, and obtain the surface subsidence, surface inclination and surface curvature respectively.

[0009] Step 4: Based on the probability integral method, the subsidence coefficient q, the main influencing tangent angle tgβ, the inflection point offset s and the mining influence propagation coefficient k are inverted to predict the future subsidence.

[0010] Advantages of the present invention:

[0011] This patent aims to solve the problem that the initial ground data cannot be obtained in the subsidence basin. According to the local geomorphic features, it can be judged that the area is part of the grassland. The initial surface elevation is similar to the nearby non-sinking area. The UAV LiDAR technology is used to obtain nearby point cloud data. Since the subsidence area is flooded and the point cloud cannot be obtained, the interpolation fitting method is used to extend the terrain of the non-sinking area to restore and simulate the initial surface terrain. The terrain of the waterlogged subsidence area uses an unmanned boat to obtain underwater three-dimensional coordinates, which solves the problem of difficulty in obtaining underwater three-dimensional coordinates, and interpolates the coordinate points to generate an underwater elevation model. It is of great significance in the acquisition of surface subsidence rock movement parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of an orthophoto of a subsidence basin in a specific embodiment of the present invention;

[0013] Figure 2It is a schematic diagram of a digital elevation model after the LiDAR point cloud is extended in a specific implementation manner of the present invention.

[0014] Figure 3 This is the measurement result of the small unmanned boat in the specific implementation mode of the present invention. DETAILED DESCRIPTION

[0015] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0016] A method for inverting rock movement parameters in a waterlogged subsidence basin comprises the following steps:

[0017] Step 1: Carry out UAV LiDAR measurement. The survey area belongs to the plain area. The UAV LiDAR route is designed according to the orthophotos obtained in advance to obtain point cloud data of the subsidence and waterlogging area and its surroundings. The standard ground point cloud is obtained through point cloud solution, data denoising, point cloud filtering, manual judgment and coordinate conversion. The point cloud data of the dip observation line and the strike observation line are extracted according to the mining working face.

[0018] Step 2: Use a small intelligent unmanned boat to perform underwater RTK measurement, obtain underwater three-dimensional coordinate data with a certain point density, and measure the water depth, such as Figure 3 As shown, the obtained three-dimensional coordinates are interpolated to generate an underwater DEM model, and the corresponding underwater elevation is extracted according to the point cloud plane coordinates of the dip observation line and the strike observation line extracted in step 1, and then sorted out as the observation data of the dip observation line and the strike observation line after sinking.

[0019] Step 3: Calculate the parameters by using the step-by-step weighted iterative least squares surface fitting method. First, use the subsidence observation values ​​of the surface points to select weighted iterative fitting to calculate the subsidence coefficient q, the main influencing angle tangent tgβ, the main influencing propagation angle k, the inflection point offset s and other parameters.

[0020] Then, according to the principle of probability integration method, the subsidence value of any point on the surface caused by unit mining is calculated as shown in formula (1) to formula (4).

[0021]

[0022] W 0 =mqcosα (2)

[0023]

[0024]

[0025] In the formula: m is the average mining thickness of the working face; q is the subsidence coefficient; α is the inclination angle of the working face; tanβ is the tangent of the main influencing angle; H is the mining depth of the main section in the strike direction; H1 and H2 are the upper boundary mining depth and the lower boundary mining depth of the working face respectively; a1 and a3 are the strike length and the dip length of the mining working face respectively; z1 and z2 are the calculated strike length and the dip calculated length of the working face respectively.

[0026] Step 4: According to the formula of the subsidence value function of any point on any section, the observation data on the rock movement observation line is substituted into the formula, and the unknown parameters are calculated to obtain the subsidence value function of any point on the main section;

[0027] The details are as follows:

[0028] Substitute the x and y values ​​of the n monitoring points extracted on the rock movement observation line into the sinking value formula of any point on any section to obtain n polynomials to form a system of equations. i ,y i Unknown parameter values ​​are obtained, thus obtaining the functional formula for the subsidence value of any point on the main section.

[0029] Step 5: Select the time influence function and construct the sinking value function of the points on the sinking area at any time. First, select the time influence function f(t), and then construct the sinking value function formula of the points on the sinking area at any time, that is:

[0030]

[0031]

[0032] In the formula, t i is the time interval between the estimated time and the unit mining time, g is the sinking velocity coefficient, r i is the main influence radius at the center point.

Claims

1. A method for inversion of rock movement parameters in a waterlogged subsidence basin, characterized by: The following steps are involved: Step 1: Carry out UAV LiDAR measurement. The survey area belongs to the plain area. The UAV LiDAR route is designed according to the orthophotos obtained in advance to obtain the point cloud data of the subsidence area and its surroundings. The standard ground point cloud is obtained through point cloud solution, data noise reduction, point cloud filtering, manual judgment and coordinate conversion. The point cloud data of the dip observation line and the strike observation line are extracted according to the mining working face; Step 2: Use a small intelligent unmanned boat to perform underwater RTK measurement, obtain underwater three-dimensional coordinate data with a certain point density, and measure the water depth. Interpolate the obtained three-dimensional coordinates to generate an underwater DEM model. According to the point cloud plane coordinates of the inclination observation line and the strike observation line extracted in step 1, extract the corresponding underwater elevation, and organize them as observation data of the inclination observation line and the strike observation line after sinking; Step 3: Parameters are obtained by using the step-by-step weighted iterative least square surface fitting method. First, the weighted iterative fitting is performed using the subsidence observation values ​​of the surface points to obtain the subsidence coefficient q, the main influencing angle tangent tgβ, the main influencing propagation angle k, and the inflection point offset s; Then, according to the principle of probability integration method, the subsidence value of any point on the surface caused by unit mining is calculated as shown in formula (1) to formula (4): IN 0 =mqcosα (2) Where: m is the average mining thickness of the working face; q is the sinking coefficient; α is the inclination angle of the working face; tanβ is the tangent of the main influencing angle; H is the mining depth of the main section in the strike direction; H1 and H2 are the upper boundary mining depth and the lower boundary mining depth of the working face respectively; z1 and z2 are the calculated length of the strike direction and the calculated length of the inclination of the working face respectively; Step 4: According to the formula of the subsidence value function of any point on any section, the observation data on the rock movement observation line is substituted into the formula, and the unknown parameters are calculated to obtain the subsidence value function of any point on the main section; The details are as follows: Substitute the x and y values ​​of the n monitoring points extracted on the rock movement observation line into the sinking value formula of any point on any section to obtain n polynomials to form a system of equations. i ,y i Unknown parameter values, thus obtaining the functional formula of the subsidence value at any point on the main section; Step 5: Select the time influence function and construct the sinking value function of the points on the sinking area at any time. First, select the time influence function f(t), and then construct the sinking value function formula of the points on the sinking area at any time, that is: Where, t i is the time interval between the estimated time and the unit mining time, g is the sinking velocity coefficient, r i is the main influence radius at the center point.

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