CN115907187A - Method for predicting development height of large mining height fully-mechanized caving water flowing fractured zone - Google Patents
Method for predicting development height of large mining height fully-mechanized caving water flowing fractured zone Download PDFInfo
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Abstract
The invention discloses a method for predicting the development height of a large mining height fully-mechanized caving water flowing fractured zone, which comprises the following steps: collecting development height data of the large mining height fully-mechanized caving mining water flowing fractured zone; predicting the development height value of the water flowing fractured zone by using an empirical formula; predicting the development height value of the water flowing fractured zone by using multivariate nonlinear regression; determining an optimal combination weight coefficient of an empirical formula and a multivariate nonlinear regression prediction method at each sample; and determining the combination weight, and predicting the development height of the roof water flowing fractured zone. The method integrates the advantages of the traditional prediction method and the multiple regression method, has high prediction precision, simple operation steps and convenient popularization, and can better serve the basic research and prevention and control work of the water damage of the high roof of the coal mining.
Description
Technical Field
The invention belongs to the field of mine water damage prevention and control, and particularly relates to a method for predicting development height of a large-mining-height fully-mechanized caving water flowing fractured zone.
Background
In the coal seam mining process, the roof overlying rocks of the mining working face can generate cracks to form a water-flowing crack zone. Once the water-flowing fractured zone is communicated with the overlying aquifer, water in the aquifer enters a working surface, a mine water inrush accident can happen underground, and underground safe mining is seriously threatened. Meanwhile, a series of ecological environment problems such as underground water level reduction and vegetation damage can be associated, and the economic sustainable development construction of the area is influenced. Therefore, the accurate prediction of the height of the water flowing fractured zone is the basis and the premise of safe coal mining design under the water body of the coal mine and the realization of water-retaining coal mining, and has great significance for safe coal mining and regional sustainable development.
The western coal resources are characterized by large reserves, excellent coal quality, shallow buried coal layers (generally 100-500 m), large mining thickness (about 10m of single-layer thickness) and the like, and a fully mechanized caving mining technology is mostly adopted. In recent years, with the large-scale development of western coal resources, roof water inrush accidents occur sometimes due to inaccurate height prediction of large mining height fully-mechanized caving water-flowing fractured zones, for example, 5-month-30-day 2011, the roof sand layer at 6lm is suddenly submerged by pushing and mining the S1210 surface of the south wing of the caragana mine, and the water inrush accidents occur, and the water quantity reaches 1200m after being stable 3 And h, causing the working surface to be flooded and production stop, and predicting that the water-flowing fractured zone of the working surface does not reach the overlying sand layer to dive by adopting a traditional empirical formula, but the actual water-flowing fractured zone reaches the overlying loose sand layer water. How to more accurately predict the height of the fully-mechanized caving water flowing fractured zone with the large mining height in the western mining area is a main problem in roof water hazard prevention and control and water retention coal mining in the western mining area. At present, a plurality of methods for predicting the development height of the water flowing fractured zone exist, wherein the most widely applied method is an empirical formula in the specification of building, water body, railway and main roadway coal pillar setting and coal pressing exploitation (the third lower specification), and then a multiple regression formula established based on the influence factors of the height of the water flowing fractured zone. In the two methods, a 'three-lower' standard empirical formula is obtained mainly based on fitting of measured height data of the water flowing fractured zone of the rock coal-two-stacked coal seam mining in the eastern mining area, and only the mining thickness is considered in the formula, so that the prediction accuracy of the height of the water flowing fractured zone of the large mining height fully-mechanized caving in the western mining area is not high. The multiple regression formula is influenced by factors such as the number of established samples and the condition difference among the samples, and the prediction precision of the multiple regression formula is uncertain.
Disclosure of Invention
In order to solve the problems, the invention provides a method for predicting the development height of the large-mining-height fully-mechanized caving water-flowing fractured zone, integrates the advantages of the traditional prediction method and the multiple regression method, has high prediction precision, simple operation steps and convenient popularization, and can better serve the basic research and prevention work of the water damage of the large-mining high roof of the coal mine.
In order to achieve the aim, the invention provides a method for predicting the development height of a large mining height fully-mechanized caving water flowing fractured zone, which comprises the following steps:
collecting development height data of the large mining height fully-mechanized caving mining water flowing fractured zone;
predicting a development height value A of the water flowing fractured zone by using an empirical formula based on the development height data of the water flowing fractured zone;
predicting a development height value B of the water flowing fractured zone by using multivariate nonlinear regression based on the development height data of the water flowing fractured zone;
determining an optimal combination weight coefficient of an empirical formula and a multivariate nonlinear regression prediction method at each water flowing fractured zone development height value sample;
and determining a combination weight based on the optimal combination weight coefficient, and predicting the development height of the roof water flowing fractured zone based on the combination weight.
Preferably, the water flowing fractured zone development height data comprises actual measurement data of the water flowing fractured zone development height under the condition of large mining height fully mechanized caving mining and influence factor data of the water flowing fractured zone development height;
the data of the high influence factors on the development of the water flowing fractured zone comprise: coal seam mining height, mining depth and mining face width.
Preferably, the empirical formula is:
wherein H f Estimating the height m for the water flowing fractured zone; and the sigma M is the accumulated thickness M of the mined coal bed.
Preferably, the method for predicting the development height value B of the water flowing fractured zone by using the multiple nonlinear regression comprises the following steps:
respectively determining the functional relationship among the mining height, the mining depth and the mining working face width of the coal bed and the measured value of the height of the water flowing fractured zone based on the development height data of the water flowing fractured zone;
and (3) obtaining a regression formula among the development height of the large-mining-height fully-mechanized caving mining water-flowing fractured zone, the mining thickness, the mining depth and the working face width by using SPSS software based on the functional relation, and predicting the development height value B of the water-flowing fractured zone of the sample by using the obtained regression formula.
Preferably, the principle of determining the optimal combined weight coefficient is to minimize a combined prediction error at a water flowing fractured zone development height value sample, and the method of minimizing an absolute value of the combined prediction error is adopted for solving.
Preferably, the combined prediction error is a difference between an actual value and a predicted value;
the model for solving the combined prediction error by adopting the method of the minimum absolute value of the combined prediction error is as follows:
wherein M is the number of sample data; y is t Combining the predicted errors for the t sample; e.g. of the type t The prediction error at the t sample for the variable weight combined prediction method; k it Weighting coefficients at the t-th sample for the ith prediction method; e.g. of the type it The prediction error of the ith prediction method at the t sample; n =1,2.
Preferably, the method for determining the combining weight includes: the method adopts the average value of the variable weight of the combination of the first M samples of the development height value of the water flowing fractured zone, and specifically comprises the following steps:
wherein M is the number of sample data; k i,j The combination weight coefficient of the ith prediction method at the jth prediction sample; k is it Weighting coefficients at the t-th sample for the ith prediction method; j =1,2.; i =1,2.
Preferably, the method for predicting the development height of the roof water flowing fractured zone comprises the following steps:
H j ＝K 1,j ·H 1,j +K 2,j ·H 2,j
wherein H j J =1,2, for the water-flowing fractured zone development height of the jth prediction sample; k is 1,j The combination weight coefficient of the empirical formula prediction method at the jth prediction sample; h 1,j Predicting the height value of the water flowing fractured zone of the jth prediction sample for an empirical formula; k 2,j The combined weight coefficient of the multiple nonlinear regression prediction method at the jth prediction sample is obtained; h 2,j And predicting the height value of the water flowing fractured zone of the jth prediction sample for the multivariate nonlinear regression.
Compared with the prior art, the invention has the following advantages and technical effects:
the invention provides a method for predicting the development height of a large-mining-height fully-mechanized caving water-flowing fractured zone, which collects relevant data of the height of the fully-mechanized caving mining water-flowing fractured zone; predicting the development height value of the water flowing fractured zone of the collected sample by using an empirical formula and multivariate regression; and determining the optimal combination weight coefficient of the empirical formula and the multivariate nonlinear regression prediction method at each sample to obtain the combination weight, and predicting the development height of the roof water flowing fractured zone. The invention combines two prediction methods which are most widely applied at present, comprehensively utilizes the advantages of various methods, overcomes the defects of the two methods, effectively improves the prediction precision of the development height of the water-flowing fractured zone of the large mining height fully-mechanized caving mining, and has important significance for preventing and controlling the water damage of the mine.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, are included to provide a further understanding of the application, and the description of the exemplary embodiments of the application are intended to be illustrative of the application and are not intended to limit the application. In the drawings:
fig. 1 is a flow chart of a method for predicting development height of a large mining height fully-mechanized caving water flowing fractured zone in the embodiment of the invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
Example one
As shown in fig. 1, the present embodiment provides a method for predicting the development height of a large mining height fully-mechanized caving water fractured zone, which specifically includes the following steps:
s1, collecting development height data of a large mining height fully-mechanized caving mining water flowing fractured zone;
the water flowing fractured zone development height data comprises water flowing fractured zone development height actual measurement data and water flowing fractured zone development height influence factor data under the fully mechanized caving mining condition, and the water flowing fractured zone development height influence factor data comprises the following data: coal seam mining height, mining depth and mining face width.
S2, based on the development height data of the water flowing fractured zone, predicting a development height value A of the water flowing fractured zone by using an empirical formula;
based on the collected sample data of the development height of the water flowing fractured zone, predicting the development height value A of the water flowing fractured zone of the sample by using an empirical formula in the Specification of coal pillar reservation and coal pressing exploitation of buildings, water bodies, railways and main roadways, wherein the calculation formula specifically comprises the following steps:
wherein H f Estimating the height m for the water flowing fractured zone; and the sigma M is the accumulated thickness M of the mined coal bed.
S3, predicting the development height value B of the water flowing fractured zone by using multivariate nonlinear regression based on the development height data of the water flowing fractured zone;
considering 3 factors of coal seam mining height, mining depth and mining working face width, and respectively determining the functional relation among the coal seam mining height, the mining depth, the mining working face width and the measured value of the height of the water flowing fractured zone based on the collected sample data of the mining height of the water flowing fractured zone; and then obtaining a regression formula among the fully-mechanized caving mining water flowing fractured zone development height, mining thickness, mining depth and working face width by using SPSS software, and predicting the water flowing fractured zone development height value B of the sample by using the obtained regression formula.
S4, determining an optimal combination weight coefficient of an empirical formula and a multivariate nonlinear regression prediction method at each water flowing fractured zone development height value sample;
the optimal combined weight coefficient is obtained by adopting a method of minimum absolute value of combined prediction error, and the model is as follows:
wherein M is the number of sample data; y is t Combining the predicted minimum error for the t sample; e.g. of a cylinder t The prediction error at the t sample for the variable weight combined prediction method; k it Weighting coefficients at the t-th sample for the ith prediction method; e.g. of the type it The prediction error of the ith prediction method at the t sample; n =1,2.
And S5, determining the combination weight based on the optimal combination weight coefficient, and predicting the development height of the roof water flowing fractured zone based on the combination weight.
Determining a combination weight coefficient at the position of the prediction sample, wherein the specific calculation adopts the following formula:
wherein M is the number of sample data; k i,j The combination weight coefficient of the ith prediction method at the jth prediction sample; k it Weighting coefficients at the t-th sample for the ith prediction method; j =1,2.; i =1,2.
And predicting the development height of the roof water flowing fractured zone according to the combined weight, wherein the specific calculation is as follows:
H j ＝K 1,j ·H 1,j +K 2,j ·H 2,j
wherein H j J =1,2, for the water-flowing fractured zone development height of the jth prediction sample; k is 1,j The combination weight coefficient of the empirical formula prediction method at the jth prediction sample; h 1,j Predicting the height value of the water flowing fractured zone of the jth prediction sample for an empirical formula; k 2,j The combined weight coefficient of the multiple nonlinear regression prediction method at the jth prediction sample is obtained; h 2,j And predicting the height value of the water flowing fractured zone of the jth prediction sample for the multivariate nonlinear regression.
In order to verify the technical effect, the method obtains the following table 1, which is a statistical table of measured values of the height of the water flowing fractured zone, according to the collected data of the measured values of the development height of the fully mechanized mining water flowing fractured zone, the mining height of the coal bed, the mining depth, the width of a mining working face and the like.
TABLE 1
The development heights of the water-flowing fractured zones of the collected 25 groups of samples were predicted by using an empirical formula and multivariate non-linear regression, and the following table 2 was obtained. The SPSS software is used for obtaining a regression formula among the development height, the mining thickness, the mining depth and the working face width of the fully mechanized caving mining water guide crack belt as follows:
y＝42.39e 0.08M -1.38×10 -4 S 2 +0.13S-2.87×10 -3 L 2 +1.54L-113.80
in the formula, M is the coal seam mining height M; s is the coal seam mining depth m; l is the width of the mining face, m.
TABLE 2
The optimal combined weight coefficient of each single prediction method at each sample is obtained by adopting the method of minimum absolute value of combined prediction error, and the following table 3 is obtained.
TABLE 3
The width of a fully mechanized caving mining working face of a certain mine is 300m, the mining thickness of a coal bed is 8.90m, and the mining depth is 251.20m. The empirical formula predicts that the development height of the water-conducting crack zone of the working surface is 55.37m, and the predicted value of the multiple nonlinear regression is 199.55m. Combining weight K 1,1 ＝0.10，K 2,1 ＝0.90。
Predicting the development height of the water-flowing fractured zone of the working surface of the target mine area by variable weight combination:
H 1 ＝K 1,1 ·H 1,1 +K 2,1 ·H 2,1 ＝0.1×55.37+0.9×199.55＝185.28
the variable weight combination is calculated to predict the development height of the water fractured zone to be 185.28m. In order to verify the accuracy of the method, the working face of the mine area is actually measured on site. And determining that the actual measurement value of the development height of the water-flowing fractured zone of the working surface of the mine area is 181.20m by observing the water pressure change measured by the osmometer and analyzing the strain distribution of the metal-based cable-shaped optical cable. The relative error of the results obtained by the two methods is 2.25%, the prediction precision is higher than that of the prediction of an empirical formula (the relative error is 69.45%) and a multivariate nonlinear regression (the relative error is 10.13%), and the accuracy and the applicability of the method are verified.
The above description is only for the preferred embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. A method for predicting the development height of a large mining height fully mechanized caving water flowing fractured zone is characterized by comprising the following steps of:
collecting development height data of the large mining height fully-mechanized caving mining water flowing fractured zone;
predicting a development height value A of the water flowing fractured zone by using an empirical formula based on the development height data of the water flowing fractured zone;
predicting a development height value B of the water flowing fractured zone by using multivariate nonlinear regression based on the development height data of the water flowing fractured zone;
determining an optimal combination weight coefficient at each water flowing fractured zone development height value sample;
and determining a combination weight based on the optimal combination weight coefficient, and predicting the development height of the roof water flowing fractured zone based on the combination weight.
2. The method for predicting the development height of the large-mining-height fully-mechanized caving water-flowing fractured zone according to claim 1, wherein the development height data of the water-flowing fractured zone comprises actual measurement data of the development height of the water-flowing fractured zone and development height influence factor data of the water-flowing fractured zone under the large-mining-height fully-mechanized caving mining condition;
the data of the high influence factors on the development of the water flowing fractured zone comprise: coal seam mining height, mining depth and mining face width.
3. The method for predicting the development height of the large mining height fully-mechanized caving water flowing fractured zone according to claim 1, wherein the empirical formula is as follows:
wherein H f Estimating the height m for the water flowing fractured zone; and sigma M is the accumulated thickness of the mined coal bed, M.
4. The method for predicting the development height of the large mining height fully mechanized caving water fractured zone according to claim 1, wherein the method for predicting the development height value B of the large mining height fully mechanized caving water fractured zone by using multivariate nonlinear regression comprises the following steps:
respectively determining the functional relationship among the mining height, the mining depth and the mining working face width of the coal bed and the measured value of the height of the water flowing fractured zone based on the development height data of the water flowing fractured zone;
and on the basis of the functional relation, obtaining a regression formula among the development height of the large mining height fully-mechanized caving mining water flowing fractured zone, the mining thickness, the mining depth and the working face width by using SPSS software, and predicting the development height value B of the water flowing fractured zone of the sample by using the obtained regression formula.
5. The method for predicting the development height of the large mining height fully mechanized caving water flowing fractured zone according to claim 1, wherein the principle of determining the optimal combined weight coefficient is to minimize a combined prediction error at a sample of the development height value of the water flowing fractured zone and obtain the minimum combined prediction error by using a method of minimizing an absolute value of the combined prediction error.
6. The method for predicting the development height of the large mining height fully-mechanized caving water flowing fractured zone according to claim 5, wherein the combined prediction error is the difference between an actual value and a predicted value;
the model for solving the combined prediction error by adopting the method for minimizing the absolute value of the combined prediction error is as follows:
wherein M is the number of sample data; y is t Combining the predicted errors for the t sample; e.g. of the type t The prediction error at the t sample for the variable weight combined prediction method; k is it Weighting coefficients at the t-th sample for the ith prediction method；e it The prediction error of the ith prediction method at the t sample; n =1,2.
7. The method for predicting the development height of the large mining height fully-mechanized caving water flowing fractured zone according to claim 1, wherein the method for determining the combination weight comprises the following steps: the method adopts the average value of variable weights of the first M water flowing fractured zone development height value samples in a combined mode, and specifically comprises the following steps:
wherein M is the number of sample data; k is i,j The combination weight coefficient of the ith prediction method at the jth prediction sample; k it Weighting coefficients at the t-th sample for the ith prediction method; j =1,2.; i =1,2.
8. The method for predicting the development height of the large mining height fully mechanized caving water flowing fractured zone according to claim 1, wherein the method for predicting the development height of the roof water flowing fractured zone is as follows:
H j ＝K 1，j ·H 1，j +K 2，j ·H 2，j
wherein H j J =1,2, for the development height of the water-flowing fissure zone of the jth prediction sample; k is 1,j The combination weight coefficient of the empirical formula prediction method at the jth prediction sample; h 1,j Predicting the height value of the water flowing fractured zone of the jth prediction sample for an empirical formula; k 2,j The combined weight coefficient of the multiple nonlinear regression prediction method at the jth prediction sample is set as the combined weight coefficient; h 2,j And predicting the height value of the water flowing fractured zone of the jth prediction sample for the multivariate nonlinear regression.
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