A method for dynamically adjusting a critical value of a pre-burst early warning index

Abstract

The present application relates to a kind of outburst early warning index critical value self-adapting dynamic adjustment method, belong to gas early warning field.This method is by dynamic correlation between early warning index and outburst prediction index, enhance the early warning effect of early warning index, specifically includes four steps: first, obtain the outburst prediction index data and early warning index data of coal mine working face;Then these data are subjected to regression analysis;Then according to the critical value of outburst prediction index, the critical value of early warning index is calculated;Finally, with the progress of mining activities, the cumulative outburst prediction index data set and early warning index data set are repeated in the second step and the third step, so that the critical value of early warning index can be self-adapting dynamic adjustment according to the latest outburst prediction data.The present application can make the critical value of outburst early warning index self-adapting dynamic adjustment according to the actual situation of coal mine production, enhance the early warning effect, provide more accurate auxiliary decision basis for the disaster prevention and control of coal and gas outburst.

Description

Technical Field

[0001] This invention belongs to the field of gas early warning and relates to an adaptive dynamic adjustment method for the critical value of gas outburst early warning index. Background Technology

[0002] Currently, there are two main methods for predicting and warning of coal and gas outburst hazards. One method involves measuring the gas desorption index of drill cuttings from the coal seam during drilling. This method has the advantage of high reliability, with a predetermined critical value, making it applicable to all coal and gas outburst mines. However, its disadvantages include discontinuous data and the inability to monitor and analyze data online. The other method utilizes computer technology to collect relevant coal and gas outburst data, establish early warning models and indicators, and achieve non-contact continuous early warning for coal and gas outbursts. This method solves the problems of data discontinuity and borehole blank zones in traditional prediction processes, becoming an effective supplement to coal and gas outburst prediction. However, the critical values ​​for the early warning indicators in this method need to be determined manually, and these critical values ​​may differ between different coal mines. How to adaptively adjust the early warning indicators according to the actual production situation of the coal mine is a key issue in improving the accuracy of early warnings.

[0003] Therefore, it is particularly important to find a precise method for predicting gas emission that can adapt to different production conditions in coal mines. Since the drill cuttings gas desorption index method is highly reliable and widely applicable, the adaptive dynamic adjustment method for the critical value of the early warning index dynamically correlates the early warning index with the drill cuttings gas desorption index, organically complementing the advantages and disadvantages of both indicators and enhancing the early warning effect. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide an adaptive dynamic adjustment method for the critical value of the anti-outburst early warning index. By dynamically linking the anti-outburst early warning index with the drill cuttings gas desorption index, the advantages and disadvantages of the drill cuttings gas desorption index and the early warning index are organically complemented, thereby enhancing the early warning effect of the early warning index.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] An adaptive dynamic adjustment method for the critical value of a sudden warning index, comprising the following steps:

[0007] S1: A set of average values ​​for coal mine outburst prevention prediction indicators for a given day. The set of average values ​​of emergency response and early warning indicator data Meanwhile, when the initial value defaults to 0 for the anti-breakthrough prediction index, the early warning index is also 0.

[0008] S2: The dataset D containing the anti-surprise prediction indexes i Dataset P of early warning indicators for emergency response iRegression analysis was performed with the initial values ​​to determine the relationship model P = a. i D+b i ;

[0009] S3: Based on the critical value D of the anti-outbreak prediction index data L Determine the critical value P of the early warning index for emergency response. L,i ;

[0010] S4: As mining activities progress, the amount of outburst prevention and early warning indicator data increases. Obtain the set of average values ​​of the outburst prevention and early warning indicator data for the previous n days. The set of average values ​​of the emergency warning indicators from the previous n days. n≥2, for D i and P i Repeat steps S2 to S3 to obtain the critical value P of the early warning indicator under data-driven conditions. L,i Adaptive results.

[0011] Optionally, in S1, the predicted data for coal mine outburst prevention indicators are obtained by measuring the gas desorption index K1 value of drill cuttings during drilling, or by measuring the gas content or gas pressure and the correlation data between coal and gas outbursts in coal mines.

[0012] Optionally, in S1, the coal mine outburst prevention early warning index data are index data in the outburst prevention early warning system, namely, the gas quantity early warning index and the gas desorption early warning index derived from the gas content inversion model.

[0013] Optionally, in S2, the regression analysis uses the linear regression method. The outburst prevention prediction index and the outburst prevention early warning index are indicators that reflect the magnitude of the coal mine outburst risk, and the two have a positive correlation.

[0014] Optionally, in S3, the critical value D of the anti-intrusion prediction index data. L The critical values ​​for indicators specified in industry standards, including the critical value of the drill cuttings gas desorption index K1. Early warning indicator threshold P L,i It is D L Substitute P = a i D+b i The result is derived from D in the equation.

[0015] The beneficial effects of the present invention are as follows: the adaptive method of the critical value of the anti-outburst early warning index of the present invention can adaptively and dynamically adjust the critical value of the anti-outburst early warning index according to the actual situation of coal mine production, thereby enhancing the early warning effect and providing auxiliary decision-making basis for the prevention and control of coal and gas outburst disasters.

[0016] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0017] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0018] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0019] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0020] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0021] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0022] like Figure 1 As shown, in a coal and gas outburst mine, the drill cuttings gas desorption index K1 value is used as a predictive indicator to predict the risk of coal and gas outbursts at the tunneling face. The critical value of K1 is... A coal and gas outburst early warning system was also installed to provide early warnings of outburst risks. The system selects the pre-gas quantity A as the early warning indicator. To improve the accuracy of early warning indicator A, the adaptive adjustment of the early warning threshold can be achieved through the following steps.

[0023] S1: Obtain the set of average values ​​of coal mine outburst prediction indicators D1 = {0.29} and the set of average values ​​of outburst warning indicators P1 = {2.59} ​​for a certain day. The initial default value is 0 for both the outburst prediction indicator and the warning indicator.

[0024] S2: Perform regression analysis on the anti-outbreak prediction index dataset D1={0.29}, the anti-outbreak early warning index dataset P1={2.59}, and the initial values ​​to determine the relationship model between them: P=8.93D+0;

[0025] S3: Based on the critical value D of the anti-outbreak prediction index data L =0.5, determine the critical value P of the early warning indicator. L,1 =4.47;

[0026] S4: As mining activities continue, the data for gas outburst prediction and early warning indicators are constantly increasing. The gas outburst prediction data sets for the previous 10 days, 20 days, and 30 days are respectively D 10 D 20 D 30 The average values ​​of the emergency response indicators for the first 10, 20, and 30 days were P, respectively. 10 P 20 P 30 .

[0027] D 10 ={0.29, 0.25, 0.29, 0.28, 0.27, 0.23, 0.27, 0.26, 0.26, 0.23}

[0028] D 20 ={0.29, 0.25, 0.29, 0.28, 0.27, 0.23, 0.27, 0.26, 0.26, 0.23, 0.24, 0.28, 0.27, 0.24, 0.3, 0.27, 0.32, 0.29, 0.17, 0.23}

[0029]

[0030] P 10 ={2.59, 1.25, 2.9, 2.69, 2.5, 1.67, 1.06, 1.75, 3.47, 2.74}

[0031] P 20={2.59, 1.25, 2.9, 2.69, 2.5, 1.67, 1.06, 1.75, 3.47, 2.74, 1.9, 2.92, 3.44, 4.77, 3.11, 2.65, 2.58, 2.37, 2.49, 2.81}

[0032]

[0033] For D 10 D 20 D 30 and P 10 P 20 P 30 Repeat process S2-S3 to obtain the critical values ​​P of the early warning indicator A for the first 10, 20, and 30 days under data-driven conditions. L,10 P L,20 P L,30 The adaptive results were 4.32, 4.43 and 7.31, respectively.

[0034] Therefore, the adaptive method for the critical value of the anti-outburst early warning index of the present invention can adaptively and dynamically adjust the critical value of the early warning index according to the actual situation of the coal mine, thereby improving the accuracy and applicability of the early warning index and achieving the best early warning effect.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for adaptive dynamic adjustment of the critical value of a sudden warning index, characterized in that: The method includes the following steps: S1: A set of average values ​​for coal mine outburst prevention prediction indicators for a given day. The set of average values ​​of emergency response and early warning indicator data Meanwhile, when the initial value defaults to 0 for the anti-breakthrough prediction index, the early warning index is also 0. S2: The dataset D containing the anti-surprise prediction indexes i Dataset P of early warning indicators for emergency response i Regression analysis was performed with the initial values ​​to determine the relationship model P = a. i D+b i ; S3: Based on the critical value D of the anti-outbreak prediction index data L Determine the critical value P of the early warning index for emergency response. L,i ; S4: As mining activities progress, the amount of outburst prevention and early warning indicator data increases. Obtain the set of average values ​​of the outburst prevention and early warning indicator data for the previous n days. The set of average values ​​of the emergency warning indicators from the previous n days. For D i and P i Repeat steps S2 to S3 to obtain the critical value P of the early warning indicator under data-driven conditions. L,i Adaptive results; In S1, the predicted data for coal mine outburst prevention indicators are the K1 value of the gas desorption index of drill cuttings measured during drilling, or the measured gas content or gas pressure and the data related to coal and gas outbursts in coal mines. In S1, the coal mine outburst prevention early warning index data are the index data in the outburst prevention early warning system, namely the gas quantity early warning index and the gas desorption early warning index derived from the gas content inversion model. In S2, the regression analysis uses the linear regression method. The outburst prevention prediction index and the outburst prevention early warning index are indicators that reflect the magnitude of the coal mine outburst risk, and the two have a positive correlation. In S3, the critical value D of the anti-intrusion prediction index data L The critical values ​​for indicators specified in industry standards, including the critical value of the drill cuttings gas desorption index K1. Early warning indicator threshold P L,i It is D L Substitute P = a i D+b i The result is derived from D in the equation.

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