Intelligent risk control method for coal and gas outburst in mining working face

Abstract

The present invention relates to the technical field of coal mine risk control, and in particular to an intelligent risk control method for coal and gas outburst in a mining working face, comprising the following steps: S1, generating a basic risk library of outburst risks according to the risk situation of coal and gas outburst; S2, performing risk identification, and entering the risk identification results into the system; S3, the system sends the control measures to the control personnel for execution and risk monitoring; S4, if the risk monitoring is qualified, the risk is added to the risk monitoring list, if the risk monitoring is unqualified, step S3 is executed; S5, if the risk dynamic monitoring result is abnormal, the risk abnormality is handled; S6, if the risk abnormality handling result is qualified, the risk dynamic monitoring is continued, if the result is unqualified, the risk abnormality is handled again. The present invention forms a basic risk library, finds the quantitative indicators of the corresponding control measures, and realizes early warning of risks by weighting the quantitative indicators and establishing an evaluation model.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine risk management and control, and in particular to an intelligent risk management and control method for coal and gas outbursts in a mining working face. Background Art

[0002] Full evaluation, also known as risk assessment, is a method and technique to identify system risk status and seek safety countermeasures. It aims to understand the possible types, degrees and consequences of dangers in the system before establishing necessary safety measures, and to conduct quantitative and qualitative analysis to propose effective risk control measures.

[0003] Commonly used safety assessment methods include traditional methods such as safety checklist analysis, expert review, pre-hazard analysis, fault type impact analysis, hazard index evaluation, accident tree analysis, fault tree analysis, operating condition hazard assessment, hazard and operability study, personnel reliability analysis, as well as new safety assessment methods such as hierarchical analysis method, fuzzy comprehensive evaluation method, grey correlation analysis method, and neural network analysis method.

[0004] When applying neural network method, entropy weight and mutation cardinality evaluation method, grey correlation evaluation method, risk matrix evaluation method and other methods, the limitations of factors such as mine geological conditions and mining type and the confusion in the dominance of indicators in the process of risk evaluation lead to certain deviations between the analysis results and the actual results. In addition, these methods have poor data correlation, chaotic evaluation structure, and poor authenticity of the evaluation results. Summary of the invention

[0005] The present invention aims to solve one of the above technical problems.

[0006] In order to solve one of the above technical problems, the present invention provides an intelligent risk control method for coal and gas outbursts in mining working faces. Through coal mining, excavation, machinery, transportation, and communication, various professional experts in coal mines identify the risks existing in all locations, places, and parts of coal mines, form a basic risk library, and determine the risk control measures and main responsible persons. The risk warning dimension is based on the basic risk library control measures, starting from the coal mine safety operating procedures and disaster occurrence mechanism, to find the quantitative indicators of the corresponding control measures, and to achieve early warning of risks by empowering the quantitative indicators and establishing an evaluation model.

[0007] The technical solution adopted by the present invention to solve the technical problem is: an intelligent risk control method for coal and gas outburst in a mining working face, comprising the following steps:

[0008] S1, formulate corresponding control measures according to the existing coal and gas outburst risk situation, and generate a basic database of coal and gas outburst risks at the mining face;

[0009] S2, refer to the basic database of coal and gas outburst risks at the mining face to identify risks, confirm the risk type, and enter the risk identification results into the system. The system selects corresponding control measures and generates an enterprise risk database;

[0010] S3, the system generates control measures corresponding to the coal and gas outburst risk and sends them to the control personnel, who then execute the control measures and monitor the risks;

[0011] S4, if the risk monitoring result is qualified, the corresponding risk is added to the risk monitoring list; if the risk monitoring result is unqualified, step S3 is executed;

[0012] S5, a risk dynamic monitoring process is performed on the risks in the risk monitoring list. After entering the risk dynamic monitoring process, if the monitoring result during the risk dynamic monitoring process is abnormal, the risk abnormality disposal is performed;

[0013] S6, evaluate the results of risk abnormality handling. If the evaluation result is qualified, continue to dynamically monitor the risk. If the evaluation result is unqualified, the system will notify the staff to re-handle the risk abnormality.

[0014] Furthermore, the risk monitoring process in step S3 includes the process of learning, feedback and reviewing the control measures. When the system sends the control tasks to the personnel who implement the measures, it also sends the control measures to the leaders in charge for their learning.

[0015] Furthermore, the dynamic risk monitoring in step S5 includes manually performing periodic checks on the risks in the risk monitoring list.

[0016] Furthermore, the dynamic risk monitoring in step S5 also includes the system evaluating the evaluation indicators of the control measures. If the evaluation result is abnormal, the system intelligently links the risk to carry out the hidden danger management process and notifies the corresponding personnel to manage the hidden danger.

[0017] Furthermore, the evaluation indicators include original coal seam outburst hazard evaluation indicators, outburst prevention measures implementation effect evaluation indicators and mining factor evaluation indicators.

[0018] Furthermore, the original coal seam outburst hazard evaluation indicators include gas pressure p, burial depth H, maximum principal stress σ1, coal damage type D, coal strength coefficient f and gas release initial velocity Δp.

[0019] Furthermore, the evaluation indicators for the implementation effect of the sudden emergency prevention measures include regional sudden emergency elimination effect, local prediction effect and safety protection measures.

[0020] Furthermore, the mining factor evaluation indicators include coal breaking method, mining face type, coal seam thickness and coal seam inclination.

[0021] Furthermore, the process of evaluating the evaluation indicators of the control measures includes the following steps:

[0022] Step 1: Establish a computational model to evaluate the evaluation indicators;

[0023] Step 2: Substitute each actual quantitative index c in the evaluation index into the calculation model established in step 1, perform calculations, and obtain the actual index score s;

[0024] Step 3: Evaluate the actual index score. When s is between 0 and 50, the evaluation result of the evaluation index is relatively dangerous. The lower the value of s, the higher the risk. When s is between 50 and 100, the evaluation result of the evaluation index is relatively safe. The higher the value of s, the lower the risk.

[0025] Further, step one includes:

[0026] Step I: Select quantitative indicators, select multiple representative quantitative indicators from the quantitative indicators, score the multiple representative quantitative indicators, and sort the selected quantitative indicators from small to large, and record them as c1, c2, ..., c i ,c j ,…,c n , and the scores corresponding to the sorted quantitative indicators are recorded as s1, s2, ..., s i ,s j ,…,s n .

[0027] Step II: When the quantitative indicator c falls into the interval [c i ,c j ], according to the formula Perform calculations;

[0028] Step III: When the quantitative indicator c falls into the interval [c i ,c j ], use linear interpolation to calculate:

[0029] When the quantitative index being evaluated c<c1, through the formula Calculate; when the quantitative index being evaluated c>c n When, through the formula Perform calculations.

[0030] The beneficial effect of the present invention is that the intelligent risk control method for coal and gas outburst in the mining working face of the present invention realizes the risk control of the production process for the risks of specific locations by referring to the basic risk library when the coal mine conducts annual and special identification; the risk warning dimension realizes the control measures according to the basic risk library, triggers from the perspective of coal mine safety operating procedures and disaster occurrence mechanism, finds the quantitative indicators of the corresponding control measures, and realizes the early warning of risks by weighting the quantitative indicators and establishing an evaluation model, so as to provide a method for the risk control and early warning of coal and gas outburst in the mining working face. This method is based on the virtual mining working face as the reference object, constructs a model for the risk control and early warning of coal and gas outburst in the excavation working face, and determines the evaluation indicators. The evaluation indicator data can come from the safety monitoring, mine pressure monitoring and other systems, which can more comprehensively and accurately reflect the disaster risk situation of the coal mine, and has strong operability. And it provides characteristic indicators for the risk control and early warning of coal and gas outburst in the mining working face, and realizes the real-time early warning of gas outburst risk according to the indicators.

[0031] The method of the present invention is used to evaluate the outstanding danger of the mining face, and the score of the evaluated coal mine mining face is obtained more intuitively, and the evaluated mining face is warned. In addition, the specific risk control measures that fail are inferred based on the mining face warning score. According to the control person specified in the control measures, the failed control measures are managed according to the standard control plan, and the risk control is completed by the quantitative data indicator management personnel.

[0032] The method of the present invention adopts a structural evaluation model to perform real-time quantitative evaluation of the danger of outburst in a mining face. At the same time, the method has wide applicability and can perform real-time risk evaluation of various underground disasters through various underground monitoring and surveillance systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0034] Figure 1 It is a schematic diagram of the intelligent risk management method for coal and gas outburst in a mining working face of the present invention.

[0035] Figure 2 It is a schematic diagram of evaluating the evaluation indicators of the control measures of the present invention.

[0036] Figure 3 It is a process schematic diagram of step one in an embodiment of the present invention.

[0037] Figure 4 It is a flow chart of the intelligent risk control method for coal and gas outburst in a mining working face of the present invention.

[0038] Figure 5 It is a schematic diagram of the factors affecting the danger of outburst in the mining working face in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0040] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more. In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be a connection between the two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0041] like Figures 1 to 5 As shown, it is the best embodiment of the present invention, a method for intelligent risk control of coal and gas outburst in a mining working face, comprising the following steps:

[0042] S1, formulate corresponding control measures according to the existing coal and gas outburst risk situation, and generate a basic database of coal and gas outburst risks at the mining face;

[0043] S2, refer to the basic database of coal and gas outburst risks at the mining face to identify risks, confirm the risk type, and enter the risk identification results into the system. The system selects corresponding control measures and generates an enterprise risk database;

[0044] S3, the system generates control measures corresponding to the coal and gas outburst risk and sends them to the control personnel, who then execute the control measures and monitor the risks;

[0045] S4, if the risk monitoring result is qualified, the corresponding risk is added to the risk monitoring list; if the risk monitoring result is unqualified, step S3 is executed;

[0046] S5, a risk dynamic monitoring process is performed on the risks in the risk monitoring list. After entering the risk dynamic monitoring process, if the monitoring result during the risk dynamic monitoring process is abnormal, the risk abnormality disposal is performed;

[0047] S6, evaluate the results of risk abnormality handling. If the evaluation result is qualified, continue to dynamically monitor the risk. If the evaluation result is unqualified, the system will notify the staff to re-handle the risk abnormality.

[0048] The risk monitoring process in step S3 includes the process of learning, feedback and reviewing the control measures. When the system sends the control tasks to the personnel who implement the measures, it also sends the control measures to the leaders in charge for their knowledge.

[0049] The dynamic risk monitoring in step S5 includes manually performing periodic checks on the risks in the risk monitoring list.

[0050] The dynamic risk monitoring in step S5 also includes the system evaluating the evaluation indicators of the control measures. If the evaluation result is abnormal, the system will be intelligently linked.

[0051] Reference Figure 1 , the process of risk control is as follows: when a coal mining enterprise conducts risk identification, the risk identification personnel analyze the production process, equipment and facilities, working environment and other conditions of the work site against the risk basic database, and use the LEC method to classify the identified risks. The LEC method is a semi-quantitative safety evaluation method for hazardous sources in potentially dangerous working environments, where L is the possibility of an accident, E is the frequency of personnel exposure to dangerous environments, and C is the possible consequences of an accident, that is, D = L × E × C, the greater the D, the greater the risk after the risk identification is completed. After the risk identification is completed, the identified risks enter the enterprise risk database, and according to the implementation requirements of the control measures of each risk point, the risk control tasks are automatically created and sent to the responsible person for knowledge, feedback and review. After the risk control measures are reviewed and qualified, a complete risk monitoring list is formed, and risk warnings are carried out according to the risk control cycle and the evaluation indicators corresponding to the control measures. When manual inspection finds that the failure of risk control measures has been upgraded to hidden dangers, the risk anomaly handling process is initiated. The risk anomaly handling process is to manage the risk anomalies that are transformed into hidden dangers according to the hidden danger handling process. When the system evaluates the evaluation indicators of the control measures, if the analysis result shows that the evaluation indicators corresponding to the control measures are abnormal, the intelligent control analysis warning is initiated.

[0052] According to the specific risks existing in the mining working face, control measures and main responsibilities of control are formulated to compile a basic database of coal and gas outburst risks at the mining working face as shown in Table 1.

[0053] Table 1 Risk basis of coal and gas outburst in mining working face

[0054]

[0055]

[0056] In order to find out the corresponding evaluation indicators of risk control measures, when conducting coal and gas outburst risk assessment of mining working faces, in order to obtain the overall situation of the current coal mine outburst risk in real time based on the underlying data, it is necessary to evaluate the outburst hazard of each mining working face one by one from the specific data obtained in the outburst prevention work of each mining working face. In addition, when evaluating the outburst hazard of each mining working face, it should not only be conducted on coal seams that have been identified as having outburst hazards, but should be conducted on coal seams of various gas grades, because even if some coal seams have not been identified or identified as non-outburst coal seams, due to changes in mining conditions or errors in identification, the mining working face of the coal seam is still likely to have an outburst disaster. One of the functions of safety evaluation and early warning is to find out the disaster risk and take countermeasures. Therefore, on the basis of the basic risk library of coal and gas outburst, based on the coal and gas outburst mechanism and outburst disaster prevention and control, the corresponding evaluation indicators of risk control measures are found, as shown in Table 2 below.

[0057] Table 2 Correspondence table of control measures and scoring indicators of coal and gas outburst risk basic library

[0058]

[0059]

[0060] Based on the risk control measures for coal and gas outbursts in mining working faces, and based on the mechanism of coal and gas outbursts and the prevention and control of outburst disasters, the corresponding evaluation indicators of risk control measures are found, including the evaluation indicators of the original coal seam outburst hazard, the evaluation indicators of the implementation effect of outburst prevention measures, and the evaluation indicators of mining factors as the criterion layer. Referring to the figure, the evaluation indicators of the original coal seam outburst hazard include gas pressure p, burial depth H, maximum principal stress σ1, coal damage type D, coal solidity coefficient f and gas release initial velocity Δp. The evaluation indicators of the implementation effect of outburst prevention measures include regional outburst elimination effect, local prediction effect and safety protection measures. The evaluation indicators of mining factors include coal breaking method, mining working face type, coal seam thickness and coal seam inclination.

[0061] Figure 5The criterion layer in the criterion layer considers the influencing factors of the outburst danger of the mining face from the overall perspective. Its elements mainly include the outburst danger of the original coal seam, the implementation effect of the anti-outburst measures to deal with this danger, and other coal seam occurrence and mining factors. The outburst danger of the original coal seam is indispensable, because the coal seam with a large outburst danger is more likely to have an outburst phenomenon in the mining project. For non-outburst coal seams, it is not necessary to take anti-outburst measures. This element should be used to represent the outburst danger of the mining face in the coal seam; the implementation effect of the anti-outburst measures mainly refers to the implementation effect of the regional measures and the implementation effect of the local measures. Only after eliminating the regional outburst danger can local mining work be carried out; in addition to disaster risks and special anti-outburst measures, there are other factors that have an important impact on the outburst danger of the mining face, such as: coal breaking methods include mechanical coal breaking, blasting coal breaking, pneumatic pick coal breaking, etc., mining face types include coal mining face, coal seam level roadway, coal seam up and down the mountain, etc., as well as coal seam thickness and inclination.

[0062] The process of evaluating the evaluation indicators of control measures includes the following steps:

[0063] Establish a computational model to evaluate the evaluation indicators;

[0064] Substitute each actual quantitative index c in the evaluation index into the calculation model established in step 1, perform calculations, and obtain the actual index score s;

[0065] The actual index score is evaluated. When s is between 0 and 50, the evaluation result of the evaluation index is relatively dangerous. The lower the value of s, the higher the risk. When s is between 50 and 100, the evaluation result of the evaluation index is relatively safe. The higher the value of s, the lower the risk.

[0066] Step one includes:

[0067] Step I: Select quantitative indicators, select multiple representative quantitative indicators from the quantitative indicators, score the multiple representative quantitative indicators, and sort the selected quantitative indicators from small to large, and record them as c1, c2, ..., c i ,c j ,…,c n , and the scores corresponding to the sorted quantitative indicators are recorded as s1, s2, ..., s i ,s j ,…,s n .

[0068] Step II: When the quantitative indicator c falls into the interval [c i ,c j ], according to the formula Calculate, i = 1, 2, 3...n;

[0069] Step III: When the quantitative indicator c falls into the interval [c i ,c j ], use linear interpolation to calculate:

[0070] When the quantitative index being evaluated c<c1, through the formula Calculate; when the quantitative index being evaluated c>c n When, through the formula Perform calculations.

[0071] For the coal and gas outburst hazard assessment model of the mining face, a virtual mining face is established as a reference object, and its indicators are all critical values, with a score of 50 points. When conducting a hazard assessment, it is necessary to compare the evaluation indicators in the criterion layer with the evaluation indicators of the virtual mining face to obtain the indicator score. The calculation rules for the scoring of the coal and gas outburst hazard assessment indicators of the mining face are shown in Table 3.

[0072] Table 3 Calculation rules for index scoring of coal and gas outburst hazards in mining operations

[0073]

[0074]

[0075] The beneficial effect of the present invention is that the intelligent risk control method for coal and gas outburst in the mining working face of the present invention realizes the risk control of the production process for the risks of specific locations by referring to the basic risk library when the coal mine conducts annual and special identification; the risk warning dimension realizes the control measures according to the basic risk library, triggers from the perspective of coal mine safety operating procedures and disaster occurrence mechanism, finds the quantitative indicators of the corresponding control measures, and realizes the early warning of risks by weighting the quantitative indicators and establishing an evaluation model, so as to provide a method for the risk control and early warning of coal and gas outburst in the mining working face. This method is based on the virtual mining working face as the reference object, constructs a model for the risk control and early warning of coal and gas outburst in the excavation working face, and determines the evaluation indicators. The evaluation indicator data can come from the safety monitoring, mine pressure monitoring and other systems, which can more comprehensively and accurately reflect the disaster risk situation of the coal mine, and has strong operability. And it provides characteristic indicators for the risk control and early warning of coal and gas outburst in the mining working face, and realizes the real-time early warning of gas outburst risk according to the indicators.

[0076] The method of the present invention is used to evaluate the outstanding danger of the mining face, and the score of the evaluated coal mine mining face is obtained more intuitively, and the evaluated mining face is warned. In addition, the specific risk control measures that fail are inferred based on the mining face warning score. According to the control person specified in the control measures, the failed control measures are managed according to the standard control plan, and the risk control is completed by the quantitative data indicator management personnel.

[0077] The method of the present invention adopts a structural evaluation model to perform real-time quantitative evaluation of the danger of outburst in a mining face. At the same time, the method has wide applicability and can perform real-time risk evaluation of various underground disasters through various underground monitoring and surveillance systems.

[0078] Based on the above ideal embodiments of the present invention, the relevant staff can make various changes and modifications without departing from the technical concept of the present invention through the above description. The technical scope of the present invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. An intelligent risk management method for coal and gas outburst in a mining working face, characterized by: The following steps are involved: S1, formulate corresponding control measures according to the existing coal and gas outburst risk situation, and generate a basic database of coal and gas outburst risks at the mining face; S2, refer to the basic database of coal and gas outburst risks at the mining face to identify risks, confirm the risk type, and enter the risk identification results into the system. The system selects corresponding control measures and generates an enterprise risk database; S3, the system generates control measures corresponding to the coal and gas outburst risk and sends them to the control personnel, who then execute the control measures and monitor the risks; S4, if the risk monitoring result is qualified, the corresponding risk is added to the risk monitoring list; if the risk monitoring result is unqualified, step S3 is executed; S5, a risk dynamic monitoring process is performed on the risks in the risk monitoring list. After entering the risk dynamic monitoring process, if the monitoring result during the risk dynamic monitoring process is abnormal, the risk abnormality disposal is performed; The dynamic risk monitoring in step S5 also includes the system evaluating the evaluation indicators of the control measures. If the evaluation result is abnormal, the system will be intelligently linked; S6, the results of risk abnormality disposal are appraised. If the appraisal result is qualified, the risk dynamic monitoring continues. If the appraisal result is unqualified, the system notifies the staff to re-handle the risk abnormality; The evaluation indexes include the original coal seam outburst hazard evaluation index, outburst prevention measures implementation effect evaluation index and mining factor evaluation index; the original coal seam outburst hazard evaluation index, outburst prevention measures implementation effect evaluation index and mining factor evaluation index are the criterion layer, the criterion layer considers the influencing factors of the outburst hazard of the mining working face from the overall perspective, and its elements mainly include the outburst hazard of the original coal seam, the implementation effect of the outburst prevention measures to deal with this hazard, and other coal seam occurrence and mining factors; The process of evaluating the evaluation indicators of control measures includes the following steps: Step 1: Establish a computational model to evaluate the evaluation indicators; Step 2: Substitute each actual quantitative index c in the evaluation index into the calculation model established in step 1, perform calculations, and obtain the actual index score s; Step 3: Evaluate the actual index score. When s is between 0 and 50, the evaluation result of the evaluation index is relatively dangerous. The lower the value of s is, the higher the risk is. When s is between 50 and 100, the evaluation result of the evaluation index is relatively safe. The higher the value of s is, the lower the risk is. Step one includes: Step I, selecting quantitative indicators, selecting multiple representative quantitative indicators from the quantitative indicators, scoring the multiple representative quantitative indicators, and sorting the selected quantitative indicators from small to large, and recording them as c1, c2, ..., ci, cj, ..., cn in sequence, and recording the scores corresponding to the sorted quantitative indicators as s1, s2, ..., si, sj, ..., sn in sequence; Step II: When the quantitative index c falls into the interval [ci ,cj ], according to the formula Perform calculations; Step III: When the quantitative index c falls outside the interval [ci, cj], use the linear interpolation method to calculate: When the quantitative index c is less than c1, the formula Calculate; when the quantitative index c>cn, through the formula Perform calculations.

2. The intelligent risk management and control method for coal and gas outburst in a mining working face according to claim 1, characterized in that: The risk monitoring process in step S3 includes the process of learning, feedback and reviewing the control measures. When the system sends the control tasks to the personnel who implement the measures, it also sends the control measures to the leaders in charge for their knowledge.

3. The intelligent risk management and control method for coal and gas outburst in a mining face according to claim 1, characterized in that: The dynamic risk monitoring in step S5 includes manually performing periodic checks on the risks in the risk monitoring list.

4. The method for intelligent risk control of coal and gas outburst in a mining face according to claim 1, characterized in that: The original coal seam outburst hazard evaluation indicators include gas pressure p, burial depth H, maximum principal stress σ1, coal damage type D, coal strength coefficient f and gas release initial velocity Δp.

5. The intelligent risk management and control method for coal and gas outburst in a mining working face according to claim 1, characterized in that: The evaluation indicators for the implementation effect of the anti-burst measures include regional sudden relief effect, local prediction effect and safety protection measures.

6. The intelligent risk management and control method for coal and gas outburst in a mining working face according to claim 1, characterized in that: The mining factor evaluation indicators include coal breaking method, mining working face type, coal seam thickness and coal seam inclination.

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