A coal mine gas extraction parameter intelligent control system and method

Abstract

The present application relates to the technical field of coal seam gas extraction, and provides a gas extraction parameter intelligent control system and method. By adjusting the safety constraint conditions of the basic data collection results of gas extraction, an optimized adjustment safety constraint condition is generated; the gas extraction control data and the real-time monitoring data set are obtained; when any data in the real-time monitoring data set cannot meet the adjustment safety constraint condition, the shutdown control is executed; the real-time monitoring data set and the gas extraction control data are input into the intelligent control model to obtain the optimal extraction system control data for intelligent control of gas extraction. The technical problem that the control of coal mine gas extraction equipment in the prior art is highly dependent on manual experience, resulting in safety hazards in gas extraction and more energy waste during the extraction process is solved, the intelligent control of gas extraction equipment is realized, the safety hazards of coal mine gas extraction are avoided, and the scientificity of the control of coal mine gas extraction system and the extraction efficiency are improved.

Description

Technical Field

[0001] The present application relates to the technical field of coal seam gas extraction, and in particular to an intelligent control system and method for coal mine gas extraction parameters. Background Art

[0002] Coal mine gas is the coalbed methane generated during the coalification process. Most coal seams require gas extraction before mining to reduce the coal seam gas content and the amount of gas outburst during mining, so as to achieve safe mining in a low-gas state, prevent gas accidents, and ensure safe production in coal mines.

[0003] With the scientific development of coal mining, coal mine gas extraction is currently mostly completed using ground fixed gas extraction systems. By controlling the extraction data of the gas extraction system, the gas extraction negative pressure, gas extraction temperature, gas extraction concentration, gas extraction pure amount and gas extraction energy efficiency ratio can be controlled within a safe range. At present, the control parameter adjustment of the gas extraction system mostly adopts manual experience control, which not only poses a safety hazard, but also generates a lot of energy waste during the operation of the gas extraction system.

[0004] In summary, the existing technology has the technical problem that the control of coal mine gas extraction equipment is highly dependent on manual experience, resulting in safety hazards in gas extraction and low gas extraction efficiency. Summary of the invention

[0005] Based on this, it is necessary to provide a coal mine gas extraction parameter intelligent control system and method that can realize the intelligent and scientific regulation of gas extraction equipment, avoid safety hazards of gas extraction, and improve the efficiency of the gas extraction process in response to the above-mentioned technical problems.

[0006] A coal mine gas extraction parameter intelligent control system, the system includes: a basic data acquisition module, used to collect coal mine gas extraction basic data through interactive sensors to obtain basic data acquisition results; a constraint condition construction module, used to construct safety constraint conditions through big data, adjust the safety constraint conditions according to the extraction basic data acquisition results, and generate adjusted safety constraint conditions; a control data acquisition module, used to perform gas extraction on the coal mine gas and obtain extraction control data; a real-time data acquisition module, used to collect data of multiple gas extraction parameter indicators through data acquisition sensors to obtain real-time monitoring data sets; a safety verification execution module, based on the adjusted safety constraint conditions The real-time monitoring data set is safety verified, and when any data cannot meet the adjustment safety constraint condition, shutdown control is executed; a data optimization execution module is used to input the real-time monitoring data set and the extraction control data into an intelligent control model, wherein the intelligent control model includes multiple feature supervision variables, and the extraction control data is regulated based on the intelligent control model, and multi-feature change fitting is performed according to the control result and the real-time monitoring data set, and control optimization of multi-feature change fitting is performed through the multiple feature supervision variables, and optimized extraction control data is output; an intelligent control execution module is used to perform intelligent regulation on the coal mine gas extraction system according to the optimized extraction control data.

[0007] A method for intelligent control of coal mine gas extraction parameters, the method comprising: collecting basic data of coal mine gas extraction through the interactive sensor to obtain basic extraction data collection results; constructing safety constraints through big data, adjusting the safety constraints according to the basic extraction data collection results, and generating adjusted safety constraints; performing gas extraction on the coal mine gas to obtain extraction control data; collecting data of multiple gas extraction parameter indicators through the data acquisition sensor to obtain a real-time monitoring data set; performing safety verification on the real-time monitoring data set based on the adjusted safety constraints, and executing shutdown control when any data cannot meet the adjusted safety constraints; inputting the real-time monitoring data set and the extraction control data into an intelligent control model, wherein the intelligent control model includes multiple feature supervision variables, controlling the extraction control data based on the intelligent control model, performing multi-feature change fitting according to the control results and the real-time monitoring data set, and performing control optimization of multi-feature change fitting through the multiple feature supervision variables, and outputting optimized extraction control data; and intelligently controlling the coal mine gas extraction system according to the optimized extraction control data.

[0008] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0009] Collect basic data of coal mine gas extraction through the interactive sensor to obtain basic data collection results;

[0010] Constructing safety constraints through big data, adjusting the safety constraints according to the basic data collection results, and generating adjusted safety constraints;

[0011] Performing gas extraction on the coal mine gas to obtain extraction control data;

[0012] The data acquisition sensor is used to collect data of multiple gas extraction parameter indicators to obtain a real-time monitoring data set;

[0013] Performing safety verification on the real-time monitoring data set based on the adjusted safety constraint condition, and executing shutdown control when any data fails to meet the adjusted safety constraint condition;

[0014] Input the real-time monitoring data set and the extraction control data into an intelligent control model, wherein the intelligent control model includes a plurality of feature supervision variables, and control the extraction control data based on the intelligent control model, and perform multi-feature change fitting according to the control result and the real-time monitoring data set, and perform control optimization of multi-feature change fitting through the plurality of feature supervision variables, and output optimized extraction control data;

[0015] The coal mine gas extraction system is intelligently controlled according to the optimal extraction control data.

[0016] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0017] Collecting basic data of coal mine gas extraction through the interactive sensor to obtain basic extraction data collection results;

[0018] Constructing safety constraints through big data, adjusting the safety constraints according to the basic data collection results, and generating adjusted safety constraints;

[0019] Performing gas extraction on the coal mine gas to obtain extraction control data;

[0020] The data acquisition sensor is used to collect data of multiple gas extraction parameter indicators to obtain a real-time monitoring data set;

[0021] Performing safety verification on the real-time monitoring data set based on the adjusted safety constraint condition, and executing shutdown control when any data fails to meet the adjusted safety constraint condition;

[0022] Input the real-time monitoring data set and the extraction control data into an intelligent control model, wherein the intelligent control model includes a plurality of feature supervision variables, and control the extraction control data based on the intelligent control model, and perform multi-feature change fitting according to the control result and the real-time monitoring data set, and perform control optimization of multi-feature change fitting through the plurality of feature supervision variables, and output optimized extraction control data;

[0023] The coal mine gas extraction system is intelligently controlled according to the optimal extraction control data.

[0024] The above-mentioned intelligent control system and method for coal mine gas extraction parameters solves the technical problem in the prior art that the control of coal mine gas extraction equipment is highly dependent on manual experience, resulting in safety hazards in gas extraction and low gas extraction efficiency. It realizes the intelligent and scientific control of gas extraction equipment, avoids safety hazards in gas extraction, and improves the technical effect of the efficiency of the gas extraction process.

[0025] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of a process of an intelligent control method for coal mine gas extraction parameters in one embodiment;

[0027] Figure 2 A schematic diagram of a process for performing intelligent control model optimization feedback optimization in an intelligent control method for coal mine gas extraction parameters in an embodiment;

[0028] Figure 3 It is a structural block diagram of a coal mine gas extraction parameter intelligent control system in one embodiment;

[0029] Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment.

[0030] Explanation of the accompanying drawings: basic data acquisition module 1, constraint condition construction module 2, control data acquisition module 3, real-time data acquisition module 4, safety verification execution module 5, data optimization execution module 6, intelligent regulation execution module 7. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0032] like Figure 1 As shown, the present application provides a method for intelligent control of coal mine gas extraction parameters, the method is applied to an intelligent control system for coal mine gas extraction parameters, the intelligent control system for coal mine gas extraction parameters is communicatively connected with a data acquisition sensor and an interactive sensor, the method includes:

[0033] S100: Collecting basic data of coal mine gas extraction through the interactive sensor to obtain basic data collection results;

[0034] Specifically, the coal mine gas is the coalbed methane generated during the coalification process of plants. Most coal seams require gas extraction before mining to reduce the coal seam gas content and the amount of gas outburst during mining, so as to achieve safe mining in a low-gas state, prevent gas accidents, and ensure safe production in coal mines.

[0035] With the scientific development of coal mining, coal mine gas extraction is currently mostly completed by using ground fixed gas extraction systems. The gas extraction system is mainly composed of extraction pumps, extraction pipelines, valve control, data monitoring mechanism and ancillary equipment. By regulating the extraction data of the gas extraction system, the gas extraction negative pressure, gas extraction temperature, gas extraction concentration, gas extraction pure amount and gas extraction energy efficiency ratio can be controlled within a safe range.

[0036] In this embodiment, the interactive sensor is a multifunctional data acquisition sensor device, which is used to obtain the original gas composition data of the gas extraction area of ​​the coal seam to be mined where gas extraction has not been performed, and obtain the basic data acquisition results. The basic data acquisition results include ethylene concentration information, carbon monoxide concentration information, oxygen volume fraction information, extraction area temperature information, extraction area humidity information, extraction area gas pure amount information and extraction area gas concentration information.

[0037] S200: constructing security constraints through big data, adjusting the security constraints according to the basic data collection results, and generating adjusted security constraints;

[0038] Specifically, in this embodiment, the parameter indicators that need to be monitored during the gas extraction process are obtained according to the "Basic Indicators of Coal Mine Gas Extraction", and the safety constraints are constructed. The safety constraints include ethylene constraints, carbon monoxide constraints, oxygen constraints, gas extraction negative pressure constraints, gas extraction temperature constraints, gas extraction concentration constraints, and gas extraction scalar constraints.

[0039] The basic data collection results include data related to coal mine gas extraction safety and data not related to it. The basic data collection results are traversed based on the safety constraints to eliminate data not related to gas extraction safety, complete conditional adjustment of the safety constraints, and obtain the adjusted safety constraints. The adjusted safety constraints include multiple gas extraction condition constraints and corresponding values.

[0040] S300: Performing gas extraction on the coal mine gas to obtain extraction control data;

[0041] Specifically, in this embodiment, gas extraction is carried out in the extraction area of ​​the coal seam to be mined based on the gas extraction system. The extraction control data is the control quantity data for regulating and controlling the gas extraction system, specifically including the valve opening and the extraction pump power. By adjusting the gas extraction system control data, the real-time gas extraction concentration, real-time gas extraction pure amount, real-time gas extraction negative pressure and real-time extraction pump efficiency of the gas extraction system are adjusted and controlled.

[0042] In this embodiment, a gas extraction system is operated to extract gas from the coal mine gas, and extraction control data of the gas extraction system during the extraction process is obtained. The extraction control data provides a control benchmark for subsequent extraction control and adjustment.

[0043] S400: Collect data of multiple parameter indicators through the data collection sensor to obtain a real-time monitoring data set;

[0044] Specifically, the gas extraction system is mainly composed of an extraction pump, an extraction pipeline, valve control, a data monitoring mechanism and ancillary equipment. The extraction pipeline is in direct contact with the coal mine gas for gas extraction. The data sensor is installed in the extraction pipeline for real-time monitoring and collection of gas extraction data. The data sensor is provided with multiple monitoring points in the extraction pipeline for execution supervision.

[0045] The parameter indicators monitored by the data sensor include: gas extraction pure amount, gas extraction concentration, extraction negative pressure, extraction pump energy efficiency ratio, ethylene concentration, carbon monoxide concentration, extraction pipeline outlet gas temperature, negative pressure, and oxygen volume fraction. The data acquisition sensor performs real-time data acquisition of the aforementioned multiple parameter indicators at the extraction pipeline outlet to obtain the real-time monitoring data set, which provides a data comparison and judgment benchmark for subsequent comparison of the adjustment constraint conditions to determine whether the gas extraction process can be safely performed at present.

[0046] S500: Performing safety verification on the real-time monitoring data set based on the adjusted safety constraint condition, and executing shutdown control when any data fails to meet the adjusted safety constraint condition;

[0047] In one embodiment, the method steps provided by the present application further include:

[0048] S510: setting an efficiency constraint threshold according to the basic extraction data collection result, wherein the set efficiency constraint threshold includes a gas concentration threshold and a gas scalar threshold;

[0049] S520: When there is data in the real-time monitoring data set that does not meet the set efficiency constraint threshold, shutdown control is performed.

[0050] Specifically, in this embodiment, the gas pure quantity information and gas concentration information of the extraction area of ​​the coal seam gas to be mined are extracted according to the basic data collection results, and the gas concentration threshold and the gas pure quantity threshold are obtained according to the gas pure quantity information and the gas extraction concentration data of the extraction area, combined with the adjusted safety constraint conditions obtained in step S200 and the gas extraction system operation efficiency index. The gas concentration threshold and the gas pure quantity threshold are the minimum critical thresholds of the corresponding operating condition indicators.

[0051] In the adjusted safety constraint conditions obtained in step S200, parameter indicators that are consistent with the real-time monitoring data set are extracted for data comparison, and primary safety verification is performed on the real-time monitoring data set. When any parameter indicator data fails to meet the adjusted safety constraint conditions, shutdown control is executed on the gas extraction system.

[0052] Parameter indicators consistent with the items in the real-time monitoring data set are extracted from the adjusted safety constraints for data comparison, and primary safety verification is performed on the real-time monitoring data set. When any parameter indicator data meets the adjusted safety constraints, efficiency constraint judgment is performed. Specifically, real-time gas extraction concentration and real-time gas extraction pure amount are extracted based on the real-time monitoring data set, and the real-time gas extraction concentration and real-time gas extraction pure amount are compared with the gas concentration threshold and gas pure amount threshold of the set efficiency constraint threshold. When any data in the real-time gas extraction concentration and the real-time gas extraction pure amount does not meet the set efficiency constraint threshold, shutdown control is performed on the gas extraction system.

[0053] When the real-time gas extraction concentration and the real-time gas extraction quantity both meet the data of the set efficiency constraint threshold, the gas extraction system is controlled and adjusted to obtain gas extraction system control data that can achieve the optimal solution for gas extraction concentration, gas extraction quantity, gas extraction negative pressure and extraction pump efficiency ratio. This embodiment elaborates on the control and adjustment content of the gas extraction system in the subsequent description.

[0054] This embodiment avoids the continuous operation of the gas extraction system under the gas extraction risk state by combining the safety constraint condition judgment with the efficiency constraint condition judgment, thereby improving the safety of coal mine gas extraction.

[0055] S600: Inputting the real-time monitoring data set and the extraction control data into an intelligent control model, wherein the intelligent control model includes a plurality of feature supervision variables, performing control of the extraction control data based on the intelligent control model, performing multi-feature change fitting according to the control result and the real-time monitoring data set, and performing control optimization of multi-feature change fitting through the plurality of feature supervision variables, and outputting optimized extraction control data;

[0056] In one embodiment, the method steps provided by the present application further include:

[0057] S610: taking gas extraction concentration, gas extraction flow rate, gas extraction negative pressure and extraction pump efficiency ratio as multiple monitoring characteristic variables;

[0058] S620: Setting the feature correlation coefficients and basic feature satisfaction values ​​of the multiple supervisory feature variables;

[0059] S630: when performing control optimization of multi-feature change fitting, determining whether the multi-feature change fitting results all meet the basic feature satisfaction value;

[0060] S640: When all the basic features satisfy the values, optimal weighted calculation of the multiple supervisory feature variables is performed according to the feature association coefficient, and the optimal fitting result is generated according to the weighted calculation result.

[0061] In one embodiment, the method steps provided by the present application further include:

[0062] S641: Setting the optimization constraint path length;

[0063] S642: when executing the control optimization, if the optimization path length has satisfied the optimization constraint path length and no optimization result satisfying the preset optimization threshold is found, the control stops the optimization;

[0064] S643: Read the local optimal value in the optimization process, and use the local optimal value as the result of controlling the optimization.

[0065] Specifically, in this embodiment, the control data optimization of the gas extraction system is executed when and only when the real-time monitoring data set satisfies the adjusted safety constraint condition and the real-time monitoring data set satisfies the set efficiency constraint threshold. In order to improve the effectiveness and scientificity of the control data optimization of the gas extraction equipment, this embodiment adopts the construction of an intelligent control model for control data optimization.

[0066] This embodiment constructs the intelligent control model based on the long short-term memory network (LSTM) of deep learning. The input data of the intelligent control model is the real-time monitoring data set and the extraction control data, and the output result is the optimal extraction control data. The optimal extraction control data specifically includes the optimal control valve opening data and the optimal extraction pump power data.

[0067] The logic of optimizing the intelligent control model is to set multiple characteristic monitoring variables consisting of gas extraction concentration, gas extraction scalar volume, gas extraction negative pressure and extraction pump efficiency ratio. The weight distribution relationship of the multiple characteristic monitoring variables is based on the gas accident risk level that may be caused by the numerical changes of the multiple characteristic monitoring variables. The specific numerical values ​​are not mandatory. The most suitable extraction control data (valve opening and extraction pump power) are found by changing the characteristic correlation coefficients of the multiple characteristic monitoring variables.

[0068] The characteristic correlation coefficient is a specific value of the supervisory characteristic variable, for example, the gas extraction concentration data is the characteristic correlation coefficient of the supervisory characteristic variable of gas extraction concentration. The basic characteristic satisfaction value sets a constraint range for the data of the supervisory characteristic variable.

[0069] The optimization control for executing multi-feature change fitting includes four optimization directions. The first direction is the multi-feature change fitting of the characteristic correlation coefficient changes of the other multiple supervised feature variables while the gas extraction concentration value is fixed. The second direction is the multi-feature change fitting of the characteristic correlation coefficient changes of the other multiple supervised feature variables while the gas extraction scalar value is fixed. The third direction is the multi-feature change fitting of the characteristic correlation coefficient changes of the other multiple supervised feature variables while the gas extraction negative pressure value is fixed. The fourth direction is the multi-feature change fitting of the characteristic correlation coefficient changes of the other multiple supervised feature variables while the extraction pump efficiency ratio value is fixed.

[0070] In the process of performing optimal control of multi-feature change fitting, the multiple feature correlation coefficients obtained by setting the numerical values ​​of the multiple supervisory feature variables are defined as the multi-feature change fitting results. When and only when each data in the set multi-feature change fitting results satisfies the corresponding basic feature satisfaction value, the optimal weighted calculation of the multiple supervisory feature variables is performed according to the feature correlation coefficient, and the optimal fitting result is generated according to the weighted calculation result. The optimal fitting result can be regarded as the weighted scoring result of the multi-feature change fitting result. The larger the numerical value of the optimal fitting result, the higher the adaptability of the extraction control data used to generate the multi-feature change fitting result to the current gas extraction system control requirements.

[0071] In this embodiment, the multiple supervisory feature variables can only be optimized when they meet the basic feature satisfaction value. At the same time, the multiple supervisory feature variables are set with preset optimization thresholds. When any feature correlation coefficient of the multiple supervisory feature variables meets the preset optimization threshold, the optimization control can be stopped and the optimization fitting result can be output.

[0072] At the same time, in order to avoid the situation where any feature correlation coefficient of multiple supervised feature variables does not meet the preset optimization threshold when performing optimization control in any direction based on multi-feature change fitting, resulting in the optimization falling into a loop or infinite optimization, this embodiment sets an optimization constraint path length as an optimization control patch. The optimization constraint path length is a limit on the number of times the optimization data group is generated. For example, after 100 optimizations, the optimization control in this direction is stopped.

[0073] When the control optimization is performed based on a certain optimization direction, if the optimization path length (the set number of multi-feature change fitting results) has satisfied the optimization constraint path length and no optimization result satisfying the preset optimization threshold is found, the control stops the optimization. The multiple optimization fitting results obtained in the optimization process are sorted from large to small, and the maximum optimization fitting result and the multi-feature change fitting result corresponding to the maximum optimization fitting result are obtained as the local optimal value of the direction, and the local optimal value is used as the result of the control optimization, and the extraction control data of the theoretical generation of the multi-feature change fitting result is obtained as the optimization extraction control data output of the direction.

[0074] The same method as above is used to perform the optimal control of multi-feature change fitting in four optimal directions to obtain four optimal extraction control data. According to the numerical values ​​of the optimal fitting results of the four optimal control data, the optimal control data corresponding to the maximum optimal fitting result is extracted and output as the output result of the intelligent control model. The technical effect of improving the intelligence and scientificity of the gas extraction system control and reducing the safety risks of the gas extraction process is achieved.

[0075] S700: Intelligently control the coal mine gas extraction system according to the optimal extraction control data.

[0076] In one embodiment, Figure 2 As shown, the method steps provided by the present application also include:

[0077] S710: After the intelligent control of coal mine gas extraction is executed, the execution of multiple supervision points is supervised by the data acquisition sensor to generate supervision collection data;

[0078] S720: generating an optimal fitting result according to the control optimization, performing a time period deviation analysis on the optimal fitting result through the supervision collection data, and generating a deviation feedback result;

[0079] S730: Perform model optimization feedback optimization of the intelligent control model according to the deviation feedback result.

[0080] Specifically, in this embodiment, the optimal extraction control data specifically includes optimal control valve opening data and optimal extraction pump power data. Based on the optimal extraction data, the gas extraction system is controlled to extract coal mine gas in the extraction area. The data acquisition sensor is used to perform execution supervision of multiple supervision points to generate supervision acquisition data. The supervision acquisition data is the real-time gas extraction pure quantity, gas extraction concentration, extraction negative pressure, and extraction pump energy efficiency ratio obtained under the control conditions of the gas extraction system based on the optimal extraction control data. The supervision acquisition data includes multiple supervision acquisition data with time series identifiers.

[0081] The supervised acquisition data are weightedly calculated one by one according to the weight distribution relationship of the multiple feature supervised variables to obtain multiple optimal fitting results. A visualization image of the optimal fitting results changing over time is generated based on the optimal fitting results and the time series identifiers of the corresponding supervised acquisition data. A deviation analysis is performed time period by time based on the visualization image to generate a deviation feedback result, which characterizes the time node at which non-smooth data fluctuations occur in the optimal fitting results.

[0082] According to the deviation feedback result, the supervised acquisition data corresponding to the optimal fitting result and the actual extraction control data are extracted as input data to the model optimization feedback optimization of the intelligent control model, and the optimization process of step S600 is executed to obtain the optimal extraction control data of the secondary optimization to control the gas extraction system. The technical effect of avoiding the obtained optimal extraction control data from being theoretical control data and not meeting the actual working requirements of the gas extraction system is achieved, improving the practical application effectiveness of the optimal extraction control data, improving the intelligence and scientificity of the gas extraction system control, and reducing the safety risks of the gas extraction process.

[0083] In one embodiment, the method steps provided by the present application further include:

[0084] S750: Setting a control cycle node for intelligent control of extraction;

[0085] S760: When the extraction intelligent control reaches the control cycle node, the data of the current node is used as input data and input into the intelligent control model;

[0086] S770: Intelligently control the coal mine gas extraction parameters according to the output results of the intelligent control model.

[0087] In one embodiment, the method steps provided by the present application further include:

[0088] S780: Generate a deviation new node according to the deviation feedback result;

[0089] S790: Add the deviated new node to the control cycle node, and perform intelligent regulation of the sampling parameters according to the updated control cycle node.

[0090] Specifically, it should be understood that as coal mine gas extraction continues, the original ethylene concentration information, carbon monoxide concentration information, oxygen volume fraction information, extraction area temperature information, extraction area humidity information, extraction area gas pure quantity information and extraction area gas concentration information in the extraction area will change to a certain extent. Therefore, it is not realistic to achieve intelligent and scientific regulation of coal mine gas extraction based on a set of optimal extraction control data and ensure the safety and stability of the extraction process.

[0091] Therefore, this embodiment sets a control cycle node for intelligent control of extraction. When the gas extraction system is controlled based on the optimal extraction control data and reaches the control cycle node, for example, 1 hour, real-time supervision and collection data is obtained based on the data acquisition device, and the real-time supervision and collection data and the current actual extraction control data are input into the intelligent control model as the data of the current node. According to the output result of the intelligent control model, the optimal extraction control data is output again to perform intelligent control on the gas extraction system that performs coal mine gas extraction.

[0092] After the second optimization in step S730, a deviation new node is generated according to the deviation feedback result, the deviation new node replaces the time node of the first optimization, and is added to the control cycle node, and intelligent extraction control is performed according to the updated control cycle node, thereby achieving real-time dynamic adjustment of the gas extraction system control with the progress of gas extraction, improving the safety and stability of gas extraction, and reducing the technical effect of safety hazards in gas extraction.

[0093] In one embodiment, Figure 3 As shown, a coal mine gas extraction parameter intelligent control system is provided, including: a basic data acquisition module 1, a constraint condition construction module 2, a control data acquisition module 3, a real-time data acquisition module 4, a safety verification execution module 5, a data optimization execution module 6, and an intelligent control execution module 7, wherein:

[0094] Basic data collection module 1, used to collect basic data of coal mine gas extraction through interactive sensors to obtain basic data collection results;

[0095] Constraint condition construction module 2, used to construct security constraint conditions through big data, adjust the security constraint conditions according to the basic data collection results, and generate adjusted security constraint conditions;

[0096] A control data acquisition module 3, used to perform gas extraction on the coal mine gas and obtain extraction control data;

[0097] A real-time data acquisition module 4 is used to collect data of multiple parameter indicators through a data acquisition sensor to obtain a real-time monitoring data set;

[0098] A safety verification execution module 5 performs safety verification on the real-time monitoring data set based on the adjusted safety constraint condition, and executes shutdown control when any data fails to meet the adjusted safety constraint condition;

[0099] A data optimization execution module 6 is used to input the real-time monitoring data set and the extraction control data into an intelligent control model, wherein the intelligent control model includes a plurality of feature supervision variables, and the extraction control data is regulated based on the intelligent control model, and multi-feature change fitting is performed according to the control result and the real-time monitoring data set, and control optimization of multi-feature change fitting is performed through the plurality of feature supervision variables, and the optimized extraction control data is output;

[0100] The intelligent control execution module 7 is used to intelligently control the coal mine gas extraction system according to the optimal extraction control data.

[0101] In one embodiment, the system further comprises:

[0102] A data collection supervision unit is used to supervise the execution of multiple supervision points through the data collection sensor after the intelligent control of coal mine gas extraction is executed, and generate supervision collection data;

[0103] A deviation feedback execution unit, used for generating an optimal fitting result according to the control optimization, performing a time period deviation analysis on the optimal fitting result through the supervision collection data, and generating a deviation feedback result;

[0104] The optimization unit is used to perform model optimization feedback optimization of the intelligent control model according to the deviation feedback result.

[0105] In one embodiment, the system further comprises:

[0106] A characteristic variable setting unit, used for taking gas extraction concentration, gas extraction flow rate, gas extraction negative pressure and extraction pump efficiency ratio as multiple monitoring characteristic variables;

[0107] A reference value setting unit is used to set the feature correlation coefficients and basic feature satisfaction values ​​of the plurality of supervisory feature variables;

[0108] A numerical judgment execution unit, used for judging whether the multi-feature change fitting results all meet the basic feature satisfaction value when performing control optimization of multi-feature change fitting;

[0109] The optimization weighted calculation unit is used to perform optimization weighted calculation of the multiple supervisory feature variables according to the feature association coefficient when all of them meet the basic feature satisfaction value, and generate the optimization fitting result according to the weighted calculation result.

[0110] In one embodiment, the system further comprises:

[0111] A constraint threshold setting unit, used to set an efficiency constraint threshold according to the extraction basic data collection result, wherein the set efficiency constraint threshold includes a gas concentration threshold and a gas scalar threshold;

[0112] The shutdown control judgment unit is used to execute shutdown control when there is data in the real-time monitoring data set that does not meet the set efficiency constraint threshold.

[0113] In one embodiment, the system further comprises:

[0114] A path length setting unit, used to set the optimization constraint path length;

[0115] An optimization control judgment unit, used for controlling to stop the optimization when the optimization path length satisfies the optimization constraint path length and no optimization result that satisfies a preset optimization threshold is found;

[0116] The local optimal solution obtaining unit is used to read the local optimal value in the optimization process and use the local optimal value as the result of controlling the optimization.

[0117] In one embodiment, the system further comprises:

[0118] A cycle node setting unit, used to set the control cycle node of the intelligent regulation of extraction;

[0119] A model input execution unit, used for inputting data of the current node as input data into the intelligent control model when the extraction intelligent control reaches the control cycle node;

[0120] An intelligent control execution unit is used to intelligently control coal mine gas extraction parameters according to the output results of the intelligent control model.

[0121] In one embodiment, the system further comprises:

[0122] A newly added node obtaining unit, used for generating a deviated newly added node according to the deviation feedback result;

[0123] The newly added node processing unit is used to add the deviated newly added node to the control cycle node, and perform intelligent regulation of the sampling parameters according to the updated control cycle node.

[0124] For a specific embodiment of a coal mine gas extraction parameter intelligent control system, please refer to the embodiment of a coal mine gas extraction parameter intelligent control method mentioned above, which will not be repeated here. Each module in the above-mentioned coal mine gas extraction parameter intelligent control device can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0125] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store news data and data such as time attenuation factors. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for intelligent control of coal mine gas extraction parameters is implemented.

[0126] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0127] In one embodiment, a computer-readable storage medium is provided, comprising a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: collecting basic coal mine gas data through the interactive sensor to obtain basic data collection results; constructing safety constraints through big data, adjusting the safety constraints according to the basic data collection results, and generating adjusted safety constraints; performing gas extraction on the coal mine gas to obtain extraction control data; collecting data of multiple parameter indicators through the data acquisition sensor to obtain a real-time monitoring data set; performing safety verification on the real-time monitoring data set based on the adjusted safety constraints, and executing shutdown control when any data cannot meet the adjusted safety constraints; inputting the real-time monitoring data set and the extraction control data into an intelligent control model, wherein the intelligent control model includes multiple feature supervision variables, performing extraction control data control based on the intelligent control model, performing multi-feature change fitting according to the control results and the real-time monitoring data set, and performing control optimization of multi-feature change fitting through the multiple feature supervision variables, and outputting optimized extraction control data; and intelligently controlling coal mine gas extraction according to the optimized extraction control data.

[0128] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0129] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. An intelligent control system for coal mine gas extraction parameters, characterized in that: The system comprises: The basic data collection module is used to collect basic data of coal mine gas extraction through interactive sensors to obtain the basic data collection results of extraction; A constraint condition construction module is used to construct safety constraint conditions through big data, adjust the safety constraint conditions according to the collection results of the basic data extraction, and generate adjusted safety constraint conditions; A control data acquisition module, used to perform gas extraction on the coal mine gas and obtain extraction control data; A real-time data acquisition module is used to collect data of multiple gas extraction parameter indicators through data acquisition sensors to obtain a real-time monitoring data set; A safety verification execution module performs safety verification on the real-time monitoring data set based on the adjusted safety constraint condition, and executes shutdown control when any data fails to meet the adjusted safety constraint condition; A data optimization execution module, used for inputting the real-time monitoring data set and the extraction control data into an intelligent control model, wherein the intelligent control model includes a plurality of feature supervision variables, performing control of the extraction control data based on the intelligent control model, performing multi-feature change fitting according to the control result and the real-time monitoring data set, and performing control optimization of multi-feature change fitting through the plurality of feature supervision variables, and outputting optimized extraction control data; An intelligent control execution module, used for intelligently controlling the coal mine gas extraction system according to the optimal extraction control data; The system comprises: A data collection supervision unit is used to supervise the execution of multiple supervision points through the data collection sensor after the intelligent control of coal mine gas extraction is executed, and generate supervision collection data; A deviation feedback execution unit, used for generating an optimal fitting result according to the control optimization, performing a time period deviation analysis on the optimal fitting result through the supervision collection data, and generating a deviation feedback result; An optimization feedback unit, used for performing model optimization feedback optimization of the intelligent control model according to the deviation feedback result; A characteristic variable setting unit, used for taking gas extraction concentration, gas extraction flow rate, gas extraction negative pressure and extraction pump efficiency ratio as multiple monitoring characteristic variables; A reference value setting unit is used to set the feature correlation coefficients and basic feature satisfaction values ​​of the plurality of supervisory feature variables; A numerical judgment execution unit, used for judging whether the multi-feature change fitting results all meet the basic feature satisfaction value when performing control optimization of multi-feature change fitting; An optimization weighted calculation unit, used for performing optimization weighted calculation of the plurality of supervisory feature variables according to the feature association coefficient when all of them meet the basic feature satisfaction value, and generating the optimization fitting result according to the weighted calculation result; The system comprises: A path length setting unit, used to set the optimization constraint path length; An optimization control judgment unit, used for controlling to stop the optimization when the optimization path length satisfies the optimization constraint path length and no optimization result that satisfies a preset optimization threshold is found; A local optimal solution obtaining unit, used for reading the local optimal value in the optimization process, and taking the local optimal value as the result of the control optimization; The system comprises: A cycle node setting unit, used to set the control cycle node of the intelligent regulation of extraction; A model input execution unit, used for inputting data of the current node as input data into the intelligent control model when the extraction intelligent control reaches the control cycle node; An intelligent control execution unit, used for intelligently controlling coal mine gas extraction parameters according to the output results of the intelligent control model; The system comprises: A newly added node obtaining unit, used for generating a deviated newly added node according to the deviation feedback result; The newly added node processing unit is used to add the deviated newly added node to the control cycle node, and perform intelligent regulation of the sampling parameters according to the updated control cycle node.

2. The system according to claim 1, characterized in that The system comprises: A constraint threshold setting unit, used to set an efficiency constraint threshold according to the extraction basic data collection result, wherein the set efficiency constraint threshold includes a gas concentration threshold and a gas scalar threshold; The shutdown control judgment unit is used to execute shutdown control when there is data in the real-time monitoring data set that does not meet the set efficiency constraint threshold.

3. A method for intelligently controlling coal mine gas extraction parameters, characterized in that: The method is applied to the intelligent control system for coal mine gas extraction parameters according to any one of claims 1 to 2, wherein the intelligent control system for coal mine gas extraction parameters is communicatively connected with a data acquisition sensor and an interactive sensor, and the method comprises: Collecting basic data of coal mine gas extraction through the interactive sensor to obtain basic extraction data collection results; Constructing safety constraints through big data, adjusting the safety constraints according to the basic data collection results, and generating adjusted safety constraints; Performing gas extraction on the coal mine gas to obtain extraction control data; The data acquisition sensor is used to collect data of multiple gas extraction parameter indicators to obtain a real-time monitoring data set; Performing safety verification on the real-time monitoring data set based on the adjusted safety constraint condition, and executing shutdown control when any data fails to meet the adjusted safety constraint condition; Input the real-time monitoring data set and the extraction control data into an intelligent control model, wherein the intelligent control model includes a plurality of feature supervision variables, and control the extraction control data based on the intelligent control model, and perform multi-feature change fitting according to the control result and the real-time monitoring data set, and perform control optimization of multi-feature change fitting through the plurality of feature supervision variables, and output optimized extraction control data; The coal mine gas extraction system is intelligently controlled according to the optimal extraction control data.

4. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method for intelligent control of coal mine gas extraction parameters described in claim 3 are implemented.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the method for intelligent control of coal mine gas extraction parameters described in claim 3 are implemented.

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