An online intelligent monitoring and early warning system and method for preventing sudden attacks

Abstract

This invention relates to an online intelligent monitoring and early warning system and method for preventing coal mine gas outbursts, belonging to the field of coal mine safety technology. The system employs a multi-system, multi-source data real-time interactive data management platform. First, it collects test data, environmental data, video data, and audio data in real time during outburst prevention operations, and also collects data from the safety monitoring system through an external monitoring system. Then, it automatically cleans, integrates, and analyzes the collected data, extracting key features. Using AI intelligent recognition, it automatically identifies and calculates the thickness, borehole depth, and dip angle of coal seams and soft strata, performing real-time prediction and early warning, and evaluating the compliance of on-site personnel's operations. Finally, it uses deep learning, artificial intelligence technology, and various algorithm models to automatically analyze and issue early warnings for outburst hazards and anomalies in mining operations. It also generates digital drawings, tables, documents, and other paper-based outburst prevention information.

Description

Technical Field

[0001] This invention belongs to the field of coal mine safety technology and relates to an online intelligent monitoring and early warning system and method for preventing coal gas outbursts. Background Technology

[0002] Coal mine gas accidents include gas explosions, coal and gas outbursts, gas asphyxiation, and gas combustion, with coal and gas outbursts being a major hazard in coal mine production. Currently, the data processing and analysis capabilities of domestic coal mine outburst early warning information systems are relatively limited, making it impossible to process and analyze large-scale data in real time. Furthermore, current coal and gas outburst disaster monitoring methods suffer from an excessive number of static indicators, relatively rigid indicators and models, and low universality, affecting the system's real-time performance and accuracy.

[0003] The main problems in current gas outburst prevention operations include: monitoring information is distributed across different systems; drilling operations are difficult to control; the standardization of gas outburst parameter sampling is affected by human factors; changes in the geological environment require manual observation; outburst precursors such as blowouts may not be identified and reported in a timely manner; abnormal gas outbursts cannot be warned in advance; monitoring information at the working face cannot be automatically integrated and analyzed; and there are no real-time alarms or early warnings.

[0004] To address the aforementioned issues, a comprehensive intelligent early warning information system for coal mine outbursts needs to be established. This system would integrate existing monitoring information and algorithms, and develop new technical solutions to achieve automatic data collection, integration, analysis, and processing. It would provide real-time monitoring and early warning for mine outburst prevention operations and working faces, eliminating the possibility of falsified outburst prevention parameters and the influence of human factors such as observed dynamic phenomena. Simultaneously, it would provide reliable technical safeguards for issues such as drilling quality, timely identification of outburst precursors, and changes in the geological environment, ensuring the system's stability, safety, and accuracy. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide an online intelligent monitoring and early warning system and method for preventing sudden incidents.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] An online intelligent monitoring and early warning system for preventing sudden attacks, the method includes the following steps: a multi-source data acquisition system, a multi-source cross-domain simulation and prediction system, and a digital decision support system;

[0008] The multi-source data acquisition system includes internal and external data sources; the internal data acquisition includes a video communication terminal, a digital azimuth measurement terminal, and a gas parameter predictor; the video communication terminal includes a camera module, an audio acquisition module, an environmental acquisition module, a real-time communication module, and a data analysis module; the pre-processed data is transmitted through the transmission layer to the multi-source cross-domain simulation prediction system and the digital decision support system;

[0009] The multi-source cross-domain simulation prediction system includes a video data storage module, an AI model analysis module, and an intelligent early warning module. The AI ​​model analysis module uses computer vision technology and pattern recognition algorithms to classify and identify abnormal noises of dynamic phenomena and precursors of coal and gas outbursts.

[0010] The digital decision support system includes a data storage module, a prominent trend early warning module, an intelligent decision-making module, and an anti-outbreak report generation module. It uses computer technology and mathematical models to perform decision analysis, providing decision support and decision execution for the online intelligent monitoring and early warning system for anti-outbreak operations.

[0011] Optionally, the video communication terminal is installed within 100 meters of the work site and transmits data wirelessly, transmitting in real time video information, audio information, drilling construction and gas outburst parameters collected by the video communication terminal, digital azimuth measurement terminal, and gas parameter predictor WTC or TWY.

[0012] Optionally, the video communication terminal includes a camera module, an audio acquisition module, an environmental acquisition module, a real-time communication module, and a data analysis module. It is carried by the anti-outburst testing personnel and placed within the effective range of the operation monitoring. Before the operation, the personnel take photos of the coal wall and construction tools as evidence and upload the data in real time.

[0013] Optionally, the digital azimuth measurement terminal measures the hole position, azimuth, and inclination before drilling, measures the hole depth after drilling, and uploads the above measurement parameters in real time.

[0014] A method for online intelligent monitoring and early warning of potential emergencies, comprising the following steps:

[0015] S1: The monitoring center sets up and measures information on the working face area, coal seam and geological information, and reads information from mobile terminal devices;

[0016] S2: Start the video communication terminal and digital display azimuth measurement terminal, highlight the parameter measuring instrument, connect to the network, and synchronously test the working face information;

[0017] S3: Take images of the coal face and drilling tools to determine the thickness, dip angle, and structure of the coal seam;

[0018] S4: Identify the location and thickness of coal seams and soft strata, calculate drill string data, and automatically generate reference data for borehole opening locations;

[0019] S5: Determine the drilling location and generate the drilling construction drawings for the measures;

[0020] S6: Determine the drilling location, orientation, and data of the drilling rig, and automatically store and upload the data;

[0021] S7: The mobile terminal module for collecting environmental parameters can be activated to detect gas and temperature data at the work site in real time, and automatically store and upload the data.

[0022] S8: Automatically collects current borehole test data using a gas outburst parameter measuring instrument and uploads it to the data storage system in real time; (Passes and uploads automatically);

[0023] S9: The AI ​​model analysis module intelligently identifies abnormal noises such as blowouts, drill jamming, and stuck drill dynamic phenomena, as well as coal bursts, splitting sounds, and buzzing sounds, which are precursors to coal and gas outbursts. It also analyzes the compliance of on-site operators' operations, extracts abnormal videos and audios, and judges abnormal characteristics and violations. If an abnormality occurs during the current operation, it will promptly issue a warning through the video communication terminal, prompting the user to stop the operation or take measures.

[0024] S10: The AI ​​model analysis module intelligently and automatically counts the number of drill rods, automatically calculates the drilling depth, and automatically uploads the data to the data storage system;

[0025] S11: After the current drilling test is completed, check the drilling opening orientation again, verify the final hole location and orientation parameters, and upload them to the data storage system.

[0026] S12: During the current drilling test completion and drill withdrawal process, count the number of drill rods withdrawn, verify the number of drill rods used in construction, calculate and verify the drilling depth, and upload the data to the data storage system;

[0027] S13: The intelligent early warning service system integrates and classifies all data collected in the current anti-intrusion work, and automatically generates paper-based anti-intrusion information and early warning information in the form of digital drawings, tables and documents;

[0028] S14: Proceed to the next round of testing.

[0029] The beneficial effects of this invention are as follows: by integrating existing monitoring information and algorithms, and developing new technical solutions, it achieves automatic data collection, integration, analysis, and processing. It enables real-time monitoring and early warning of mine outburst prevention operations and mining faces, eliminating the possibility of falsifying outburst prevention parameters and the influence of human factors such as dynamic phenomena. Simultaneously, it provides reliable technical safeguards for issues such as drilling quality, timely identification of outburst precursors, and changes in the geological environment, ensuring the system's stability, safety, and accuracy.

[0030] 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

[0031] 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:

[0032] Figure 1 Organizational structure diagram of the online monitoring and intelligent early warning system for anti-outburst defense provided by the present invention;

[0033] Figure 2 This invention provides a functional association diagram between the online monitoring and intelligent early warning system for preventing sudden incidents and the video communication terminal.

[0034] Figure 3 The flowchart illustrates the key steps in the gas outburst parameter measurement method provided by this invention. Detailed Implementation

[0035] 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.

[0036] 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.

[0037] 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.

[0038] Organizational Structure of the Online Monitoring and Intelligent Early Warning System for Emergency Response Figure 1 As shown.

[0039] The early warning system mainly consists of two parts: hardware and software. The hardware includes a video communication terminal, a digital azimuth measurement terminal, a gas parameter predictor, an intrinsically safe multi-protocol gateway, a data protocol gateway, a video data storage module, an AI model analysis module, and an intelligent early warning module.

[0040] 1. The video communication terminal includes a camera module, an audio acquisition module, an environmental acquisition module, a real-time communication module, and a data analysis module. Pre-processed data is transmitted via the transmission layer to multi-source cross-domain simulation prediction systems and digital decision support systems, such as... Figure 2 As shown.

[0041] 2. The digital azimuth measurement terminal can collect borehole opening data and upload it in real time to the multi-source cross-domain simulation prediction system and digital decision support system.

[0042] 3. The gas parameter predictor is mainly used to collect gas parameters, outburst parameters and other outburst prevention test data, and upload them in real time to the multi-source cross-domain simulation prediction system and digital decision support system.

[0043] 4. The video communication terminal transmits data via wired or wireless means (Ethernet, WIFI, Bluetooth, 4G / 5G, etc.) and transmits in real time the gas parameters and other anti-outburst test data collected by the video communication terminal, digital azimuth measurement terminal, and gas parameter predictor (WTC, TWY).

[0044] 5. The Intrinsically Secure Multi-Protocol Gateway is used for data conversion, transmission, and exchange between different platforms, networks, and protocols, enabling communication between various networks.

[0045] 6. Data protocol gateways are mainly used to effectively separate and convert data between different devices and systems.

[0046] 7. The video storage module is used to store video and audio data collected at the work site.

[0047] 8. The AI ​​analysis module uses AI voice / image intelligent recognition technology to achieve human operation recognition, intelligent image calculation, abnormal image recognition, and abnormal audio recognition.

[0048] 9. The data storage module, intelligent early warning module, and decision-making module are used to store internal and external data sources, parse data, and process parameter data and outburst detection data collected from external systems and the field, enabling online monitoring, early warning, real-time forecasting, and trend prediction of outburst hazards. Simultaneously, based on uploaded electronic outburst prevention information such as borehole trajectories, they quickly generate digital drawings, tables, documents, and other paper-based outburst prevention information.

[0049] The flowchart of key steps in the gas outburst parameter determination process is as follows: Figure 3As shown:

[0050] S1: First, the monitoring center sets up the measurement of working face area information, coal seam and geological information, and reads information from mobile terminal devices;

[0051] S2: Start the video communication terminal, digital display azimuth measurement terminal, and other equipment such as the parameter measuring instrument, connect to the network, and synchronously test the working face information;

[0052] S3: Before performing the outburst parameter measurement, take images of the coal face and drill bit to determine the thickness, dip angle and structure of the coal seam;

[0053] S4: Identify the location and thickness of coal seams and soft strata, calculate drill bit data, and automatically generate reference data such as borehole opening locations;

[0054] S5: Determine the drilling location and generate the drilling construction drawings for the measures;

[0055] S6: Measure data such as the drilling position and orientation of the drilling rig, and automatically store and upload the data;

[0056] S7: The mobile terminal for video acquisition can collect environmental parameters, detect environmental data such as gas and temperature at the work site in real time, and automatically store and upload the data.

[0057] S8: Automatically collects current borehole test data through a gas outburst parameter measuring instrument and uploads it to the data storage system in real time; passes and is automatically uploaded.

[0058] S9: The AI ​​model analysis module intelligently identifies dynamic phenomena such as blowouts, drill jamming, and stuck drills, as well as abnormal sounds that are precursors to coal and gas outbursts, such as coal popping, splitting sounds, and buzzing sounds. It also analyzes and assesses the compliance of on-site personnel's operations, extracts abnormal video and audio, and determines whether there are any features or violations detected by the real-time video and audio capture system via the video communication terminal. If an abnormality occurs during the current operation, a timely warning is issued via the video communication terminal, prompting the user to stop the operation or take appropriate measures.

[0059] S10: The AI ​​model analysis module intelligently and automatically counts the number of drill rods, automatically calculates the drilling depth, and automatically uploads the data to the data storage system;

[0060] S11: After the current drilling test is completed, check the drilling opening orientation again, verify the final hole location, orientation and other parameters, and automatically upload them to the data storage system.

[0061] S12: During the current drilling test completion and drill withdrawal process, count the number of drill rods withdrawn, verify the number of drill rods used in construction, automatically calculate and verify the drilling depth, and automatically upload the data to the data storage system;

[0062] S13: The intelligent early warning service system uses data processing algorithms to automatically generate digital drawings, tables, documents and other paper-based anti-outburst information and early warning information from all data collected in the current test borehole.

[0063] S14: Proceed to the next round of testing.

[0064] 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. An online intelligent monitoring and early warning system for preventing sudden attacks, characterized in that: The system includes: a multi-source data acquisition system, a multi-source cross-domain simulation and prediction system, and a digital decision support system; The multi-source data acquisition system includes internal and external data sources; the internal data acquisition includes a video communication terminal, a digital azimuth measurement terminal, and a gas parameter predictor; the video communication terminal includes a camera module, an audio acquisition module, an environmental acquisition module, a real-time communication module, and a data analysis module; the pre-processed data is transmitted through the transmission layer to the multi-source cross-domain simulation prediction system and the digital decision support system; The multi-source cross-domain simulation prediction system includes a video data storage module, an AI model analysis module, and an intelligent early warning module. The AI ​​model analysis module uses computer vision technology and pattern recognition algorithms to classify and identify abnormal noises of dynamic phenomena and precursors of coal and gas outbursts. The digital decision support system includes a data storage module, a prominent trend early warning module, an intelligent decision-making module, and an anti-outbreak report generation module. It uses computer technology and mathematical models to perform decision analysis, providing decision support and decision execution for the online intelligent monitoring and early warning system for anti-outbreak operations. The digital azimuth measurement terminal measures the hole position, azimuth, and inclination before drilling, and measures the hole depth after drilling is completed, and uploads the above measurement parameters in real time.

2. The online intelligent monitoring and early warning system for preventing sudden attacks according to claim 1, characterized in that: The video communication terminal is installed within 100 meters of the work site and transmits data wirelessly in real time, including video and audio information, drilling and gas outburst parameters collected by the video communication terminal, digital azimuth measurement terminal, and gas parameter predictor WTC or TWY.

3. A method for online intelligent monitoring and early warning of potential incidents using the monitoring and early warning system described in claim 1 or 2, characterized in that: The method includes the following steps: S1: The monitoring center sets up and measures information on the working face area, coal seam and geological information, and reads information from mobile terminal devices; S2: Start the video communication terminal and digital display azimuth measurement terminal, highlight the parameter measuring instrument, connect to the network, and synchronously test the working face information; S3: Take images of the coal face and drilling tools to determine the thickness, dip angle, and structure of the coal seam; S4: Identify the location and thickness of coal seams and soft strata, calculate drill string data, and automatically generate reference data for borehole opening locations; S5: Determine the drilling location and generate the drilling construction drawings for the measures; S6: Determine the drilling location, orientation, and data of the drilling rig, and automatically store and upload the data; S7: The mobile terminal module for collecting environmental parameters can be activated to detect gas and temperature data at the work site in real time, and automatically store and upload the data. S8: Automatically collects current borehole test data using a gas outburst parameter measuring instrument and uploads it to the data storage system in real time; (Passes and uploads automatically); S9: The AI ​​model analysis module intelligently identifies abnormal noises such as blowouts, drill jamming, and stuck drill dynamic phenomena, as well as coal bursts, splitting sounds, and buzzing sounds, which are precursors to coal and gas outbursts. It also analyzes the compliance of on-site operators' operations, extracts abnormal videos and audios, and judges abnormal characteristics and violations. If an abnormality occurs during the current operation, it will promptly issue a warning through the video communication terminal, prompting the user to stop the operation or take measures. S10: The AI ​​model analysis module intelligently and automatically counts the number of drill rods, automatically calculates the drilling depth, and automatically uploads the data to the data storage system; S11: After the current drilling test is completed, check the drilling opening orientation again, verify the final hole location and orientation parameters, and upload them to the data storage system. S12: During the current drilling test completion and drill withdrawal process, count the number of drill rods withdrawn, verify the number of drill rods used in construction, calculate and verify the drilling depth, and upload the data to the data storage system; S13: The intelligent early warning service system integrates and classifies all data collected in the current anti-intrusion work, and automatically generates paper-based anti-intrusion information and early warning information in the form of digital drawings, tables and documents; S14: Proceed to the next round of testing.

Images