Fully mechanized caving mining liquid nitrogen intervention efficient dust fall and coal gangue infrared identification method

Abstract

The invention belongs to the technical field of coal mine underground fully-mechanized caving mining coal gangue mixing degree recognition and underground dust prevention, and particularly discloses a fully-mechanized caving mining liquid nitrogen intervention efficient dust falling and coal gangue infrared recognition method which comprises the following steps that S1, a system is installed; the system comprises a liquid nitrogen dust falling system, a coal gangue infrared identification system and a computer control system, s2, debugging and parameter optimization are carried out on a liquid nitrogen dust fall system and a coal gangue infrared identification system; s3, operating and detecting a liquid nitrogen dust falling system and a coal gangue infrared identification system; and S4, starting a liquid nitrogen dust falling system and a coal gangue infrared identification system. By the adoption of the fully mechanized caving mining liquid nitrogen intervention efficient dust falling and coal gangue infrared identification method, the problems that in the prior art, the dust falling effect is poor, and coal gangue identification is inaccurate can be solved.

Description

Technical Field

[0001] This invention belongs to the field of underground fully mechanized longwall mining and underground dust control technology, specifically relating to a method for efficient dust suppression using liquid nitrogen and infrared identification of coal gangue in fully mechanized longwall mining. Background Technology

[0002] Coal-fired power generation still accounts for a significant proportion of global electricity supply. Increased coal mining ensures stable power supply and meets the growing demands of industrial and residential electricity consumption. Gangue, a byproduct extracted along with coal during mining, releases numerous toxic and harmful gases (CO, H2S, SO2, etc.) during combustion if not properly separated. This causes significant pollution, damages the living environment, harms human health, and contradicts national requirements for the clean utilization of coal resources. Furthermore, accumulated gangue releases greenhouse gases. Under natural conditions, gangue within gangue piles may undergo slow oxidation reactions, releasing gases such as carbon dioxide and methane, exacerbating global warming.

[0003] Intelligent coal mining is an important way to promote the high-quality development of the coal industry and realize the green development and low-carbon clean utilization of coal resources. However, the intelligentization of fully mechanized longwall mining in coal mines is quite difficult, and accurate identification of coal and gangue is a key link in realizing intelligent longwall mining. Therefore, coal and gangue need to be separated in actual production. Traditional manual separation methods are labor-intensive and have low efficiency, and have been gradually phased out. At present, the main methods for separating coal and gangue include heavy media coal preparation, jigging coal preparation, flotation, dry coal preparation, and gamma-ray detection, which generally suffer from problems such as high investment costs, low separation efficiency, and serious environmental pollution.

[0004] Therefore, there is a need in this field to develop a method for efficient dust suppression using liquid nitrogen and infrared identification of coal gangue in integrated underground top coal caving mining, which can effectively solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining, which can solve the problems of poor dust suppression effect and inaccurate coal gangue identification in the prior art.

[0006] To achieve the above objectives, this invention provides a method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining, comprising the following steps:

[0007] Step S1: Install the system; the system includes a liquid nitrogen dust suppression system, a coal gangue infrared identification system, and a computer control system;

[0008] Step S2: Debug and optimize the parameters of the liquid nitrogen dust suppression system and the coal gangue infrared identification system;

[0009] Step S3: Operate and test the liquid nitrogen dust suppression system and the coal gangue infrared identification system;

[0010] Step S4: Start the liquid nitrogen dust suppression system and the coal gangue infrared identification system.

[0011] Preferably, in step S1, the liquid nitrogen dust suppression system includes a liquid nitrogen storage tank, a high-pressure conveying pipeline, and a liquid nitrogen nozzle, with the two ends of the high-pressure conveying pipeline connected to the liquid nitrogen storage tank and the liquid nitrogen nozzle, respectively.

[0012] The high-pressure delivery pipeline is equipped with pressure sensors and flow regulating valves to detect local pressure fluctuations, enabling timely detection of anomalies in the pipeline section and ensuring precise control. The liquid nitrogen nozzle has a multi-nozzle structure, with each nozzle independently adjustable in terms of spray angle and range. The liquid nitrogen nozzle is equipped with a heating device, which utilizes explosion-proof electric heating elements. During system shutdown or maintenance, electrical energy is converted into heat to heat the nozzle, melting residual liquid nitrogen or ice crystals to prevent blockage. The heating process is monitored in real-time by a temperature sensor to ensure the temperature remains within a safe range and avoids overheating. Simultaneously, the device is linked to a computer control system, dynamically adjusting the heating power and duration based on the nozzle status. Explosion-proof design and multiple protection mechanisms are employed to balance downhole operation safety and equipment stability, effectively ensuring long-term unobstructed operation and extended service life of the nozzle.

[0013] The inner wall of the high-pressure transmission pipeline is made of low-temperature wear-resistant material.

[0014] Preferably, in step S1, the coal and gangue infrared identification system includes an infrared camera, which is equipped with an infrared image sensor; the infrared camera acquires coal and gangue images during the top coal caving process, and the infrared image sensor identifies the coal and gangue to distinguish different substances.

[0015] Preferably, in step S1, the computer control system works in conjunction with the liquid nitrogen dust suppression system and the coal gangue infrared identification system to enhance the accuracy of the coal gangue infrared identification system while reducing dust. At the same time, the coal gangue identification results are fed back to the liquid nitrogen dust suppression system to optimize the dust suppression parameters of the liquid nitrogen dust suppression system. The computer control system adjusts the injection volume and frequency of liquid nitrogen in the liquid nitrogen dust suppression system in real time according to the gangue content. When the coal gangue infrared identification system detects a high proportion of coal gangue, the injection volume and frequency of liquid nitrogen in the liquid nitrogen dust suppression system are increased to improve the dust suppression effect, thereby improving the accuracy of coal gangue identification. The computer control system receives signals from the infrared image sensor and controls the working status of the liquid nitrogen dust suppression system.

[0016] Preferably, step S1 specifically involves setting up liquid nitrogen nozzles and pressure sensors based on the actual conditions of the fully mechanized longwall mining face. The input end of the liquid nitrogen nozzles is connected to a liquid nitrogen storage tank and a high-pressure conveying pipeline. The computer control system is electrically connected to the liquid nitrogen dust suppression system and the coal gangue infrared identification system, respectively.

[0017] Preferably, step S2 specifically involves:

[0018] Step S21: Install a high-precision infrared camera below the tail beam of the hydraulic support in the fully mechanized longwall mining face to quickly collect infrared image data of coal and gangue, and transmit the collected data to the data analysis and processing center underground.

[0019] Step S22: Establish a large database of coal and gangue infrared images, collect infrared image data of coal and gangue samples from different origins and of different qualities, and use deep learning algorithms to analyze and train the infrared image data of coal and gangue samples.

[0020] Step S23: The data analysis and processing center performs real-time analysis on the collected infrared image data. If gangue is identified, a signal is immediately sent to the sorting device on the conveyor belt.

[0021] Step S24: The sorting device uses a robotic arm or pneumatic baffle structure to quickly separate the gangue from the coal flow and transport the gangue to the designated gangue collection area.

[0022] Step S25: Connect the coal gangue infrared identification system to the automated control system of the entire fully mechanized longwall mining operation. When the gangue content is too high, automatically adjust the top coal caving process of the fully mechanized longwall mining face.

[0023] Preferably, step S3 specifically involves:

[0024] Step S31: The liquid nitrogen dust suppression system is in operation;

[0025] Step S311, Automation Control Logic: Construct an intelligent control center based on PLC or DCS, connect it with the operating signals of the hydraulic support and the rear scraper conveyor fully mechanized mining equipment, and obtain their working status information;

[0026] Step S312: Based on the working status information, automatically calculate the optimal injection parameters of liquid nitrogen according to the preset algorithm, including injection pressure, flow rate, nozzle angle and number of openings, and control the liquid nitrogen supply system and injection device in real time to perform precise operation.

[0027] Step S313, Coordination of liquid nitrogen dust suppression system and ventilation system: Combine liquid nitrogen dust suppression system with underground ventilation system, optimize the position and angle of liquid nitrogen injection according to ventilation airflow direction, wind speed and air volume parameters, so that liquid nitrogen and airflow work together;

[0028] Step S32: The coal gangue infrared identification system is in operation;

[0029] Step S33: Testing the liquid nitrogen dust suppression system;

[0030] Step S34: Coal gangue infrared identification system detection;

[0031] Step S341, Identification Accuracy Detection: Establish a coal gangue identification accuracy detection mechanism, regularly collect samples from coal gangue mixtures, use manual sorting or other high-precision detection methods to determine the true proportion of coal gangue in the samples, then use these samples to identify and analyze them through a coal gangue infrared identification system, compare the identification results with the true proportion, and calculate the identification accuracy.

[0032] Step S342, Data Transmission and System Response Detection: Detect the data transmission lines and the response speed of the control system in the coal gangue infrared identification system.

[0033] Preferably, step S312 specifically involves:

[0034] a. Establish normal mining dust suppression mode, high dust concentration emergency mode and equipment maintenance mode; under normal mining dust suppression mode, set stable liquid nitrogen injection parameters according to the normal dust generation range to maintain the basic dust suppression effect of the fully mechanized mining face.

[0035] b. When the dust monitoring sensor detects that the dust concentration instantly exceeds the preset high warning value, the system automatically switches to the high dust concentration emergency mode. At this time, the liquid nitrogen injection volume and coverage are greatly increased to quickly reduce the dust concentration in the air.

[0036] c. In equipment maintenance mode, stop liquid nitrogen injection and only maintain the system's pressure monitoring and equipment inspection functions to ensure that the equipment is in a safe standby state so that equipment maintenance and repair work can be carried out.

[0037] Preferably, steps S32 and S33 are specifically as follows:

[0038] Step S321, Real-time data acquisition and transmission: Install one infrared camera under the tail beam of each hydraulic support in the fully mechanized longwall mining face; set up a data verification and retransmission mechanism, and use a high-speed data transmission line to transmit the acquired infrared image data to the data analysis server located in the underground monitoring room or the ground dispatch center in real time.

[0039] Step S322, Online Identification and Decision-Making: After receiving the infrared image data, the data analysis server immediately uses a pre-trained deep learning model to perform coal gangue identification and analysis;

[0040] If gangue is identified, the computer control system calculates the optimal top coal caving process for the fully mechanized longwall face and the sorting action parameters of the coal and gangue sorting device in the transport roadway based on information such as the location and size of the gangue and the running speed of the conveyor belt, and sends control commands to the coal and gangue sorting device.

[0041] Step S323, Self-learning and Model Update: The coal gangue infrared identification system has a self-learning function. During operation, it continuously collects new coal gangue infrared image data and compares and analyzes it with existing sample data.

[0042] When new data features are found to be mismatched with or deviate from the existing model, the model update mechanism is automatically activated to retrain and optimize the deep learning model using the new data; when new coal seams are mined or geological conditions change and the characteristics of coal gangue change, the coal gangue infrared recognition system automatically senses and adjusts the recognition model.

[0043] Step S331, Liquid nitrogen parameter monitoring: Install several monitoring devices such as pressure sensors, temperature sensors, flow sensors and liquid level sensors in key parts such as liquid nitrogen storage tanks, delivery pipelines and nozzles to monitor the pressure, temperature, flow rate and storage volume of liquid nitrogen in real time.

[0044] The parameters are transmitted to the monitoring system, and reasonable parameter thresholds are set. When an abnormality in liquid nitrogen parameters is detected, the liquid nitrogen dust suppression system immediately issues an alarm signal and displays the location and specific value of the abnormal parameters.

[0045] Step S332, Spraying effect test: Set up dust concentration monitoring instruments at several locations in the fully mechanized longwall mining face to monitor the changes in dust concentration before and after dust suppression, and evaluate the dust suppression effect of the liquid nitrogen spraying system.

[0046] Step S333, Equipment Operation Status Detection: Real-time monitoring of the operation status of pumps, valves, and pipeline connection components in the liquid nitrogen dust suppression system.

[0047] Preferably, step S4 specifically involves:

[0048] Step S41: Start the liquid nitrogen dust suppression system;

[0049] Step S411: Start the liquid nitrogen dust suppression system. After the system starts, the central control system automatically adjusts the speed of the liquid nitrogen pump and the opening of the valve according to the dust concentration and the working status of the hydraulic support, thereby controlling the flow rate and injection pressure of the liquid nitrogen.

[0050] Step S412: Install dust concentration sensors, wind speed sensors, and hydraulic support position and operation status sensors on the fully mechanized longwall mining face to collect real-time information on dust concentration, ventilation wind speed, and hydraulic support operation status, and transmit these signals to the central control system.

[0051] Step S413: Install several liquid nitrogen nozzles at different locations on the fully mechanized longwall mining face. Each liquid nitrogen nozzle is equipped with an angle adjustment mechanism and a solenoid valve. The central control system controls the opening and closing of the solenoid valve and the angle of the liquid nitrogen nozzle based on sensor information and the preset dust suppression strategy.

[0052] Step S42: The coal gangue infrared identification system is activated;

[0053] Step S421: Start the coal gangue infrared identification system to perform real-time infrared detection on the coal gangue mixture, collect infrared image data of the coal gangue, and transmit the data to the data processing unit;

[0054] Step S422: After receiving the infrared image data, the data processing unit first performs preprocessing, including data filtering, noise reduction, and normalization. Then, it compares and analyzes the processed data with the pre-stored coal gangue infrared image feature database, and uses pattern recognition algorithms or machine learning models to identify the type and distribution of coal gangue.

[0055] Step S423: Based on the coal and gangue identification results, the data processing unit generates corresponding control commands and transmits the commands to the coal and gangue sorting device.

[0056] The present invention employs the above-mentioned method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining, and its beneficial effects are as follows:

[0057] (1) The purpose of the increased coal mining in this invention is to reduce the waste of coal resources and lay a solid foundation for economic development; to reduce the mining and transportation costs, reduce the land occupation caused by gangue accumulation and the potential environmental pollution risk, and reduce ecological pressure from the source; among them, dust reduction is a key measure to improve the mining environment and protect the health of miners.

[0058] (2) This invention optimizes mining processes, upgrades ventilation equipment, and adopts efficient spray dust suppression systems to minimize the suspension and diffusion of dust in the air and create a clean working space.

[0059] (3) Since promoting intelligent development is the core path for the coal industry to move towards modernization, this invention utilizes advanced sensor technology, big data analysis, artificial intelligence and automated control methods to achieve precise, efficient and safe coal mining; enabling the coal industry to achieve green, sustainable and high-quality development in the wave of intelligentization.

[0060] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating an embodiment of the present invention: a method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining.

[0062] Figure 2 This is a schematic diagram of the system composition of an embodiment of the method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to the present invention;

[0063] Figure 3 This is a diagram of a liquid nitrogen dust suppression system according to an embodiment of the present invention, which describes a method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining. Detailed Implementation

[0064] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0065] Example

[0066] like Figures 1-3 As shown, a method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining includes the following steps:

[0067] Step S1: Install the system. The system includes a liquid nitrogen dust suppression system, a coal gangue infrared identification system, and a computer control system.

[0068] The liquid nitrogen dust suppression system includes a liquid nitrogen storage tank, a high-pressure delivery pipeline, and liquid nitrogen nozzles. The high-pressure delivery pipeline is connected to both the liquid nitrogen storage tank and the liquid nitrogen nozzles. Based on the actual conditions of the longwall top-coal caving mining face, liquid nitrogen nozzles are installed. The input end of each liquid nitrogen nozzle is connected to both the liquid nitrogen storage tank and the high-pressure delivery pipeline to ensure the system's sealing and safety. The computer control system is electrically connected to both the liquid nitrogen dust suppression system and the coal gangue infrared identification system.

[0069] Mining wireless communication equipment utilizes explosion-proof wireless communication base stations deployed in fully mechanized longwall mining faces to support multi-node networking underground. This enables real-time data transmission between the liquid nitrogen dust suppression system, the coal gangue infrared identification system, and the computer control system. The communication equipment employs low-power, interference-resistant wireless protocols (such as LoRa or 5G mining private networks) to ensure stable signal transmission in complex underground environments.

[0070] This embodiment features a specially designed liquid nitrogen storage tank with excellent thermal insulation properties to minimize evaporation loss. The inner wall of the high-pressure delivery pipeline is made of a low-temperature wear-resistant material to ensure the stability of the liquid nitrogen during transportation. The high-pressure delivery pipeline is equipped with pressure sensors and flow control valves to precisely control the delivery pressure and flow rate of the liquid nitrogen based on real-time monitoring data of the size of the fully mechanized longwall face, the operating speed of the rear scraper conveyor, and the amount of dust generated.

[0071] Liquid nitrogen storage tanks store liquid nitrogen, which is then transported to nozzles via pipelines. These nozzles are installed at appropriate locations within the longwall mining face to spray the liquid nitrogen into the air for efficient dust suppression. The liquid nitrogen nozzles feature a multi-nozzle structure, with each nozzle independently adjustable in terms of spray angle and range. This design ensures uniform atomization of the liquid nitrogen, enhancing dust suppression effectiveness. It is used to spray liquid nitrogen into the longwall mining area to reduce coal dust generation. A computer control system automatically adjusts the nozzle angle based on the shape of the longwall mining face and the direction of dust diffusion, ensuring comprehensive coverage of the dust-generating area. The liquid nitrogen nozzles are equipped with heating devices. When dust suppression operations cease, the nozzles are appropriately heated to prevent liquid nitrogen residue from clogging them, thus ensuring normal operation and extending their lifespan.

[0072] The coal and gangue infrared identification system includes an infrared camera equipped with an infrared image sensor. The infrared camera captures images of coal and gangue during the top coal caving process. By analyzing and processing the acquired sensor data, machine learning algorithms are used to accurately identify the coal and gangue. The infrared image sensor identifies coal and gangue, distinguishing between different materials.

[0073] The computer control system works in conjunction with the liquid nitrogen dust suppression system and the coal gangue infrared identification system. While reducing dust, it enhances the accuracy of the coal gangue infrared identification system. Simultaneously, the coal gangue identification results are fed back to the liquid nitrogen dust suppression system to optimize its dust suppression parameters. When the coal gangue infrared identification system detects a high proportion of coal gangue, the injection volume and frequency of the liquid nitrogen in the liquid nitrogen dust suppression system are increased to improve the dust suppression effect. The computer control system receives signals from the infrared image sensor and controls the operating status of the liquid nitrogen dust suppression system.

[0074] Dust settling principle: The low temperature of liquid nitrogen can rapidly cool and condense coal dust. Based on the nucleation effect, the nitrogen molecules formed after liquid nitrogen vaporization can act as nuclei, promoting the aggregation and settling of dust particles. The evaporation process of liquid nitrogen absorbs a large amount of heat, lowering the temperature of the surrounding air and reducing the generation of coal dust. The cooling effect lowers the temperature of dust particles, increases their surface viscosity, and makes them easier to agglomerate and settle.

[0075] Infrared thermal imaging principle: Infrared thermal imaging is a measurement technique that uses an infrared thermal imager to capture infrared radiation signals emitted from the surface of coal and gangue, and then processes these electrical signals with a detector to convert them into an infrared thermal image of temperature distribution. When the coal and gangue being measured absorbs radiation from the surrounding environment, it radiates infrared rays when its temperature is above absolute zero. The infrared thermal imager then uses a detector to decompose the energy representing the element's temperature and arranges it according to a specific pattern. The collected data is transmitted to an infrared display device, thus presenting a thermal image of the surface temperature of the coal and gangue being measured. This process is infrared thermal imaging.

[0076] (1) Generation of thermal radiation: Any object with a temperature above absolute zero (-273.15℃) will release energy in the electrons of its atoms during thermal motion. This energy will propagate outward in the form of electromagnetic waves, which include infrared radiation. The higher the temperature of coal gangue, the more intense the thermal motion of its molecules or atoms, and the stronger its infrared radiation.

[0077] (2) Reception and focusing of infrared radiation: The infrared thermal imaging system uses the optical imaging objective lens in front of the infrared detector to focus the infrared radiation emitted by the coal gangue onto the infrared detector.

[0078] (3) Detector operation: The infrared detector is the core component of the thermal imaging system. It can receive infrared radiation and convert it into electrical signals. The photon detector directly generates an electrical effect after absorbing infrared energy.

[0079] (4) Signal processing and image generation: The electrical signal generated by the detector is very weak. It is amplified, filtered and other signal processing processes to improve the quality and stability of the signal.

[0080] The processed electrical signal is converted into a standard video signal, which is then displayed as an infrared thermal image of the object through devices such as displays or monitors. In the thermal image, different colors or gray levels represent different temperature distributions on the surface of the coal gangue; typically, red and pink indicate higher temperatures, while blue and green indicate lower temperatures.

[0081] The neural network input layer receives preprocessed infrared image data, which consists of infrared radiation intensity values ​​across multiple bands. The hidden layer performs complex nonlinear transformations on the input data. Through the connection weights and activation functions between multiple neurons, it mines latent features from the data. In coal gangue identification, the hidden layer can learn the subtle differences between coal and gangue in infrared images. Multiple hidden layers are configured, each further refining and abstracting features, enabling the neural network to construct complex classification models. The output layer has two neurons, representing the categories of "coal" and "gangue," respectively. By comprehensively judging the signals from the hidden layers, the output layer provides the final identification result: [0,1] represents gangue, and [1,0] represents coal.

[0082] In the task of coal gangue identification, instantaneous gangue content and total gangue content are important indicators for measuring the gangue content. Based on the results of neural network output, the calculation formulas for instantaneous gangue content and total gangue content are derived.

[0083] Instantaneous gangue content refers to the proportion of gangue in a given frame of an image at a specific moment. The output of a neural network for a given frame of an infrared image is [P]. 煤 P 矸石 ], where P 煤P represents the probability that an image is classified as "coal". 矸石 This represents the probability that an image is classified as "gangue". Instantaneous gangue content R 瞬时 It can be expressed as:

[0084]

[0085] Among them, P 矸石 P is the output value of the neuron representing "gangue" in the output layer of the neural network. 煤 It is the output value of the neuron representing "coal" in the output layer of the neural network.

[0086] Total gangue content refers to the average proportion of gangue in a given time period or a series of images. Assuming there are N frames of images, and the instantaneous gangue content of each frame is R... 瞬时 If (i = 1, 2, ..., N), then the total gangue content R 总 It can be expressed as:

[0087]

[0088] Among them, R 瞬时 is the instantaneous slag content of the i-th frame, and N is the total number of frames.

[0089] Training Process: The neural network is trained using labeled infrared image data samples of coal gangue. During training, the connection weights between the layers of the neural network are continuously adjusted using the backpropagation algorithm. The error between the predicted result and the actual label is calculated, and the weights are updated based on the error, allowing the neural network to gradually converge during continuous iteration, thereby improving the accuracy of coal gangue identification.

[0090] Application and Optimization: The trained neural network system is deployed at the fully mechanized longwall mining face to perform real-time infrared scanning and identification of coal gangue on the rear scraper conveyor. Furthermore, as new data is continuously collected, the neural network is optimized to adapt to the differences in coal gangue characteristics across different coal mines, further improving the accuracy and stability of the identification.

[0091] Coal and gangue identification method: After liquid nitrogen spraying, both coal and gangue will show a significant temperature drop. Due to the differences in chemical composition and physical properties, their surface temperatures also differ. Infrared image sensors are used to detect the surface temperatures of coal and gangue. Through analysis and processing, coal and gangue can be accurately identified.

[0092] Step S2: Debug and optimize the parameters of the liquid nitrogen dust suppression system and the coal gangue infrared identification system.

[0093] Step S21: Install a high-precision infrared camera below the tail beam of the hydraulic support in the fully mechanized longwall mining face to quickly collect infrared image data of coal and gangue, and transmit the collected data to the underground data analysis and processing center.

[0094] Step S22: Establish a large-scale infrared image database of coal and gangue, collect infrared image data of coal and gangue samples from different origins and of different qualities, and use deep learning algorithms to analyze and train the infrared image data of coal and gangue samples to improve the accuracy of the recognition model. In this embodiment, the recognition accuracy rate can reach over 93%.

[0095] Step S23: The data analysis and processing center performs real-time analysis on the collected infrared image data. If gangue is identified, a signal is immediately sent to the sorting device in the transport tunnel.

[0096] Step S24: The sorting device uses a robotic arm or pneumatic baffle to quickly separate the gangue from the coal flow and transport the gangue to the designated gangue collection area.

[0097] Step S25: Connect the coal gangue infrared identification system to the automated control system of the entire fully mechanized longwall mining operation. When the gangue content is too high, automatically adjust the top coal caving process of the fully mechanized longwall mining face.

[0098] Step S3: Run and test the liquid nitrogen dust suppression system and the coal gangue infrared identification system.

[0099] Step S31: The liquid nitrogen dust suppression system is in operation.

[0100] Step S311, Automation Control Logic: Construct an intelligent control center based on PLC or DCS, connect it with the operating signals of the hydraulic support and the rear scraper conveyor fully mechanized mining equipment, and obtain their working status information.

[0101] Step S312: Based on the working status information, automatically calculate the optimal injection parameters of liquid nitrogen according to the preset algorithm, including injection pressure, flow rate, nozzle angle and number of openings, and control the liquid nitrogen supply system and injection device in real time to perform precise operation.

[0102] a. Establish normal mining dust suppression mode, high dust concentration emergency mode, and equipment maintenance mode. Under normal mining dust suppression mode, set stable liquid nitrogen injection parameters based on the normal dust generation range to maintain the basic dust suppression effect of the fully mechanized longwall mining face.

[0103] b. When the dust monitoring sensor detects that the dust concentration instantly exceeds the preset high warning value, the system automatically switches to the high dust concentration emergency mode. At this time, the liquid nitrogen injection volume and coverage are greatly increased to quickly reduce the dust concentration in the air.

[0104] c. In equipment maintenance mode, stop liquid nitrogen injection and only maintain the system's pressure monitoring and equipment inspection functions to ensure that the equipment is in a safe standby state so that equipment maintenance and repair work can be carried out.

[0105] Step S313, Coordinating the Liquid Nitrogen Dust Suppression System with the Ventilation System: Combine the liquid nitrogen dust suppression system with the underground ventilation system. Optimize the position and angle of liquid nitrogen injection based on the direction, speed, and volume parameters of the ventilation airflow to enable the liquid nitrogen and airflow to work synergistically and improve dust settling efficiency.

[0106] Step S32: The coal gangue infrared identification system is in operation.

[0107] Step S321, Real-time Data Acquisition and Transmission: One infrared camera is installed below the tail beam of each hydraulic support in the fully mechanized longwall mining face to ensure timely acquisition of infrared image information of the coal-gangue mixture. To ensure the stability and reliability of data transmission, a data verification and retransmission mechanism is set up to prevent data loss or errors due to signal interference or line failure. A high-speed data transmission line is used to transmit the acquired infrared image data in real time to the data analysis server located in the underground monitoring room or the ground dispatch center.

[0108] Step S322, Online Identification and Decision-Making: After receiving the infrared image data, the data analysis server immediately uses a pre-trained deep learning model to perform coal and gangue identification and analysis. This deep learning model is trained and optimized based on a large amount of coal and gangue infrared image sample data, and can accurately identify the differences in characteristic images of coal and gangue, and quickly determine the distribution of coal and gangue in the material flow.

[0109] If gangue is identified, the computer control system calculates the optimal top coal caving process for the fully mechanized longwall face and the sorting parameters of the coal and gangue sorting device in the transport roadway based on information such as the location and size of the gangue and the running speed of the conveyor belt, and sends control commands to the coal and gangue sorting device.

[0110] Step S323, Self-learning and Model Update: The coal gangue infrared identification system has a self-learning function. During operation, it continuously collects new coal gangue infrared image data and compares and analyzes it with existing sample data.

[0111] When new data features are found to be mismatched or deviate from the existing model, the model update mechanism is automatically activated. The deep learning model is retrained and optimized using the new data to improve the model's recognition accuracy and adaptability. When new coal seams are mined or geological conditions change, altering the characteristics of coal and gangue, the coal and gangue infrared recognition system automatically senses and adjusts the recognition model to ensure that the accuracy of coal and gangue recognition remains unaffected.

[0112] Step S33: Testing the liquid nitrogen dust suppression system.

[0113] Step S331, Liquid nitrogen parameter monitoring: Install several monitoring devices such as pressure sensors, temperature sensors, flow sensors and liquid level sensors in key parts such as liquid nitrogen storage tanks, delivery pipelines and nozzles to monitor the pressure, temperature, flow rate and storage volume of liquid nitrogen in real time.

[0114] The parameters are transmitted to the monitoring system, and reasonable parameter thresholds are set. When abnormal liquid nitrogen parameters are detected, such as excessively high or low pressure, insufficient flow, or abnormal temperature rise, the liquid nitrogen dust suppression system immediately issues an alarm signal and displays the location and specific value of the abnormal parameters, so that staff can promptly troubleshoot and handle the problem.

[0115] Step S332, Spraying effect detection: Set up dust concentration monitoring instruments at several locations in the fully mechanized longwall mining face to monitor the changes in dust concentration before and after dust suppression, and evaluate the dust suppression effect of the liquid nitrogen spraying system.

[0116] Based on coal mine safety regulations and actual operating environment requirements, target dust suppression efficiency values ​​are set, such as requiring that the dust concentration in the air after dust suppression must not exceed a specific value. Regular statistical analysis of dust concentration monitoring data is conducted. If the dust suppression effect fails to meet the expected target, the system automatically adjusts the liquid nitrogen injection parameters and re-monitors and evaluates the adjusted effect until a satisfactory dust suppression effect is achieved. Simultaneously, a high-speed camera records the liquid nitrogen injection process, observing the atomization state, injection angle, and coverage area of ​​the liquid nitrogen. This provides a visual aid to determine the normal operation of the injection device. If problems such as uneven liquid nitrogen atomization, nozzle blockage, or injection angle deviation are found, timely maintenance and adjustments are made.

[0117] Step S333, Equipment Operation Status Detection: Real-time monitoring of the operation status of pumps, valves, and pipeline connection components in the liquid nitrogen dust suppression system.

[0118] Vibration sensors are used to monitor the vibration of pumps and valves. By analyzing the vibration frequency and amplitude, mechanical faults can be identified. Current sensors monitor the operating current of the motor; abnormally high or fluctuating motor current indicates potential problems such as motor overload, phase loss, or short circuit in the windings. Displacement sensors or strain gauges are installed at pipe connections to detect pipe deformation and displacement, preventing liquid nitrogen leaks caused by pipe ruptures, leaks, or loose connections. Once an abnormal operating condition is detected, the system immediately issues an alarm, locates the fault, and provides corresponding troubleshooting suggestions to help maintenance personnel quickly repair the equipment.

[0119] Step S34: Detection by the coal gangue infrared identification system.

[0120] Step S341, Identification Accuracy Detection: Establish a coal gangue identification accuracy detection mechanism. Collect samples from the coal gangue mixture regularly, use manual sorting or other high-precision detection methods to determine the true proportion of coal gangue in the samples, and then use the coal gangue infrared identification system to identify and analyze these samples. Compare the identification results with the true proportion to calculate the identification accuracy.

[0121] Based on the actual requirements of coal mine production, a minimum recognition accuracy standard is set, such as requiring that the coal gangue recognition accuracy rate not be lower than 95%. If the recognition accuracy rate is found to be lower than the standard value, the system automatically starts the recognition model optimization program, retrains the deep learning model and adjusts the parameters, and then re-tests the accuracy rate of the optimized model until the recognition accuracy rate meets the requirements.

[0122] Step S342, Data Transmission and System Response Detection: Detect the data transmission lines and the response speed of the control system in the coal gangue infrared identification system.

[0123] A network tester was used to test parameters such as bandwidth, latency, and packet loss rate of the data transmission lines to ensure that data could be transmitted quickly and accurately between the infrared image sensor and the data analysis server. Simultaneously, an analog signal generator was used to send different types of test commands to the control system to detect the system's response time and execution accuracy, such as the start-up time of the sorting device, the precision of its actions, and the feedback of control signals. If problems were found in data transmission or system response, line faults were promptly investigated, network configuration was optimized, or the hardware and software of the control system were checked to ensure stable and efficient system operation.

[0124] Step S4: Start the liquid nitrogen dust suppression system and the coal gangue infrared identification system.

[0125] Step S41: Start the liquid nitrogen dust suppression system.

[0126] Step S411: Start the liquid nitrogen dust suppression system. After the system is started, the central control system automatically adjusts the speed of the liquid nitrogen pump and the opening of the valve according to the dust concentration and the operating status of the rear scraper conveyor, and controls the flow rate and injection pressure of liquid nitrogen to ensure that liquid nitrogen can effectively cover the dust generation area.

[0127] Step S412: Install dust concentration sensors, wind speed sensors, and operating status sensors on the fully mechanized longwall mining face to collect information such as dust concentration, ventilation wind speed, and hydraulic support working status in real time, and transmit these signals to the central control system.

[0128] Step S413: Install several liquid nitrogen nozzles at different locations on the fully mechanized longwall mining face. Each liquid nitrogen nozzle is equipped with an angle adjustment mechanism and a solenoid valve. The central control system controls the opening and closing of the solenoid valve and the angle of the liquid nitrogen nozzle based on sensor information and a preset dust suppression strategy, so that the liquid nitrogen can be accurately sprayed to the dust source to achieve efficient dust suppression.

[0129] Step S42: The coal gangue infrared identification system is started.

[0130] Step S421: Start the coal gangue infrared identification system to perform real-time infrared detection on the coal gangue mixture, collect infrared image data of the coal gangue, and transmit the data to the data processing unit.

[0131] Step S422: After receiving the infrared image data, the data processing unit first performs preprocessing, including data filtering, noise reduction, and normalization, to improve data quality. Then, the processed data is compared and analyzed with a pre-stored database of coal gangue infrared image features. Using pattern recognition algorithms or machine learning models, the type and distribution of coal gangue are identified.

[0132] Step S423: Based on the coal and gangue identification results, the data processing unit generates corresponding control commands and transmits the commands to the coal and gangue sorting device.

[0133] Therefore, the present invention employs the above-mentioned method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining, which can solve the problems of poor dust suppression effect and inaccurate coal gangue identification in the prior art.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. 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 still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining, characterized in that, Includes the following steps: Step S1: Install the system; the system includes a liquid nitrogen dust suppression system, a coal gangue infrared identification system, and a computer control system; Step S2: Debug and optimize the parameters of the liquid nitrogen dust suppression system and the coal gangue infrared identification system; Step S3: Operate and test the liquid nitrogen dust suppression system and the coal gangue infrared identification system; Step S4: Start the liquid nitrogen dust suppression system and the coal gangue infrared identification system.

2. The method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to claim 1, characterized in that: In step S1, the liquid nitrogen dust suppression system includes a liquid nitrogen storage tank, a high-pressure conveying pipeline, and a liquid nitrogen nozzle. The two ends of the high-pressure conveying pipeline are connected to the liquid nitrogen storage tank and the liquid nitrogen nozzle, respectively. The high-pressure delivery pipeline is equipped with a pressure sensor and a flow regulating valve; the liquid nitrogen nozzle has a multi-nozzle structure, with each nozzle independently adjustable in terms of spray angle and range; and the liquid nitrogen nozzle is equipped with a heating device. The inner wall of the high-pressure transmission pipeline is made of low-temperature wear-resistant material.

3. The method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to claim 1, characterized in that: In step S1, the coal gangue infrared identification system includes an infrared camera, which is equipped with an infrared image sensor. The infrared camera collects images of coal gangue during the top coal caving process, and the infrared image sensor identifies the coal and gangue to distinguish different substances.

4. The method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to claim 1, characterized in that: In step S1, the computer control system works in conjunction with the liquid nitrogen dust suppression system and the coal gangue infrared identification system to enhance the accuracy of the coal gangue infrared identification system while suppressing dust. At the same time, the coal gangue identification results are fed back to the liquid nitrogen dust suppression system to optimize the dust suppression parameters of the liquid nitrogen dust suppression system. The computer control system adjusts the injection volume and frequency of liquid nitrogen in the liquid nitrogen dust suppression system in real time according to the gangue content. The computer control system receives signals from the infrared image sensor and controls the working status of the liquid nitrogen dust suppression system.

5. The method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to claim 1, characterized in that: Step S1 specifically involves setting up liquid nitrogen nozzles and pressure sensors based on the actual conditions of the fully mechanized longwall mining face. The input end of the liquid nitrogen nozzles is connected to the liquid nitrogen storage tank and the high-pressure delivery pipeline. The computer control system is electrically connected to the liquid nitrogen dust suppression system and the coal gangue infrared identification system, respectively.

6. The method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to claim 1, characterized in that: Step S2 specifically involves: Step S21: Install a high-precision infrared camera under the tail beam of the hydraulic support in the fully mechanized longwall mining face to quickly collect infrared image data of coal and gangue, and transmit the collected data to the data analysis and processing center underground. Step S22: Establish a large database of coal and gangue infrared images, collect infrared image data of coal and gangue samples from different origins and of different qualities, and use deep learning algorithms to analyze and train the infrared image data of coal and gangue samples. Step S23: The data analysis and processing center performs real-time analysis on the collected infrared image data. If gangue is identified, a signal is immediately sent to the sorting device in the transport tunnel. Step S24: The sorting device uses a robotic arm or pneumatic baffle structure to quickly separate the gangue from the coal flow and transport the gangue to the designated gangue collection area. Step S25: Connect the coal gangue infrared identification system to the automated control system of the entire fully mechanized longwall mining operation. When the gangue content is too high, automatically adjust the top coal caving process of the fully mechanized longwall mining face.

7. The method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to claim 1, characterized in that: Step S3 specifically involves: Step S31: The liquid nitrogen dust suppression system is in operation; Step S311, Automation Control Logic: Construct an intelligent control center based on PLC or DCS, connect it with the operating signals of the hydraulic support and the rear scraper conveyor fully mechanized mining equipment, and obtain their working status information; Step S312: Based on the working status information, automatically calculate the optimal injection parameters of liquid nitrogen according to the preset algorithm, including injection pressure, flow rate, nozzle angle and number of openings, and control the liquid nitrogen supply system and injection device in real time to perform precise operation. Step S313, Coordination of liquid nitrogen dust suppression system and ventilation system: Combine liquid nitrogen dust suppression system with underground ventilation system, optimize the position and angle of liquid nitrogen injection according to ventilation airflow direction, wind speed and air volume parameters, so that liquid nitrogen and airflow work together; Step S32: The coal gangue infrared identification system is in operation; Step S33: Testing the liquid nitrogen dust suppression system; Step S34: Coal gangue infrared identification system detection; Step S341, Identification Accuracy Detection: Establish a coal gangue identification accuracy detection mechanism, regularly collect samples from coal gangue mixtures, use manual sorting or other high-precision detection methods to determine the true proportion of coal gangue in the samples, then use these samples to identify and analyze them through a coal gangue infrared identification system, compare the identification results with the true proportion, and calculate the identification accuracy. Step S342, Data Transmission and System Response Detection: Detect the data transmission lines and the response speed of the control system in the coal gangue infrared identification system.

8. The method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to claim 7, characterized in that: Step S312 specifically involves, a. Establish normal mining dust suppression mode, high dust concentration emergency mode and equipment maintenance mode; under normal mining dust suppression mode, set stable liquid nitrogen injection parameters according to the normal dust generation range to maintain the basic dust suppression effect of the fully mechanized mining face. b. When the dust monitoring sensor detects that the dust concentration instantly exceeds the preset high warning value, the system automatically switches to the high dust concentration emergency mode. At this time, the liquid nitrogen injection volume and coverage are greatly increased to quickly reduce the dust concentration in the air. c. In equipment maintenance mode, stop liquid nitrogen injection and only maintain the system's pressure monitoring and equipment inspection functions to ensure that the equipment is in a safe standby state so that equipment maintenance and repair work can be carried out.

9. The method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to claim 8, characterized in that: Steps S32 and S33 are specifically as follows: Step S321, Real-time data acquisition and transmission: Install an infrared camera below the tail beam of the hydraulic support in the fully mechanized longwall mining face; set up a data verification and retransmission mechanism, and use a high-speed data transmission line to transmit the acquired infrared image data in real time to the data analysis server located in the underground monitoring room or the ground dispatch center. Step S322, Online Identification and Decision-Making: After receiving the infrared image data, the data analysis server immediately uses a pre-trained deep learning model to perform coal gangue identification and analysis; If gangue is identified, the computer control system calculates the optimal top coal caving process for the fully mechanized longwall face and the sorting action parameters of the coal and gangue sorting device in the transport roadway based on the location, size, and speed of the gangue and the conveyor belt, and sends control commands to the coal and gangue sorting device. Step S323, Self-learning and Model Update: The coal gangue infrared identification system has a self-learning function. During operation, it continuously collects new coal gangue infrared camera data and compares and analyzes it with existing sample data. When new data features are found to be mismatched with or deviate from the existing model, the model update mechanism is automatically activated to retrain and optimize the deep learning model using the new data; when new coal seams are mined or geological conditions change and the characteristics of coal gangue change, the coal gangue infrared recognition system automatically senses and adjusts the recognition model. Step S331, Liquid nitrogen parameter monitoring: Install several monitoring devices such as pressure sensors, temperature sensors, flow sensors and liquid level sensors at key parts of the liquid nitrogen storage tank, delivery pipeline and nozzle to monitor the pressure, temperature, flow and storage volume parameters of liquid nitrogen in real time. The parameters are transmitted to the monitoring system, and reasonable parameter thresholds are set. When an abnormality in liquid nitrogen parameters is detected, the liquid nitrogen dust suppression system immediately issues an alarm signal and displays the location and specific value of the abnormal parameters. Step S332, Spraying effect test: Set up dust concentration monitoring instruments at several locations in the fully mechanized longwall mining face to monitor the changes in dust concentration before and after dust suppression, and evaluate the dust suppression effect of the liquid nitrogen spraying system. Step S333, Equipment Operation Status Detection: Real-time monitoring of the operation status of pumps, valves, and pipeline connection components in the liquid nitrogen dust suppression system.

10. The method for efficient dust suppression and coal gangue infrared identification using liquid nitrogen in fully mechanized longwall mining according to claim 1, characterized in that: Step S4 specifically involves, Step S41: Start the liquid nitrogen dust suppression system; Step S411: Start the liquid nitrogen dust suppression system. After the system starts, the central control system automatically adjusts the speed of the liquid nitrogen pump and the opening of the valve according to the dust concentration and the working status of the hydraulic support, thereby controlling the flow rate and injection pressure of the liquid nitrogen. Step S412: Install dust concentration sensors, wind speed sensors, and hydraulic support position and operation status sensors on the fully mechanized longwall mining face to collect real-time information on dust concentration, ventilation wind speed, and hydraulic support operation status, and transmit these signals to the central control system. Step S413: Install several liquid nitrogen nozzles at different locations on the fully mechanized longwall mining face. Each liquid nitrogen nozzle is equipped with an angle adjustment mechanism and a solenoid valve. The central control system controls the opening and closing of the solenoid valve and the angle of the liquid nitrogen nozzle based on sensor information and the preset dust suppression strategy. Step S42: The coal gangue infrared identification system is activated; Step S421: Start the coal gangue infrared identification system to perform real-time infrared detection on the coal gangue mixture, collect infrared camera data of the coal gangue, and transmit the data to the data processing unit. Step S422: After receiving the infrared camera data, the data processing unit first performs preprocessing, including data filtering, noise reduction, and normalization operations; then, it compares and analyzes the processed data with the pre-stored coal gangue infrared camera feature database, and uses pattern recognition algorithms or machine learning models to identify the type and distribution of coal gangue. Step S423: Based on the coal and gangue identification results, the data processing unit generates corresponding control commands and transmits the commands to the coal and gangue sorting device.

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