A coal mine underground nitrogen pipeline end monitoring system

Abstract

This invention relates to the technical field of nitrogen pipeline end-of-pipeline monitoring systems, and discloses a nitrogen pipeline end-of-pipeline monitoring system for underground coal mines. The system includes a point confirmation module, which acquires basic mine data, constructs a nitrogen pipeline access-type pressurization model, and determines the theoretical nitrogen access point based on the model; a correction module, which corrects the theoretical nitrogen access point based on the actual mine conditions, and confirms the actual nitrogen access point; a parameter acquisition module, which acquires parameter information at the end of a pipeline branch located at the actual nitrogen access point; and a signal processing and compensation module, which constructs a corresponding signal attenuation prediction model and a wireless transmission algorithm model based on the acquired parameter information. These models are used to quantify the impact of multiple interference sources on the signal. This system can quantify the impact of multiple interference sources on the signal, predict and dynamically compensate for signal attenuation in the mine, and solve data delay and packet loss problems through the wireless transmission algorithm model.

Description

Technical Field

[0001] This invention belongs to the field of nitrogen pipeline end detection technology, and specifically provides a monitoring system for the end of nitrogen pipelines in coal mines. Background Technology

[0002] The nitrogen pipeline end-of-line detection system is a safety assurance device for the use of nitrogen in industrial and laboratory settings, primarily monitoring key parameters such as pressure, purity, and leakage. Equipped with high-precision sensors and a real-time transmission module, it offers rapid response and timely alarms, supporting remote monitoring and data traceability. Its convenient installation and maintenance adapt to various scenarios, effectively mitigating leakage risks, ensuring personnel and equipment safety, and guaranteeing stable nitrogen quality, thereby contributing to improved production and experimental accuracy.

[0003] As coal mining progresses, the distance of nitrogen pipelines for fire prevention and extinguishing increases, resistance grows, and nitrogen delivery capacity and equipment nitrogen production capacity decrease significantly. This makes it difficult to effectively deliver sufficient flow of nitrogen to the fire prevention and extinguishing area, resulting in an inability to guarantee fire prevention and extinguishing capabilities during coal mining. Therefore, nitrogen booster devices are added to the nitrogen pipelines. However, during the gas delivery process, the booster devices cause vibration in the pipelines, leading to signal attenuation and signal transmission failure.

[0004] Therefore, there is an urgent need for a monitoring system at the end of underground nitrogen pipelines in coal mines to ensure the nitrogen delivery capacity of nitrogen pipelines. Summary of the Invention

[0005] This invention provides a monitoring system for the end of a nitrogen pipeline in an underground coal mine to solve the aforementioned problems in the prior art.

[0006] A monitoring system for the end of a nitrogen pipeline in an underground coal mine includes: The point confirmation module acquires basic data of the mine, constructs a nitrogen pipeline access pressurization model, and determines the theoretical nitrogen access point based on the nitrogen pipeline access pressurization model. The parameter acquisition module acquires parameter information from the end of the pipeline branch. The signal attenuation prediction module, based on the acquired parameter information, uses a signal attenuation prediction model to predict the signal attenuation in the mine, and obtains the predicted signal attenuation, which is used to quantify the impact of multiple interference sources on the signal. The signal compensation module dynamically optimizes the signal in the mine based on the predicted signal attenuation using a wireless transmission algorithm model.

[0007] Furthermore, it also includes: The correction module corrects the theoretical nitrogen access point confirmed in the nitrogen pipeline access booster model based on the actual working conditions of the mine, confirms the actual nitrogen access point, and enables the parameter acquisition module to obtain the parameter information of the pipeline branch end of the actual nitrogen access point.

[0008] Furthermore, the nitrogen pipeline access pressurization model, based on the pipeline layout data in the basic data of the mine and relying on the gas pipeline resistance calculation theory, calculates the resistance of gas passing through the pipeline and confirms the theoretical access point of nitrogen.

[0009] Furthermore, the monitoring system also includes a pressurization device installed at the nitrogen inlet point, the pressurization device comprising: The motor, the housing mounted on the motor, the two screws located inside the housing and rotatably connected to the housing, the two end caps mounted on the housing, and the air intake and exhaust ports opened on the housing; Two of the screws are helical and parallel, and they mesh with each other. One of them is the male rotor, which is connected to the motor output, and the other is the female rotor. The female rotor, male rotor and housing form a "V" shaped area. As the motor rotates, the male rotor rotates counterclockwise, causing the space in the above area to gradually decrease. As the two screws rotate, the above area can move from the air intake port to the air exhaust port, completing the air intake, compression and exhaust process.

[0010] Furthermore, the construction of the signal attenuation prediction model includes the following steps: First, the relationship between gas concentration and rock stratum dielectric constant in the mine is defined, and based on electromagnetic wave propagation theory, the basic signal attenuation coefficient under the synergistic effect of gas and rock stratum is obtained. Next, the airflow vibration frequency during nitrogen injection is obtained, and the signal attenuation increment coefficient is obtained based on the airflow vibration frequency. The quantitative correlation between the signal attenuation increment coefficient and the signal attenuation increment coefficient is defined. A functional relationship between signal attenuation and the basic signal attenuation coefficient, the signal attenuation increment coefficient, and the wireless transmission distance is established as a signal attenuation prediction model.

[0011] Furthermore, the training of the signal attenuation prediction model includes: The system can acquire real-time gas concentration, airflow vibration frequency during actual nitrogen injection, actual transmission distance, and actual attenuation at a predetermined time. The real-time gas concentration, the airflow vibration frequency during actual nitrogen injection, and the actual transmission distance are input into the signal attenuation prediction model to obtain the predicted signal attenuation. Based on the predicted signal attenuation and the actual signal attenuation, the parameters in the signal attenuation prediction model are calibrated using the least squares method to ensure that the error between the predicted signal attenuation and the actual signal attenuation is within a predetermined range.

[0012] Furthermore, the wireless transmission algorithm model includes a signal optimization sub-model; used to optimize the carrier frequency, modulation scheme, and transmit power based on the predicted signal attenuation; the optimization steps are as follows: First, a preset threshold range for predicted signal attenuation is established, and each threshold range corresponds to a carrier frequency. If the predicted signal attenuation exceeds the threshold range corresponding to the current frequency, the carrier frequency is switched, and the switching time is less than 50ms. Simultaneously, based on the preset signal prediction attenuation threshold range, the corresponding modulation mode is switched, and the switching records are cached. The required transmit power is calculated based on the predicted attenuation, and the actual signal-to-noise ratio (SNR) at the receiver is compared with the minimum SNR at the receiver. Then, the transmit power is increased so that the actual SNR at the receiver is not less than the minimum SNR at the receiver.

[0013] Furthermore, the wireless transmission algorithm model also includes a path planning sub-model; used to construct the pipeline topology and plan the signal transmission path; The steps for constructing the pipeline topology are as follows: First, establish a topology diagram between the downhole monitoring node, relay node, and control center; then, calculate the link weight by weighting the link attenuation, maximum allowable attenuation, and historical packet loss rate, which is used to characterize the link quality.

[0014] The planned signal transmission path includes the following steps: The optimal and backup paths from the monitoring node to the control center are determined using Dijkstra's algorithm, with the following steps: First, perform the initialization steps, define the weight of the control center as 0, the weight of the nodes as ∞, and mark all nodes as unvisited; Then, an iterative process is performed: the node with the smallest weight among the unvisited nodes is selected and marked as visited; the weights of the neighboring nodes of the node with the smallest weight are updated; if the sum of the direct link weights between the node with the smallest weight and its neighboring nodes is less than the weight of the neighboring nodes, the weights of the neighboring nodes are updated to be the sum of the direct link weights between the node with the smallest weight and its neighboring nodes. The termination condition is that when all nodes have been visited, the optimal path is obtained by backtracking; and the links in the optimal path are deleted. The above steps are repeated to obtain the backup path.

[0015] Furthermore, the wireless transmission algorithm model also includes a topology optimization sub-model for optimizing pipeline topology. The optimization of pipeline topology includes the following steps: The monitoring nodes encapsulate real-time data into data frames with sequence numbers and timestamps, and transmit them through the optimal path and backup path. If the control center receives the same sequence number at the same time, it will choose the one with the smaller timestamp. If only one message is received, it is parsed directly; if none are received, the data frame is processed according to the rule of retransmission up to three times. Then, a sliding window mechanism is used to count the success rate of data reception. If the success rate is lower than 95%, relay nodes are added to optimize the topology.

[0016] Beneficial Effects: To monitor the end of nitrogen pipelines and extinguish fires in mines, this invention includes a pressurization device. This device draws in, pressurizes, and exhausts nitrogen, ensuring it is delivered to a designated location for fire suppression. To address signal transmission failures caused by pipeline vibration during nitrogen delivery, the system incorporates a signal attenuation prediction model and a wireless transmission algorithm model. Combining these two models quantifies the impact of multiple interference sources on the signal, enabling prediction and dynamic compensation of signal attenuation in the mine. Simultaneously, the wireless transmission algorithm model adaptively adjusts carrier parameters and multi-path redundant transmission, resolving data delay and packet loss issues and ensuring smooth wireless transmission. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the intake process of the booster device, in which... Figure 1 The attached figures a, b, and c show the stages of the intake process of the booster device: the beginning stage, the intake process stage, and the end stage, respectively. Figure 2 The compression process of the booster device, in which Figure 2 The attached diagrams a, b, and c show the following stages of the compression process of the booster device: the intake compression process about to begin, the intake compression process, and the end of the intake compression process and the beginning of the exhaust process, respectively. Figure 3 This refers to the exhaust process of the booster unit, in which... Figure 3 Figures a and b in the figure represent the exhaust process stage and the exhaust process end stage of the supercharger exhaust process, respectively. Figure 4 This is a flowchart of the nitrogen pipeline end monitoring system of the present invention. Detailed Implementation

[0018] The present invention will now be described in detail with reference to the accompanying drawings.

[0019] Reference Figure 4 A monitoring system for the end of a nitrogen pipeline in an underground coal mine, comprising: The point confirmation module acquires basic data of the mine, constructs a nitrogen pipeline access pressurization model, and determines the theoretical nitrogen access point based on the above model. The basic data includes underground nitrogen injection data and pipeline layout data. The correction module corrects the theoretical nitrogen inlet point based on the actual working conditions of the mine and confirms the actual nitrogen inlet point. The parameter acquisition module acquires parameter information at the end of the pipeline branch located at the actual nitrogen inlet point; The signal attenuation prediction module, based on the acquired parameter information, uses a signal attenuation prediction model to predict the signal attenuation in the mine, and obtains the predicted signal attenuation, which is used to quantify the impact of multiple interference sources on the signal. The signal compensation module dynamically optimizes the signal in the mine based on the predicted signal attenuation using a wireless transmission algorithm model.

[0020] The basic data of the mine includes, but is not limited to, the output pressure and flow parameters of the surface nitrogen injection equipment; the actual working conditions of the mine include, but are not limited to, the location of the target fire prevention and extinguishing area of ​​the mine and the required nitrogen pressure and flow threshold, as well as the space constraints of the underground roadways; the nitrogen pipeline layout data includes, but is not limited to, the pipe diameter, length, bending angle, number and type of pipe fittings, as well as the topology of the pipeline, i.e., the branch nodes and path direction of the pipeline. The pipeline-connected pressurization model includes the following steps: First, based on the pipeline resistance formula in fluid mechanics, the friction resistance and local resistance are used to substitute the pipeline layout data such as pipe diameter, length, and bending angle to calculate the resistance loss distribution when nitrogen flows through the pipeline, i.e., the pressure attenuation degree at different pipeline locations. Then, the pressure or flow data of the surface and underground nitrogen injection systems, the nitrogen demand threshold of the fire prevention and extinguishing area, and the resistance distribution are combined to determine the critical position in the pipeline where the pressure attenuates below the demand threshold. Using the critical position as a reference, and combined with the branch nodes in the pipeline topology, the theoretical access point that can make the pressurized nitrogen pressure and flow meet the fire prevention and extinguishing requirements is determined through model iterative calculation.

[0021] Based on the pipeline layout data in the basic data of the mine and relying on the gas pipeline resistance calculation theory, the resistance of gas passing through the pipeline is obtained, and the theoretical access point of nitrogen is confirmed. The pipeline layout data includes, but is not limited to, the diameter of the conveying pipeline, the direction of the bend, the number of pipe fittings of the tee bend and the number of branch branches. During the process of gas passing through a pipe, at least two forms of flow resistance are generated. One is the resistance generated by the viscosity of the gas itself and the friction between the gas and the pipe wall, which is called frictional resistance. The other is the resistance caused by the local eddies generated when the gas flows through the pipe fittings (such as tees, elbows, etc.) and the magnitude and direction of the flow velocity changes, which is called local resistance. According to the principles of fluid mechanics, the frictional resistance per unit length of pipe when gas flows inside a pipe is calculated using the following formula: R m =λ(V1²×ρ) / 2D; In the formula, R m The frictional resistance per unit length is expressed in Pa / m. V1 is the air velocity inside the duct, in m / s; ρ is the density of air, with units of... ; λ is the frictional resistance coefficient; D is the pipe diameter, in meters (m). The frictional resistance coefficient λ is related to the airflow state in the duct and the roughness of the duct inner wall; The frictional resistance coefficient λ is related to the airflow state and the roughness of the duct inner wall, and the correlation formula is as follows: R e =(V3×d) / ν; In the formula, V3 is the air velocity inside the duct, measured in m / s; d is the inner diameter of the duct, in meters (m). ν is the kinematic viscosity, with units of m² / s; R e It is the Reynolds number; The formula for calculating local resistance is: Z = ξ × (V² × ρ) / 2 In the formula, Z represents the local resistance, measured in Pa. ξ is the local drag coefficient; V2 is the air velocity, measured in m / s; ρ is the air density, with units of kg / m³; By combining the aforementioned resistance with actual operating conditions, the theoretical access point for nitrogen pressurization regulation is determined. Then, the theoretical access point is verified by actual measurement, and a correction coefficient is assigned to the theoretical access point to confirm the actual nitrogen access point.

[0022] In a further embodiment, the experimental verification steps include: first, obtaining the basic test conditions, namely preparing the booster equipment, pressure and flow sensors, and resistance monitoring device, while simulating the actual working conditions such as pressure and flow rate of daily nitrogen injection in a coal mine; then, conducting tests based on the theoretical access point: temporarily connecting the booster equipment at the theoretical access point, starting the nitrogen injection system, and collecting pressure changes before and after the access point, actual pipeline resistance, and pressure and flow data of the end fire prevention and extinguishing zone under different nitrogen injection flow rates and different pipeline resistances; finally, calculating the deviation between theory and actual measurement, that is, comparing the theoretical booster effect and end parameters calculated by the relevant model with the actual data obtained by actual measurement to determine the degree of difference between the two. The correction coefficient is obtained through the following steps: collecting the differences between theoretical and measured values ​​under different test conditions; taking into account the actual usage frequency of each condition, comprehensively weighing the deviations under different conditions to obtain a correction coefficient that is suitable for the actual conditions; integrating the correction coefficient into the model of the theoretical access point and adjusting the parameters of the booster equipment or the location of the access point; and verifying the adjusted access point by conducting another actual test to confirm that the terminal pressure and flow rate meet the fire prevention and extinguishing requirements, and then determining the access point as the actual nitrogen access point.

[0023] The monitoring system also includes a pressurization device installed at the nitrogen inlet point, the pressurization device comprising: The motor, the housing mounted on the motor, the two screws located inside the housing and rotatably connected to the housing, the two end caps mounted on the housing, and the air intake and exhaust ports opened on the housing; Two of the screws are helical and parallel, and they mesh with each other. One of them is the male rotor, which is connected to the motor output, and the other is the female rotor. The female rotor, male rotor and housing form a "V" shaped area. As the motor rotates, the male rotor rotates counterclockwise, so that the space in the above area gradually decreases. As the two screws rotate, the above area can move from the air intake port to the air exhaust port, completing the air intake, compression and exhaust process. Reference Figure 1-3 These are schematic diagrams illustrating the intake, compression, and exhaust processes of the booster unit. Figure 1 In the figure, a, b, and c represent the beginning stage, the intake stage, and the end stage of the intake process of the booster device, respectively. Figure 2 The attached diagrams a, b, and c show the following stages of the compression process of the booster device: the intake compression process about to begin, the intake compression process, and the end of the intake compression process and the beginning of the exhaust process, respectively. Figure 3 Figures a and b in the figure represent the exhaust process stage and the exhaust process end stage of the supercharger exhaust process, respectively.

[0024] In addition to the pressurization device, the system also includes a pressure regulating host, an explosion-proof power system, a parameter monitoring and frequency conversion integration system, and a skid-mounted enclosure structure. This booster unit uses a positive displacement rotary machine, namely a screw booster. Based on the working cycle of the screw booster and related design elements, the shape of the screw is determined, and the output power of the main unit is determined based on the screw. Then, based on the output power requirements, the power of the main motor is determined, and the motor is selected based on the performance requirements of the main unit.

[0025] The construction of the signal attenuation prediction model includes the following steps: First, the relationship between gas concentration and rock stratum dielectric constant in the mine is defined, and based on electromagnetic wave propagation theory, the basic signal attenuation coefficient under the synergistic effect of gas and rock stratum is obtained. Next, the airflow vibration frequency during nitrogen injection is obtained, and the signal attenuation increment coefficient is obtained based on the airflow vibration frequency. A quantitative correlation between this coefficient and the fundamental signal attenuation coefficient is then defined. Specifically, the relationship between the gas concentration c and the rock stratum dielectric constant ε is first defined. r The correlation: Based on laboratory measured data, the formula for the change of sandstone dielectric constant with gas concentration was obtained by fitting the data as follows: ; In the formula: ε r0 The dielectric constant of pure sandstone is 4.5. k1 is the gas concentration influence coefficient, with a value of 0.02; in, The influence coefficient of gas concentration was obtained by fitting the dielectric constant values ​​of 5 different gas concentrations, and the goodness of fit R was set. 2 >0.98; Then, based on the electromagnetic wave propagation theory, the fundamental signal attenuation coefficient α1 is obtained again; ; In the formula, f is the wireless transmission frequency, taken as 2.4GHz; μ0 is the free permeability, taken as 4π × 10⁻⁶. -7 H / m; ε0 is the vacuum permittivity, taken as 8.85 × 10⁻⁶. -7 F / m; tanδ is the tangent of the sandstone loss angle, taken as 0.03; Therefore, the signal fundamental attenuation coefficient α1 can be obtained by calculating using the above formula.

[0026] The signal attenuation prediction model construction also includes the following steps: based on the obtained basic signal attenuation coefficient and signal attenuation increment coefficient, and combined with the actual wireless transmission distance of the signal, the predicted attenuation of the signal under multiple interference sources is constructed. Then, obtain the measured information from the mine site. When the vibration frequency is in the range of 50-200Hz, at this time: ; In the formula, f v The vibration frequency; k2 is the vibration frequency influence coefficient, taken as... ; b2 is the base decay increment, taken as 0.02; α2 is the signal attenuation increment coefficient; Then, the attenuation values ​​were fitted using three sets of measurements at different vibration frequencies, where the goodness of fit R was obtained. 2 >0.97; Finally, combining the synergistic disturbances of gas and rock formations with the vibration disturbances during nitrogen injection, a predicted attenuation A is constructed. total ;

[0027] In the formula, L represents the wireless transmission distance, measured in meters (m), and ranges from 100 to 5000 meters.

[0028] The training process of the signal attenuation prediction model includes: setting a predetermined time, and then sequentially acquiring the real-time gas concentration, the actual nitrogen injection vibration frequency, the actual transmission distance, and the actual attenuation. By calibrating the parameters in the signal attenuation prediction model using the least squares method, the error between the predicted value and the actual value is kept within a predetermined range. The preset time period is 24 hours, and then based on the collected relevant information, ... ; Among them, A real This represents the actual attenuation, where the calibration formula is as follows: ; In the formula, The number of data sets collected for each calibration. For the first Predicted decay of group data For the first The actual attenuation of the data set.

[0029] The wireless transmission algorithm model includes a signal optimization sub-model, a path planning sub-model, and a topology optimization sub-model.

[0030] The signal optimization sub-model optimizes the carrier frequency, modulation scheme, and transmit power based on the predicted signal attenuation obtained from the signal attenuation prediction model. The specific steps are as follows: First, referring to Table 1, preset the signal prediction attenuation threshold range and make each threshold range correspond to a carrier frequency. If the signal prediction attenuation exceeds the threshold range corresponding to the current frequency, the carrier frequency will be switched, and the switching time will be less than 50ms. Meanwhile, referring to Table 2, the corresponding modulation mode is switched according to the preset signal prediction attenuation threshold range, and the switching record is cached. The required transmit power is calculated based on the predicted attenuation, and the actual signal-to-noise ratio (SNR) at the receiver is compared with the minimum SNR at the receiver. Then, the transmit power is increased so that the actual SNR at the receiver is not less than the minimum SNR at the receiver.

[0031] Table 1: Matching Table of Predicted Signal Attenuation Threshold Range and Carrier Frequency

[0032] Table 2: Correspondence between predicted attenuation threshold range and modulation method

[0033] First, set the minimum signal-to-noise ratio at the receiver. ; Then the required transmission power P tx The formula is as follows: ; In the formula, P rxmin The minimum sensitivity of the receiver is set to -90dBm; G tx The transmit antenna gain is set to 10 dB. G rx For the receiving antenna gain, set it to 10dB; By real-time monitoring of the actual signal-to-noise ratio (SN) at the receiver Rreal .

[0034] When the actual signal-to-noise ratio is less than the minimum signal-to-noise ratio, the transmission power is increased in steps of ΔP = 2dB, and the maximum transmission power is required to not exceed 30dBm, until the actual signal-to-noise ratio is not less than the minimum signal-to-noise ratio.

[0035] The path planning sub-model first constructs multiple transmission paths under the pipeline topology to achieve redundant data transmission and reduce packet loss rate. The steps are as follows: First, establish downhole monitoring nodes (V1, V2, ..., V...). m ), relay nodes (R1,R2,...,R)n A topological diagram of the relationship between the control center (C) and the control center (C). Next, the link weight is obtained by weighting the link attenuation, the maximum allowable attenuation, and the historical packet loss rate. The smaller the link weight value, the better the link quality. The link weight is w ij The calculation formula is as follows: ; In the formula, A max The maximum allowable attenuation is set to 100 dB; A ij This represents the actual link attenuation from point i to node j. l ij Let be the historical packet loss rate from node i to node j.

[0036] The optimal and backup paths from the monitoring node to the control center are determined using Dijkstra's algorithm, with the following steps: First, perform the initialization steps, define the weight of the control center as 0, the weight of the nodes as ∞, and mark all nodes as unvisited; Second, an iterative process is performed. The node with the smallest weight among the unvisited nodes is selected and marked as visited. Then, the weights of the neighboring nodes of the node with the smallest weight are updated. If the sum of the direct link weights between the node with the smallest weight and its neighboring nodes is less than the weight of the neighboring nodes, the weights of the neighboring nodes are updated to be the sum of the direct link weights between the node with the smallest weight and its neighboring nodes. The termination condition is that when all nodes have been visited, the optimal path is obtained by backtracking; and the links in the optimal path are deleted. The above steps are repeated to obtain the backup path.

[0037] The topology optimization sub-model encapsulates real-time data into data frames with sequence numbers and timestamps through monitoring nodes, and transmits them through the optimal path and backup path. The control center selects the smaller timestamp when the same sequence number is received simultaneously. If only one message is received, it is parsed directly; if none are received, the data frame is processed according to the rule of retransmission up to three times. A sliding window mechanism is used to statistically analyze the success rate of data reception. If the success rate is lower than 95%, relay nodes are added to optimize the topology.

[0038] This system first combines mine nitrogen injection and pipeline data, calculates friction and local resistance formulas, and makes on-site corrections to determine the actual connection point of the nitrogen booster device. Then, at this point, the screw-type booster device is activated, and the rotor is driven by a motor to achieve nitrogen intake, compression, and exhaust, delivering sufficient nitrogen to the fire prevention and extinguishing area. At the same time, to address the signal attenuation problem caused by multiple interference sources underground, a model is constructed. First, the correlation formula between gas concentration and rock stratum dielectric constant is fitted, and the basic attenuation coefficient is calculated by combining electromagnetic wave propagation theory. This enables signal attenuation prediction and calibration, ensuring the efficient and stable operation of the system.

[0039] The above content is only a preferred embodiment of the present invention. For those skilled in the art, many changes can be made in the specific implementation and application scope based on the concept of the present invention. As long as these changes do not depart from the concept of the present invention, they all fall within the protection scope of the present invention.

Claims

1. A coal mine underground nitrogen pipeline end monitoring system, characterized in that, include: The point confirmation module acquires basic data of the mine, constructs a nitrogen pipeline access pressurization model, and determines the theoretical nitrogen access point based on the nitrogen pipeline access pressurization model. The parameter acquisition module acquires parameter information from the end of the pipeline branch. The signal attenuation prediction module, based on the acquired parameter information, uses a signal attenuation prediction model to predict the signal attenuation in the mine, and obtains the predicted signal attenuation, which is used to quantify the impact of multiple interference sources on the signal. The signal compensation module dynamically optimizes the signal in the mine based on the predicted signal attenuation using a wireless transmission algorithm model. The construction of the signal attenuation prediction model includes the following steps: First, the relationship between gas concentration and rock stratum dielectric constant in the mine is defined, and based on electromagnetic wave propagation theory, the basic signal attenuation coefficient under the synergistic effect of gas and rock stratum is obtained. Next, the airflow vibration frequency during nitrogen injection is obtained, and the signal attenuation increment coefficient is obtained based on the airflow vibration frequency. The quantitative correlation between the airflow vibration frequency and the signal attenuation increment coefficient is defined. Establish a functional relationship between signal attenuation and the basic signal attenuation coefficient, the signal attenuation increment coefficient, and the wireless transmission distance of the signal, as a signal attenuation prediction model; The training of the signal attenuation prediction model includes: The system can acquire real-time gas concentration, airflow vibration frequency during actual nitrogen injection, actual transmission distance, and actual attenuation at a predetermined time. The real-time gas concentration, the airflow vibration frequency during actual nitrogen injection, and the actual transmission distance are input into the signal attenuation prediction model to obtain the predicted signal attenuation. Based on the predicted signal attenuation and the actual signal attenuation, the parameters in the signal attenuation prediction model are calibrated using the least squares method to ensure that the error between the predicted signal attenuation and the actual signal attenuation is within a predetermined range. The wireless transmission algorithm model includes a signal optimization sub-model, used to optimize the carrier frequency, modulation scheme, and transmit power based on the predicted signal attenuation. The optimization steps are as follows: First, a preset threshold range for predicted signal attenuation is established, and each threshold range corresponds to a carrier frequency. If the predicted signal attenuation exceeds the threshold range corresponding to the current frequency, the carrier frequency is switched, and the switching time is less than 50ms. Simultaneously, based on the preset signal prediction attenuation threshold range, the corresponding modulation mode is switched, and the switching records are cached. The required transmit power is calculated based on the predicted attenuation, and the actual signal-to-noise ratio (SNR) at the receiver is compared with the minimum SNR at the receiver. Then, the transmit power is increased so that the actual SNR at the receiver is not less than the minimum SNR at the receiver.

2. The coal mine underground nitrogen pipeline end monitoring system according to claim 1, characterized in that: Also includes: The correction module corrects the theoretical nitrogen access point confirmed in the nitrogen pipeline access booster model based on the actual working conditions of the mine, confirms the actual nitrogen access point, and enables the parameter acquisition module to obtain the parameter information of the pipeline branch end of the actual nitrogen access point.

3. The coal mine underground nitrogen pipeline end monitoring system according to claim 2, characterized in that: The nitrogen pipeline access booster model is based on the pipeline layout data in the basic data of the mine and relies on the gas pipeline resistance calculation theory to obtain the resistance when the gas passes through the pipeline and confirm the theoretical access point of nitrogen.

4. The coal mine underground nitrogen pipeline end monitoring system according to claim 3, characterized in that: The monitoring system also includes a pressurization device installed at the nitrogen inlet point, the pressurization device comprising: The motor, the housing mounted on the motor, the two screws located inside the housing and rotatably connected to the housing, the two end caps mounted on the housing, and the air intake and exhaust ports opened on the housing; Two of the screws are helical and parallel, and they mesh with each other. One of them is the male rotor, which is connected to the motor output, and the other is the female rotor. The female rotor, male rotor and housing form a "V" shaped area. As the motor rotates, the male rotor rotates counterclockwise, causing the space in the above area to gradually decrease. As the two screws rotate, the above area can move from the air intake port to the air exhaust port, completing the air intake, compression and exhaust process.

5. The coal mine underground nitrogen pipeline end monitoring system according to claim 1, characterized in that: The wireless transmission algorithm model also includes a path planning sub-model, used to construct the pipeline topology and plan the signal transmission path. The steps for constructing the pipeline topology are as follows: First, establish a topology diagram between the downhole monitoring nodes, relay nodes, and control center; Next, the link weight is obtained by weighting the link attenuation, the maximum allowable attenuation, and the historical packet loss rate, which is used to characterize the link quality. The planned signal transmission path includes the following steps: The optimal and backup paths from the monitoring node to the control center are determined using Dijkstra's algorithm, and the steps are as follows: First, perform the initialization steps, define the weight of the control center as 0, the weight of the nodes as ∞, and mark all nodes as unvisited; Then, an iterative process is performed: the node with the smallest weight among the unvisited nodes is selected and marked as visited; the weights of the neighboring nodes of the node with the smallest weight are updated; if the sum of the direct link weights between the node with the smallest weight and its neighboring nodes is less than the weight of the neighboring nodes, the weights of the neighboring nodes are updated to be the sum of the direct link weights between the node with the smallest weight and its neighboring nodes. The termination condition is that when all nodes have been visited, the optimal path is obtained by backtracking; and the links in the optimal path are deleted. The above steps are repeated to obtain the backup path.

6. The coal mine underground nitrogen pipeline end monitoring system according to claim 5, characterized in that: The wireless transmission algorithm model also includes a topology optimization sub-model for optimizing pipeline topology. The optimization of pipeline topology includes the following steps: The monitoring nodes encapsulate real-time data into data frames with sequence numbers and timestamps, and transmit them through the optimal path and backup path. If the control center receives data frames with the same sequence number at the same time, it selects the data frame with the smaller timestamp. If only one message is received, it is parsed directly; if none are received, the data frame is processed according to the rule of retransmission up to three times. Then, a sliding window mechanism is used to count the success rate of data reception. If the success rate is lower than 95%, relay nodes are added to optimize the topology.

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