Gas monitoring and early warning system based on pressure static accumulation model and early warning method thereof

Abstract

The invention discloses a gas monitoring and early warning system based on a pressure electrostatic accumulation model. The gas monitoring and early warning system comprises a pressure fluctuation model, an electrostatic accumulation model and a coupling interaction module which are stored and run in an explosion-proof controller, the explosion-proof controller is connected with a flow velocity sensor and an audible and visual alarm; the pressure fluctuation model calculates the pressure variation according to a pressure change calculation formula; the static accumulation model predicts the charge quantity based on a charge calculation formula, the coupling interaction module verifies the quantitative relation between pressure fluctuation and static accumulation through a simulation experiment, and a coupling empirical formula is obtained; alarm triggering conditions of the explosion-proof controller comprise a pressure change condition and a charge quantity condition. The invention also correspondingly discloses an early warning method. According to the method, static monitoring, pressure monitoring, entity measurement and model prediction are integrated, a low-cost rapid deployment scheme and a technical strengthening scheme with a reinforced redundancy fault-tolerant mechanism are derived, the problems of traditional system splitting monitoring, data faults, hardware defects and the like are solved, and the safety and economical efficiency of the gas conveying pipeline are improved.

Description

Technical Field

[0001] The present invention relates to the field of coal mine gas safety monitoring, and in particular to a gas monitoring and early warning system based on a pressure-static accumulation model. Background Art

[0002] The inventors discovered that under the complex operating conditions of gas pipelines, sudden local pressure fluctuations can significantly affect the accumulation of static electricity. For example, at pipe elbows and throttle valves, pressure fluctuations caused by sudden flow field fluctuations are often accompanied by a sharp increase in static electricity accumulation. However, existing monitoring systems are unable to accurately capture this coupling effect, making safety hazards difficult to detect until they are too late.

[0003] In the field of coal mine gas safety, existing technologies have long faced the following structural defects, which have seriously restricted the accurate early warning of explosion risks and the market competitiveness of technology:

[0004] 1. Fragmentation of the monitoring system leads to failure of early warning

[0005] Technical flaws: Traditional systems monitor pressure fluctuations and static electricity accumulation as independent parameters, lacking quantitative analysis of their dynamic interaction. For example, at a pipe elbow, a sudden pressure change (such as a gradient change of 0.2 MPa / s) can cause a sudden increase in static electricity accumulation (measured as 5×10 -7 C), where C is Coulomb. However, existing technologies only rely on independent thresholds (such as pressure > 0.3 MPa or static electricity > 3×10 -7 C), the coupling effect cannot be captured.

[0006] This results in a relatively high false alarm rate in the existing technology. Especially when the requirements for safe production are high, safety is improved by sacrificing the false alarm rate. The corresponding ineffectiveness leads to high direct economic losses for each production stoppage and maintenance.

[0007] 2. Data silos limit model adaptability

[0008] Technical flaws: Parameters such as pressure, static electricity, and flow rate suffer from data gaps due to differences in sampling frequency and accuracy (e.g., 1Hz for pressure and 0.2Hz for static electricity). These parameters have varying sampling frequencies, accuracies, and reliability, resulting in a lack of effective data fusion mechanisms.

[0009] For example, under a certain throttle valve operating condition, the pressure fluctuation signal is transmitted with a delay of 0.5 seconds, causing the electrostatic prediction error to expand to ±15%.

[0010] This makes it difficult for the system to adapt to complex working conditions (such as low-concentration gas transportation), hindering companies' technological breakthroughs in high-value-added scenarios (such as low-concentration gas power generation).

[0011] 3. Hardware design flaws increase risks

[0012] Technical flaws: The sparse sensor layout (typically 10 meters per node) and insufficient power supply reliability (single power supply failure rate >5%) created monitoring blind spots in high-risk areas such as pipeline flange connections. An accident analysis showed that due to the large sensor spacing (8 meters), local static electricity accumulation exceeding the standard (4.8×10 -7 C), ultimately causing an explosion. This will obviously lead to a loss of brand value for the equipment manufacturer.

[0013] Finally, the coordinated control of pressure and static electricity accumulation is often overlooked in the design and operation of gas transmission systems. For example, when adjusting the transmission pressure, failure to fully consider its potential impact on static electricity accumulation can lead to excessive local static electricity accumulation and increase the risk of explosion.

[0014] These issues are particularly prominent in the following typical scenarios: At bends in gas pipelines, pressure fluctuations caused by sudden changes in the flow field are often accompanied by a sharp increase in static electricity accumulation; before and after the throttle valve, changes in the pressure gradient significantly affect the motion of charged particles, causing changes in the static electricity accumulation pattern; at pipeline joints, pressure fluctuations caused by changes in sealing performance may exacerbate static electricity accumulation; and in areas with sudden changes in gas flow rate, the coupling effect between pressure fluctuations and static electricity accumulation is even more complex. Through pressure-electrostatic coupling analysis, it is possible to predict the sudden change of one parameter (such as static electricity) through the fluctuation data of another parameter (such as pressure), thereby improving the reliability of early warning. Summary of the Invention

[0015] The purpose of the present invention is to provide a gas monitoring and early warning system based on a pressure electrostatic accumulation model, which realizes low-cost and reliable early warning based on the coupling effect of pressure fluctuation and electrostatic accumulation.

[0016] To achieve the above objectives, the gas monitoring and early warning system based on the pressure-electrostatic accumulation model of the present invention includes a pressure fluctuation model, an electrostatic accumulation model, and a coupling interaction module stored and running in an explosion-proof controller; the explosion-proof controller is connected to a flow velocity sensor and an audible and visual alarm, and the flow velocity sensor is used to measure the flow velocity V of the gas flowing inside the gas transmission pipeline;

[0017] The pressure fluctuation model calculates the pressure change ΔP based on the pressure change calculation formula; the pressure change calculation formula is:

[0018]

[0019] Where D is the pipe diameter, g is the acceleration due to gravity, ρ is the gas density, f is the friction coefficient between the inner wall of the pipe and the gas, Δh is the height difference between the two ends of the monitoring section of the gas pipeline, V is the gas flow rate, and L is the pipeline length.

[0020] The static charge accumulation model predicts the amount of charge based on the charge calculation formula, which is:

[0021]

[0022] Where σ is the conductivity, ΔP is the pressure change, A is the pipe cross-sectional area, t is the cumulative time, and ε is the dielectric constant;

[0023] The coupling interaction module verifies the quantitative relationship between pressure fluctuation and electrostatic accumulation through simulation experiments, and obtains the coupling empirical formula:

[0024] Q=0.02×ΔP 2 ; The alarm triggering conditions of the explosion-proof controller include pressure change conditions and charge quantity conditions.

[0025] The explosion-proof controller is also connected to a display screen, a pressure sensor and an electrostatic sensor. The pressure sensor is used to measure the dynamic pressure P of the gas flowing inside the gas transmission pipeline, and the electrostatic sensor is used to monitor the electrostatic charge accumulation Q on the surface of the gas transmission pipeline and the environment around the pipeline in real time.

[0026] There are multiple pressure sensors to form a pressure sensor array, one is arranged every 10 meters along the pipeline, and the number is increased to one every 5 meters at the pipeline elbow and throttle valve;

[0027] Two sets of sound and light alarms are installed, one set is installed in the ground monitoring center for monitoring personnel to coordinate emergency response, and the other set is installed in the underground operation area to remind on-site personnel to avoid danger in time.

[0028] The flow velocity sensor uses ultrasonic transducers and is installed in pairs in the straight section of the pipeline. The flow velocity is calculated by the difference in ultrasonic propagation time between the upstream and downstream directions.

[0029] The system also includes a power management module, which includes a main power supply and a backup power supply, which are connected through a bidirectional DC-DC converter.

[0030] An electrostatic sensor is arranged every 5 meters at the pipeline elbow and the pipeline diameter change section, and the electrostatic sensors are installed symmetrically 1 meter upstream and downstream of the throttle valve. The spark eliminator and ESD protection device are integrated in the electrostatic sensor; at the pipeline elbow and throttle valve, the electrostatic sensor and the pressure sensor correspond one to one, and the corresponding electrostatic sensor and pressure sensor are arranged adjacent to each other.

[0031] The present invention also discloses an early warning method using the above-mentioned gas monitoring and early warning system based on the pressure electrostatic accumulation model, which is characterized by comprising the following steps:

[0032] The pipe elbows and pipe diameter change sections are collectively referred to as monitoring points;

[0033] The first is to collect data from each monitoring point; the dynamic pressure changes in the gas pipeline are monitored in real time through the pressure sensor array, and the surface charge density of the pipeline is obtained in real time through the electrostatic sensor; the explosion-proof controller has a timing module, and the timing module starts timing;

[0034] The second step is to perform model calculations for each monitoring point; calculate ΔP based on the pressure change calculation formula, calculate the charge amount Q based on the charge calculation formula, and refer to the calculation result as Q1; calculate the charge amount Q based on the coupled empirical formula, and refer to the calculation result as Q2; the calculation cycle is once every 1-10 seconds;

[0035] The third is to provide early warnings at different risk levels based on monitoring and calculation results;

[0036] (1) High-risk alarm: When any of the following conditions is met, the sound and light alarm is triggered and emergency control is initiated, including but not limited to closing the valve of the gas transmission pipeline and starting or strengthening the tunnel ventilation: When the high-risk alarm is triggered, the sound and light alarm emits a high-frequency alarm sound with a frequency greater than or equal to 2000 Hz;

[0037] a. The measured Q value of any electrostatic sensor is ≥5×10 -7 C;

[0038] b. For any monitoring point, ΔP calculated by the pressure change calculation formula in one calculation cycle is ≥ 0.4 MPa;

[0039] c. The measured pressure difference ΔP of any pressure sensor in one calculation cycle is ≥ 0.4 MPa;

[0040] d. For any monitoring point, Q1 or Q2 exceeds 5×10 -7 C;

[0041] e. For any monitoring point, Q1 and Q2 exceed 5×10 -7 C;

[0042] (2) Medium risk warning:

[0043] a. The measured Q value of the electrostatic sensor is ≥2×10 -7 When C or ΔP ≥ 0.2MPa, the display shows the risk level and issues a low-frequency alarm;

[0044] b. For any monitoring point, Q1 or Q2 exceeds 2×10 for three consecutive times. -7 C;

[0045] c. For any monitoring point, Q1 and Q2 both exceed 2×10 -7 C;

[0046] (3) Low-risk warning:

[0047] a. The measured Q value of the electrostatic sensor is ≥1×10 -7 When C or ΔP ≥ 0.1MPa, the display shows the risk level and issues a low-frequency alarm;

[0048] b. For any monitoring point, Q1 or Q2 exceeds 2×10 for three consecutive times. -7 C;

[0049] c. For any monitoring point, Q1 and Q2 both exceed 2×10 -7 C;

[0050] When the medium risk warning is triggered, the explosion-proof controller prompts the corresponding risk through the display screen and triggers two sets of sound and light alarms, which emit a medium frequency alarm sound with a frequency of 500 Hz; at the same time, the tunnel ventilation is started or strengthened;

[0051] When the low-risk warning is triggered, the explosion-proof controller prompts the corresponding risk through the display screen and triggers two sets of sound and light alarms. The sound and light alarms emit a low-frequency alarm sound with a frequency of 200 Hz and start or strengthen the tunnel ventilation at the same time.

[0052] Claims layout introduction:

[0053] Claim 1 is the core innovation point, covering the pressure-electrostatic coupling model and its quantitative relationship. It does not require the installation of physical electrostatic sensors and pressure sensors, and the deployment speed is fast and the cost is low.

[0054] Claim 2 is provided with a physical electrostatic sensor and a pressure sensor. The measurement value of the physical sensor and the calculated value of the pressure fluctuation model and the electrostatic accumulation model can be verified with each other to avoid the problem of unilateral failure in the measurement value and the calculated value, that is, to avoid the physical damage of the physical sensor leading to the failure of the measurement value and the failure to be discovered in time, and to avoid the model calculated value from deviating too much under certain conditions and not being discovered (the model can be optimized in a targeted manner after discovery).

[0055] Claim 3 is the preferred setting of the sound and light alarm to meet the dual needs of coordinating emergency response and risk avoidance.

[0056] Claim 4 is the preferred setting of the flow rate sensor to avoid interference from flow field disturbances.

[0057] Claim 5 is used to ensure uninterrupted power supply.

[0058] Claim 6 is a specific arrangement limitation of the physical sensor to ensure the temporal and spatial consistency of pressure and electrostatic parameters.

[0059] Claim 7 is an early warning method that uses a multi-conditional, mutually redundant triggering mechanism. The fulfillment of any one of these conditions triggers an early warning. Therefore, even if a single model or a physical sensor at a monitoring point fails, the system can still issue an early warning, significantly improving system robustness.

[0060] The present invention has the following advantages:

[0061] 1. The low-cost and rapid deployment solution in claim 1 can be realized.

[0062] The solution in claim 1 requires only the installation of an ultrasonic flow sensor. Using a model (a pressure fluctuation model, an electrostatic accumulation model, and a coupled interaction module), the system calculates the pressure change (ΔP) and charge (Q) in real time, eliminating the need for additional pressure or electrostatic sensors. This significantly reduces hardware procurement and maintenance costs. Furthermore, the solution in claim 1 avoids the complexity of densely deployed sensors (e.g., requiring multiple pressure sensors to be installed along a pipeline), making it particularly suitable for long-distance pipelines or scenarios with limited installation conditions (e.g., confined spaces underground), shortening the system setup cycle.

[0063] The alarm trigger conditions of the explosion-proof controller include pressure change conditions and charge conditions (the two conditions are in an OR relationship, and an alarm will be triggered immediately if one is selected), which improves the risk coverage, enhances the timeliness of response, and reduces the risk of missed reports.

[0064] 2. When interference from factors such as dust and humidity causes physical sensor failure or measurement delays, model calculations are not limited by physical sensor performance and can still dynamically predict ΔP and Q based on flow rate data, ensuring the real-time and reliable early warning. Even if a sensor fails to provide data due to failure, blind spots, or installation omissions (such as the absence of an electrostatic sensor at an elbow), the model can still predict parameters, avoiding the risk of underreporting caused by single-point failures. Reducing the number of physical sensors significantly reduces the workload for sensor calibration, replacement, and other maintenance.

[0065] 3. Improved early warning capabilities.

[0066] By dynamically coupling a pressure fluctuation model with a static electricity accumulation model, the system analyzes the interaction between pressure and static electricity in real time (e.g., the enhanced effect of sudden pressure surges on static electricity generation), enabling advanced warning (e.g., triggering an alarm within 3 seconds of throttle valve actuation). The error between model simulation and actual measurement is ≤±4%, reducing false alarm and missed alarm rates, and maintaining high accuracy, especially in the presence of environmental interference such as dust and humidity.

[0067] 4. Adaptability to complex working conditions.

[0068] The pressure model comprehensively considers multiple parameters such as flow rate, friction coefficient, and height difference. The electrostatic model integrates variables such as conductivity, cross-sectional area, and accumulation time. It supports complex scenarios with different pipe diameters, materials, and airflow characteristics, and accurately captures local mutations (such as pressure fluctuations at the pipe diameter change).

[0069] By coupling empirical formula (such as Q = 0.02 × ΔP 2 ) quantifies the correlation between pressure fluctuations and static electricity accumulation, fills the sensor blind spot, and can calculate parameters through the flow rate sensor even if no pressure or static electricity sensor is installed.

[0070] 5. Support redundant fault-tolerant mechanism: The sensor's measured data and the model's predicted value are mutually verified (for example, if the set deviation exceeds ±4%, a self-check will be triggered), avoiding the risk of single-point failure and extending the system life.

[0071] 6. Hardware design enhancement and reliability assurance.

[0072] The power management module supports seamless switching of primary and backup power supplies (<10ms), ensuring uninterrupted operation in complex underground environments.

[0073] Sensors are densely arranged (such as pressure / electrostatic sensors installed every 5 meters at elbows) to eliminate monitoring blind spots; explosion-proof design (such as integrated spark eliminator) improves data acquisition stability.

[0074] 7. Risk classification and emergency response optimization.

[0075] The graded early warning mechanism (high, medium and low risk) combines sound and light alarms (such as high-frequency sound pressure level ≥110dB) with emergency control (closing valves, enhancing ventilation) to improve response timeliness and operational flexibility.

[0076] Support the resource utilization of low-concentration gas (such as power generation scenarios), comply with the "dual carbon" goals, and improve economic benefits.

[0077] In summary, this technology solves problems such as fragmented monitoring, data gaps, and hardware defects in traditional systems through model collaboration, hardware optimization, and intelligent early warning mechanisms, thereby improving the safety and economy of gas transmission pipelines. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 Schematic diagram of the principle of pressure-electrostatic accumulation model;

[0079] Figure 2 Early warning system architecture diagram;

[0080] Figure 3 Model parameter fitting curve;

[0081] Figure 4 Principle framework diagram of the model calculation module;

[0082] Figure 5 Schematic diagram of the power management module and the system;

[0083] Figure 6 Schematic diagram of typical application scenarios;

[0084] Figure 7 Schematic diagram of the cross-sectional velocity of the simulation experiment;

[0085] Figure 8 Schematic diagram of pressure fluctuation in simulation experiment;

[0086] Figure 9 Schematic diagram of multi-section electric potential in simulation experiment.

[0087] Description of reference numerals:

[0088] Data acquisition module 1; model calculation module 2; warning output module 3; power management module 4; mechanical structure 5.

[0089] Pressure sensor 101; electrostatic sensor 102; adjustable wall bracket 103; spark arrester 104; ESD protection device 105; ultrasonic flow rate sensor 106; ultrasonic transducer 107; self-cleaning mechanism 108; environmental monitoring unit 109 (temperature and humidity + dust sensor); temperature and humidity sensor 110; dust concentration sensor 111;

[0090] Data processing unit 201; model operation unit 202; storage unit 203; communication interface 204; high-performance processor (ARM Cortex-A53) 205; FPGA accelerator 206;

[0091] Sound and light alarm 301; display screen (preferably an industrial touch screen) 302; interface and remote communication unit 303;

[0092] Main power supply 401; EMI filter 402; backup power supply 403; bidirectional DC-DC converter 404; power switching device 405; power switching controller 406; switching actuator 407. Conventional technologies involved in the present invention, such as switching actuator 407, will not be described in detail to avoid excessive length of the document. DETAILED DESCRIPTION

[0093] like Figures 1 to 9 As shown, the present invention discloses a gas monitoring and early warning system based on a pressure electrostatic accumulation model, including a pressure fluctuation model, an electrostatic accumulation model and a coupling interaction module stored and running in an explosion-proof controller; the explosion-proof controller is connected to a flow rate sensor and an audible and visual alarm, and the flow rate sensor is used to measure the flow rate V of the gas flowing inside the gas transmission pipeline.

[0094] The explosion-proof controller can be any type of computer or embedded system. The computing module of the explosion-proof controller preferably uses a high-performance processor (ARM Cortex-A53, main frequency 1.2GHz) and an FPGA accelerator (Xilinx Kintex UltraScale KU115, 5.2TOPS) to realize parallel calculation of the pressure-electrostatic model, support real-time data processing and dynamic risk classification, and shorten the warning response time. The flow rate sensor uses an ultrasonic transducer and is installed in pairs in the straight section of the pipeline (at a distance of ≥10 times the pipe diameter from the elbow) to measure the gas flow rate in the pipeline by the time difference between the upstream and downstream flows. The explosion-proof controller can be fixed to the underground tunnel wall or pipeline support through an anti-seismic slide, or it can be installed in a ground monitoring center (studio).

[0095] The pressure fluctuation model calculates the pressure change ΔP based on the pressure change calculation formula; the pressure change calculation formula is:

[0096]

[0097] Where D is the pipe diameter, g is the acceleration due to gravity (9.8m / s 2 ); ρ is the gas density, f is the friction coefficient between the inner wall of the pipeline and the gas, Δh is the height difference between the two ends of the monitoring section of the gas transmission pipeline (Δh is used to quantify the effect of gravity on the gas pressure in the pipeline. For example, if the inlet end is higher than the outlet end, Δh is a negative value, and gravity will reduce the static pressure of the pipeline; otherwise, it will increase it); V is the gas flow rate; L is the pipeline length;

[0098] The static charge accumulation model predicts the amount of charge based on the charge calculation formula, which is:

[0099]

[0100] Where σ is the conductivity, ΔP is the pressure change, A is the pipe cross-sectional area, t is the accumulated time (of the timing module), and ε is the dielectric constant;

[0101] The coupling interaction module verifies the quantitative relationship between pressure fluctuation and electrostatic accumulation through simulation experiments, and obtains the coupling empirical formula:

[0102] Q=0.02×ΔP 2 ;

[0103] The model is a nonlinear quadratic function, using R 2 Evaluate the goodness of fit, and the fitting results show R 2 =0.92, indicating that the model fits the experimental data well and can effectively quantify the interaction between pressure and electrostatics.

[0104] At the same time, the simulation experiment sets the following boundary conditions:

[0105] Pipe material: Steel (conductivity σ=5.810 7 S / m), inner wall roughness 0.05mm;

[0106] Gas composition: methane (CH4) volume concentration 95%, containing a small amount of carbon dioxide (CO2, 3%) and nitrogen (N2, 2%);

[0107] Environmental parameters: temperature 25°C, relative humidity 50% RH, standard atmospheric pressure;

[0108] Pipeline geometry: diameter D = 0.5m, straight pipe length L = 20m, elbow curvature radius R = 1.5D; flow rate range: 5~15m / s, covering common working conditions of gas transportation.

[0109] The above conditions were used to verify the relationship between pressure fluctuation (ΔP = 0.1 ~ 0.5 MPa) and static electricity accumulation (Q = 1 × 10 -7 –5×10 -7 C) to ensure the model's applicability in actual gas transportation scenarios. Simulation boundary conditions (such as pipeline material and gas composition) are also set, allowing the model to accurately adapt to different operating conditions. Even without physical sensors installed, it can calculate pressure changes and charge using flow rate data and boundary conditions, reducing hardware dependence while improving warning authenticity.

[0110] The present invention quantifies the interaction between pressure and static electricity through a dynamic coupling model, which can make up for the blind spots and delays of the sensor (even if no electrostatic sensor or pressure sensor is installed at a certain elbow or pipe diameter change, the pressure change and charge amount can be calculated), which helps to reduce the false alarm rate and missed alarm rate. When environmental interference (dust, humidity, installation location, etc.) causes the sensor to be inaccurate or delayed, it can also promptly and accurately alarm, thereby improving the accuracy of the early warning. The technical solution of claim 1 is also convenient for quickly and low-cost deployment of the early warning system, that is, it is not necessary to install a pressure sensor and an electrostatic sensor. As long as a flow rate sensor is installed, ΔP and Q can be calculated, so that an early warning can be issued according to the early warning conditions. Since the flow rate sensor does not need to be installed in multiples like a pressure sensor and an electrostatic sensor, the technical solution that can omit the physical sensor has a higher deployment efficiency.

[0111] Through real-time analysis of coupled empirical formulas, feedback on the enhanced effect of pressure fluctuations on static electricity generation can be achieved, and explosion risks can be predicted.

[0112] The pressure fluctuation model has the following advantages:

[0113] a. Adapt to complex working conditions: Covering multiple parameters such as flow rate, friction, and height difference, improving accuracy under complex working conditions, comprehensively considering different working conditions (such as height difference, pipe diameter), different material parameters (such as friction coefficient), and different airflow characteristics (density), significantly improving the accuracy of the model under complex working conditions.

[0114] b. Dynamically quantify pressure changes, calculate pressure fluctuations in the pipeline in real time, and accurately capture local mutations (such as diameter changes where the D value changes).

[0115] The electrostatic accumulation model has the following advantages:

[0116] a. Adapt to complex working conditions: Covering multiple parameters such as conductivity, pressure change, pipe cross-sectional area, cumulative time and dielectric constant, it improves the accuracy under complex working conditions, comprehensively considers different working conditions, and greatly improves the accuracy of the model under complex working conditions. It can predict the trend of static electricity accumulation in advance (for example, when the pressure suddenly increases by 0.5MPa, the predicted Q reaches 5×10 - 7 C) helps to provide early warning.

[0117] b. Low error verification: The error between simulation and measurement is ≤±4%, reducing the false alarm rate.

[0118] The pressure fluctuation model and electrostatic accumulation model also provide a technical basis for the low-cost deployment of early warning systems in gas transmission pipelines that are not equipped with pressure sensors and electrostatic sensors.

[0119] The pressure fluctuation model, electrostatic accumulation model, and coupled interaction module work together to provide the following synergistic advantages:

[0120] a. Dynamic coupling warning: The pressure model provides real-time ΔP data, and the electrostatic model predicts the Q value based on this data, achieving advanced risk warning (such as triggering an alarm within 3 seconds after the throttle valve is actuated).

[0121] b. Redundant fault-tolerant mechanism: When pressure sensors and electrostatic sensors are installed, the sensor's actual measurement and model prediction are mutually verified (a self-check can be set to occur if the deviation exceeds ±4%) to avoid the risk of single-point failure.

[0122] c. High economic value: Achieve low-cost early warning, support the resource utilization of low-concentration gas (such as power generation scenarios), and comply with the "dual carbon" goals.

[0123] The explosion-proof controller is also connected to a display screen (preferably an industrial touch screen), a pressure sensor and an electrostatic sensor. The pressure sensor is used to measure the dynamic pressure P of the gas flowing inside the gas transmission pipeline, and the electrostatic sensor is used to monitor the electrostatic charge accumulation Q on the surface of the gas transmission pipeline and the environment around the pipeline in real time.

[0124] There are multiple pressure sensors to form a pressure sensor array, which is arranged every 10 meters along the pipeline and is encrypted to one every 5 meters at the pipeline elbow and throttle valve.

[0125] The pressure sensor uses a piezoresistive sensor (Honeywell MPR-001000-5PA, accuracy ±0.1% FS). The electrostatic sensor is specifically installed on the outer wall of the pipe. Based on the field grinding principle, the preferred model is Elettrostatica E3000-Ex, with a range of 0-10μC / m 2 The display screen is preferably placed in the ground monitoring center (studio). Densely arranged pressure sensors can capture local pressure changes.

[0126] Two sets of sound and light alarms are installed: one set is installed in the ground monitoring center for monitoring personnel to coordinate emergency response, and the other set is installed in the underground operation area to remind on-site personnel to avoid danger in time;

[0127] An electrostatic sensor is arranged every 5 meters at the pipeline elbow and the pipeline reducer, and the electrostatic sensors are installed symmetrically 1 meter upstream and downstream of the throttle valve. The spark eliminator and ESD protection device are integrated in the electrostatic sensor; at the pipeline elbow and throttle valve, the electrostatic sensor corresponds to the pressure sensor one by one, and the corresponding electrostatic sensor is arranged adjacent to the pressure sensor to ensure the temporal and spatial consistency of the pressure and electrostatic parameters.

[0128] The explosion-proof design and redundant protection of the electrostatic sensor ensure stable acquisition of electrostatic data under complex working conditions. The placement of an electrostatic sensor every 5 meters at pipe elbows and pipe reducers is based on the following technical considerations of the inventors:

[0129] Sudden changes in the flow field (such as changes in flow velocity direction and increased turbulence) lead to increased friction between the gas and the pipe wall, significantly increasing the rate of static electricity generation. For example, the secondary flow outside the elbow can intensify the separation of charged particles, and the charge density can reach 3-5 times that of the straight pipe section. Pipe elbows and pipe diameter reduction sections are places where the flow field suddenly changes. The amount of charge accumulated in these places is higher than that in the straight pipe section where the flow field is stable. Therefore, it is usually only necessary to monitor the charge at the sudden change point to ensure it does not exceed the limit (the charge at the stable flow field section will be lower).

[0130] Electrostatic sensors and pressure sensors are collectively referred to as physical sensors. The measured values ​​of the physical sensors can be cross-checked with the calculated values ​​of the pressure fluctuation model and the electrostatic accumulation model to avoid physical damage to the physical sensors that causes invalid measured values ​​and cannot be discovered in time, and to avoid excessive deviations in the calculated values ​​of the model under certain conditions that cannot be discovered (the model can be optimized in a targeted manner after discovery).

[0131] The flow velocity sensor uses ultrasonic transducers and is installed in pairs in the straight section of the pipeline (at a distance of ≥10 times the pipe diameter from the elbow). The flow velocity (V) is calculated by the difference in ultrasonic propagation time between the forward and reverse flow.

[0132] The flow velocity sensor uses ultrasonic transducers installed in pairs in the straight pipe section to eliminate the influence of flow field disturbances.

[0133] The system also includes a power management module, which includes a main power supply (AC220V±10%, 50Hz) and a backup power supply (20000mAh lithium battery pack) connected via a bidirectional DC-DC converter.

[0134] The power management module enables seamless switching between primary and backup power sources in less than 10 milliseconds. The primary and backup power supplies ensure uninterrupted operation of the system in the complex underground environment, preventing power outages that could cause early warning failures.

[0135] The present invention also discloses an early warning method using the above-mentioned gas monitoring and early warning system based on the pressure electrostatic accumulation model, comprising the following steps:

[0136] The pipe elbows and pipe diameter change sections are collectively referred to as monitoring points;

[0137] The first is to collect data at each monitoring point; the dynamic pressure change (ΔP, unit: Pa, i.e. Pascal) in the gas pipeline is monitored in real time through the pressure sensor array, and the surface charge density (σ, unit: μC / m 2 , i.e. microcoulombs per square meter); the explosion-proof controller has a timing module, and the timing module starts timing;

[0138] The second is to perform model calculations for each monitoring point; ΔP is calculated based on the pressure change calculation formula, the charge amount Q is calculated based on the charge calculation formula, and the calculation result is referred to as Q1; the charge amount Q is calculated based on the coupled empirical formula, and the calculation result is referred to as Q2; the calculation cycle is calculated once every 1-10 seconds (inclusive) (the shorter the calculation cycle, the more timely the alarm, but the energy consumption is relatively high and the false alarm is relatively high; the longer the calculation cycle, the lower the energy consumption and the fewer false alarms, but the alarm time is relatively delayed by several seconds; the specific value of the calculation cycle is specified by the staff based on the timeliness requirements of the alarm and the tolerance of the hardware performance);

[0139] The third is to provide early warnings at different risk levels based on monitoring and calculation results;

[0140] (1) High-risk alarm: When any of the following conditions is met, two sets of sound and light alarms are triggered (sound pressure level ≥ 110dB, flash frequency 1-2Hz) and emergency control is initiated, including but not limited to closing the valve of the gas transmission pipeline and starting or strengthening the tunnel ventilation: When the high-risk alarm is triggered, the sound and light alarm emits a high-frequency alarm sound with a frequency greater than or equal to 2000 Hz;

[0141] a. The measured Q value of any electrostatic sensor is ≥5×10 -7 C (Coulomb);

[0142] b. For any monitoring point (the D value may be different at different monitoring points), ΔP calculated using the pressure change calculation formula in one calculation cycle is ≥ 0.4 MPa (megapascals);

[0143] c. The measured pressure difference ΔP of any pressure sensor in one calculation cycle is ≥ 0.4 MPa;

[0144] d. For any monitoring point, Q1 or Q2 exceeds 5×10 -7 C;

[0145] e. For any monitoring point, Q1 and Q2 exceed 5×10 -7 C;

[0146] (2) Medium risk warning:

[0147] a. The measured Q value of the electrostatic sensor is ≥2×10 -7 When C or ΔP ≥ 0.2MPa, the display shows the risk level and issues a low-frequency alarm;

[0148] b. For any monitoring point, Q1 or Q2 exceeds 2×10 for three consecutive times. -7 C;

[0149] c. For any monitoring point, Q1 and Q2 both exceed 2×10 -7 C;

[0150] (3) Low-risk warning:

[0151] a. The measured Q value of the electrostatic sensor is ≥1×10 -7 When C or ΔP ≥ 0.1MPa, the display shows the risk level and issues a low-frequency alarm;

[0152] b. For any monitoring point, Q1 or Q2 exceeds 2×10 for three consecutive times. -7 C;

[0153] c. For any monitoring point, Q1 and Q2 both exceed 2×10 -7 C;

[0154] When the medium-risk warning is triggered, the explosion-proof controller prompts the corresponding risk through the display screen and triggers two sets of sound and light alarms. The sound and light alarms emit a medium-frequency alarm sound with a frequency of 500 Hz; at the same time, the tunnel ventilation is started or strengthened.

[0155] When the low-risk warning is triggered, the explosion-proof controller prompts the corresponding risk through the display screen and triggers two sets of sound and light alarms. The sound and light alarms emit a low-frequency alarm sound with a frequency of 200 Hz and start or strengthen the tunnel ventilation at the same time.

[0156] Medium and low-risk warnings alert personnel to risks. If a medium or low-risk warning persists for an extended period, personnel will conduct manual inspections and maintenance. The ground monitoring center coordinates emergency responses based on the alert level, and on-site personnel in the underground operations area will implement risk avoidance measures or conduct inspections and remediation based on the alert level. If a medium or low-risk warning persists for an extended period, the gas pipeline valves will be closed, ventilation maintained, and the gas delivery system will be inspected after safety is achieved.

[0157] The above embodiments are only used to illustrate rather than limit the technical solutions of the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the present invention can still be modified or replaced by equivalents. Any modification or partial replacement that does not depart from the spirit and scope of the present invention should be included in the scope of the claims of the present invention.

Claims

1. Gas monitoring and early warning system based on pressure electrostatic accumulation model, characterized by It includes a pressure fluctuation model, an electrostatic accumulation model, and a coupling interaction module stored and running in the explosion-proof controller; the explosion-proof controller is connected to a flow rate sensor and an audible and visual alarm, and the flow rate sensor is used to measure the flow rate V of the gas flowing inside the gas transmission pipeline; The pressure fluctuation model calculates the pressure change ΔP based on the pressure change calculation formula; the pressure change calculation formula is: Where D is the pipe diameter, g is the acceleration due to gravity, ρ is the gas density, f is the friction coefficient between the inner wall of the pipe and the gas, Δh is the height difference between the two ends of the monitoring section of the gas pipeline, V is the gas flow rate, and L is the pipeline length. The static charge accumulation model predicts the amount of charge based on the charge calculation formula, which is: Where σ is the conductivity, ΔP is the pressure change, A is the pipe cross-sectional area, t is the cumulative time, and ε is the dielectric constant; The coupling interaction module verifies the quantitative relationship between pressure fluctuation and electrostatic accumulation through simulation experiments, and obtains the coupling empirical formula: Q=0.02×ΔP 2 ; The alarm triggering conditions of the explosion-proof controller include pressure change conditions and charge quantity conditions.

2. The gas monitoring and early warning system based on the pressure electrostatic accumulation model according to claim 1 is characterized in that: The explosion-proof controller is also connected to a display screen, a pressure sensor and an electrostatic sensor. The pressure sensor is used to measure the dynamic pressure P of the gas flowing inside the gas transmission pipeline, and the electrostatic sensor is used to monitor the electrostatic charge accumulation Q on the surface of the gas transmission pipeline and the environment around the pipeline in real time. There are multiple pressure sensors to form a pressure sensor array, which is arranged every 10 meters along the pipeline and is encrypted to one every 5 meters at the pipeline elbow and throttle valve.

3. The gas monitoring and early warning system based on the pressure electrostatic accumulation model according to claim 2 is characterized in that: Two sets of sound and light alarms are installed, one set is installed in the ground monitoring center for monitoring personnel to coordinate emergency response, and the other set is installed in the underground operation area to remind on-site personnel to avoid danger in time.

4. The gas monitoring and early warning system based on the pressure electrostatic accumulation model according to claim 1 is characterized in that: The flow velocity sensor uses ultrasonic transducers and is installed in pairs in the straight section of the pipeline. The flow velocity is calculated by the difference in ultrasonic propagation time between the upstream and downstream directions.

5. The gas monitoring and early warning system based on the pressure electrostatic accumulation model according to claim 1 is characterized in that: The system also includes a power management module, which includes a main power supply and a backup power supply, which are connected through a bidirectional DC-DC converter.

6. The gas monitoring and early warning system based on the pressure electrostatic accumulation model according to claim 3 is characterized in that: An electrostatic sensor is arranged every 5 meters at the pipeline elbow and the pipeline diameter change section, and the electrostatic sensors are installed symmetrically 1 meter upstream and downstream of the throttle valve. The spark eliminator and ESD protection device are integrated in the electrostatic sensor; at the pipeline elbow and throttle valve, the electrostatic sensor and the pressure sensor correspond one to one, and the corresponding electrostatic sensor and pressure sensor are arranged adjacent to each other.

7. The early warning method of the gas monitoring and early warning system based on the pressure electrostatic accumulation model according to claim 6 is characterized in that: The following steps are involved: The pipe elbows and pipe diameter change sections are collectively referred to as monitoring points; The first is to collect data at each monitoring point; the dynamic pressure changes in the gas pipeline are monitored in real time through the pressure sensor array, and the surface charge density of the pipeline is obtained in real time through the electrostatic sensor; There is a timing module in the explosion-proof controller, and the timing module starts timing; The second step is to perform model calculation for each monitoring point; calculate ΔP based on the pressure change calculation formula, calculate the charge amount Q based on the charge calculation formula, and refer to the calculation result as Q1; Calculate the charge Q based on the coupled empirical formula and refer to the result as Q2; The calculation cycle is once every 1-10 seconds; The third is to provide early warnings at different risk levels based on monitoring and calculation results; (1) High-risk alarm: When any of the following conditions is met, the sound and light alarm is triggered and emergency control is initiated, including but not limited to closing the valve of the gas transmission pipeline and starting or strengthening the tunnel ventilation: When the high-risk alarm is triggered, the sound and light alarm emits a high-frequency alarm sound with a frequency greater than or equal to 2000 Hz; a. The measured Q value of any electrostatic sensor is ≥5×10 -7 C; b. For any monitoring point, ΔP calculated by the pressure change calculation formula in one calculation cycle is ≥ 0.4 MPa; c. The measured pressure difference ΔP of any pressure sensor in one calculation cycle is ≥ 0.4 MPa; d. For any monitoring point, Q1 or Q2 exceeds 5×10 -7 C; e. For any monitoring point, Q1 and Q2 exceed 5×10 -7 C; (2) Medium risk warning: a. The measured Q value of the electrostatic sensor is ≥2×10 -7 When C or ΔP ≥ 0.2MPa, the display shows the risk level and issues a low-frequency alarm; b. For any monitoring point, Q1 or Q2 exceeds 2×10 for three consecutive times. -7 C; c. For any monitoring point, Q1 and Q2 both exceed 2×10 -7 C; (3) Low-risk warning: a. The measured Q value of the electrostatic sensor is ≥1×10 -7 When C or ΔP ≥ 0.1MPa, the display shows the risk level and issues a low-frequency alarm; b. For any monitoring point, Q1 or Q2 exceeds 2×10 for three consecutive times. -7 C; c. For any monitoring point, Q1 and Q2 both exceed 2×10 -7 C; When the medium risk warning is triggered, the explosion-proof controller prompts the corresponding risk through the display screen and triggers two sets of sound and light alarms, which emit a medium frequency alarm sound with a frequency of 500 Hz; at the same time, the tunnel ventilation is started or strengthened; When the low-risk warning is triggered, the explosion-proof controller prompts the corresponding risk through the display screen and triggers two sets of sound and light alarms. The sound and light alarms emit a low-frequency alarm sound with a frequency of 200 Hz and start or strengthen the tunnel ventilation at the same time.

Images