Vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipe gallery

Abstract

The invention discloses a vehicle-mounted gas leakage monitoring system for a petroleum and petrochemical pipe gallery, and relates to the technical field of gas leakage monitoring, and the system comprises an environment model which is composed of a temperature field model, a humidity field model and an illumination intensity field model, and is used for monitoring environment parameters around the pipe gallery in real time through a temperature sensor, a humidity sensor and an illumination sensor; a dynamic environment model is established according to the environment data, and the influence of environment change on gas leakage is predicted; the pipe gallery parameter monitoring module is used for acquiring physical parameters, including permeability and density parameters, of buried soil or concrete of the pipe gallery; according to the gas leakage model, the diffusion path and speed of gas leakage are determined in combination with the pipe gallery buried physical parameters and the environment model. According to the method, the state of the pipe gallery is comprehensively considered by establishing the environment model and the pipe gallery buried physical parameters, the gas leakage monitoring requirements under different environment conditions are met according to the state of the pipe gallery, and flexible switching among multiple monitoring modes can be achieved according to corresponding parameter changes.

Description

Technical Field

[0001] The invention relates to the technical field of gas leakage monitoring, and in particular to a vehicle-mounted gas leakage monitoring system for a petroleum and petrochemical pipeline gallery. Background Art

[0002] Vehicle-mounted gas detection and leak monitoring systems play a vital role in industrial and urban infrastructure, especially in the safety monitoring of natural gas and oil pipelines. The system usually uses mid-infrared laser absorption spectroscopy technology to detect changes in gas concentration at the part per million (PPB) level. The system is equipped with a high-precision Beidou / GPS positioning module and a wind speed and direction sensor, which can monitor gas concentration in real time while the vehicle is driving, and calculate the location of the leak source through an atmospheric diffusion model.

[0003] Announcement No. CN105203264B discloses a gas leakage monitoring method, a gas leakage monitoring device and a system. The monitoring method disclosed in the case includes: receiving a movement instruction sent by a control terminal, controlling multiple gas leakage monitoring devices to move to different positions in the gas leakage area respectively; obtaining a panoramic image of the location of each of the gas leakage monitoring devices; detecting the leakage gas concentration at the location of each of the gas leakage monitoring devices; transmitting the leakage gas concentration and the panoramic image at the location of each of the gas leakage monitoring devices to the control terminal. The case also proposes a gas leakage monitoring device and system using the method. The gas leakage monitoring method can monitor the changing trend of the leakage gas concentration in the gas leakage area by setting multiple gas leakage monitoring devices.

[0004] The construction locations of pipeline corridors are divided into two types: above ground and underground. Underground pipeline corridors do not occupy ground space, which is conducive to intensive use of land; they can avoid the clutter of pipelines on the ground and improve the aesthetics of the environment; they can reduce the impact of external factors on pipelines and improve safety.

[0005] However, underground pipe galleries are difficult to maintain, and the inspection and maintenance of underground pipe galleries are relatively difficult. In addition, the gas leakage monitoring system of underground pipe galleries usually relies on a single detection method, and fails to fully consider the impact of environmental factors on gas leakage detection, resulting in insufficient detection accuracy and reliability. With the development of the petroleum and petrochemical industry, the scale and complexity of underground pipe galleries continue to increase, and traditional monitoring methods can no longer meet the needs of efficient and accurate leakage detection. Therefore, it is of great significance to develop a gas leakage monitoring system that comprehensively considers environmental factors and pipe gallery material properties. Summary of the invention

[0006] The purpose of the present invention is to provide a monitoring system that can comprehensively consider environmental factors such as temperature, light, humidity, etc., and determine the gas leakage status according to the soil or concrete parameters buried in the tunnel, so as to improve the accuracy and reliability of gas leakage detection.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a vehicle-mounted gas leakage monitoring system for a petroleum and petrochemical pipeline gallery, comprising:

[0008] The environmental model consists of a temperature field model, a humidity field model, and a light intensity field model. The environmental parameters around the pipe gallery are monitored in real time through temperature sensors, humidity sensors, and light sensors. Based on the environmental data, a dynamic environmental model is established to predict the impact of environmental changes on gas leakage.

[0009] The tunnel parameter monitoring module obtains the physical parameters of the soil or concrete where the tunnel is buried, including permeability and density parameters;

[0010] The gas leakage model combines the buried physical parameters of the pipeline corridor with the environmental model to determine the diffusion path and speed of the gas leakage;

[0011] The gas sensor matrix consists of an internal collection matrix and an external collection matrix for monitoring the gas concentration inside and outside the corridor and comprehensively analyzing the gas leakage status.

[0012] The wireless communication module transmits the monitoring data to the monitoring center for data analysis and processing.

[0013] In one or more embodiments of the present invention, the diffusion path and speed of gas leakage are obtained according to the permeability and density of the monitored location in combination with the environmental model, and a gas leakage diffusion model is established according to the gas leakage status collected by the internal collection matrix of the pipe gallery and the external collection matrix of the pipe gallery to predict the gas diffusion behavior under different leakage amounts and environmental conditions;

[0014] Through big data analysis and artificial intelligence technology, gas leakage patterns can be identified, data trends can be analyzed, and real-time reports can be generated.

[0015] In one or more embodiments of the present invention, establishing an environment model includes:

[0016] Temperature field model: The temperature data around the pipe gallery is collected through multi-point temperature sensors, and a three-dimensional temperature field model is constructed using interpolation algorithms and data fitting technology. The temperature field model reflects the temperature changes in different seasons and time periods.

[0017] Humidity field model: The humidity data around the pipe gallery is collected through humidity sensors, and a humidity field model is constructed using multiple regression analysis and data fitting technology. The humidity field model reflects the humidity changes under different environmental conditions.

[0018] Light intensity field model: The light intensity data around the tunnel is collected through light sensors, and the light intensity field model is constructed using interpolation algorithms and data fitting technology. The light intensity field model reflects the changes in light under different time periods and weather conditions.

[0019] In one or more embodiments of the present invention, the gas sensor matrix comprises:

[0020] The internal data collection matrix of the pipe gallery is composed of infrared sensors, electrochemical sensors and semiconductor sensors, which are set at the node positions of the pipe gallery and equipped with protective covers to ensure the stability of the sensors.

[0021] Pipe gallery external data collection matrix: It is composed of infrared sensors and laser sensors, installed on a vehicle used to monitor gas leaks and monitors the location of the pipe gallery.

[0022] In one or more embodiments of the present invention, the gas leakage state determination method comprises the following steps:

[0023] Soil parameter determination: The physical parameters of the soil buried in the tunnel, such as permeability, density and water content, are determined experimentally, and combined with the environmental model to determine the diffusion path and speed of gas leakage;

[0024] Concrete parameter determination: Physical parameters such as permeability, density and porosity of buried concrete in the tunnel are measured experimentally, and the diffusion path and speed of gas leakage are determined in combination with environmental models;

[0025] The gas concentration changes are monitored in real time through the gas sensor matrix. The sensor layout is determined according to the environmental model and the gas leakage diffusion model, and the monitoring coverage and sensitivity are measured;

[0026] The gas leakage status is determined based on the diffusion path and speed of the gas leakage.

[0027] In one or more embodiments of the present invention, the gas diffusion path and velocity are calculated based on the gas data inside the pipe gallery and the gas data outside the pipe gallery:

[0028] Data collection includes internal data and external data of the corridor:

[0029] Data inside the tunnel: Real-time monitoring of gas concentration through the internal data collection matrix of the tunnel.

[0030] Environmental parameters: collect environmental parameters such as temperature, humidity and pressure;

[0031] Pipeline gallery external data: monitor the gas concentration in the external environment through the pipeline gallery external acquisition matrix;

[0032] Environmental parameters: collect temperature, humidity, wind speed and wind direction data of the external environment;

[0033] The gas diffusion equation is used to describe the diffusion process of gas inside and outside the tunnel. The diffusion equation takes into account factors such as gas concentration gradient, temperature, humidity and wind speed.

[0034] The diffusion equation is discretized using the finite element method or the finite difference method to solve the change of the gas concentration field;

[0035] Set reasonable boundary conditions, gas concentration, temperature and humidity at the inlet and outlet of the tunnel to ensure the accuracy of numerical simulation;

[0036] Diffusion path and velocity calculation:

[0037] Path calculation: Based on the numerical simulation results, draw a gas concentration value line graph to determine the main path of gas diffusion;

[0038] Use the streamline method to track the movement path of gas molecules and determine the specific route of gas diffusion;

[0039] Speed ​​calculation:

[0040] Through the numerical simulation results, the concentration change rate of the gas at different locations is calculated to determine the gas diffusion rate;

[0041] The particle tracking method is used to simulate the motion of gas molecules and calculate the average velocity of gas diffusion.

[0042] In one or more embodiments of the present invention, Fick's law is used to describe the diffusion process of methane inside and outside the pipeline gallery:

[0043]

[0044] Where J is the diffusion flux, D is the diffusion coefficient, C is the gas concentration, and x is the position;

[0045] The finite element method is used to discretize the diffusion equation and solve the change of gas concentration field;

[0046] The gas concentration, temperature, and humidity at the tunnel inlet and outlet are input into the model as boundary conditions;

[0047] Path calculation:

[0048] Based on the numerical simulation results, draw the methane concentration contour map to determine the main path of gas diffusion;

[0049] Use the streamline method to track the movement path of methane molecules and determine the specific route of gas diffusion;

[0050] Speed ​​calculation:

[0051] Through the numerical simulation results, the concentration change rate of methane at different locations is calculated to determine the gas diffusion rate;

[0052] The particle tracking method is used to simulate the motion of methane molecules and calculate the average velocity of gas diffusion.

[0053] In one or more embodiments of the present invention, the soil or concrete permeability is calculated:

[0054] Soil constant head permeability calculation formula:

[0055]

[0056] Where k is the permeability coefficient, Q is the amount of water passing through the soil sample, L is the sample length, A is the sample cross-sectional area, h is the hydraulic head difference, and t is time;

[0057] Soil variable head infiltration calculation formula:

[0058]

[0059] Where a is the cross-sectional area of ​​the test tube, L is the sample length, A is the cross-sectional area of ​​the sample, t is the time, h1 and h2 are the initial and final water heads respectively;

[0060] Concrete pressure penetration calculation formula:

[0061]

[0062] Where k is the permeability coefficient, Q is the amount of water passing through the concrete sample, A is the cross-sectional area of ​​the sample, ΔP is the water pressure difference, and t is time.

[0063] In one or more embodiments of the present invention, soil or concrete density is calculated:

[0064] Soil wet density calculation formula:

[0065] ρw=Vmw;

[0066] Among them, ρw is the wet density, mw is the wet soil mass, and V is the sample volume;

[0067] Soil dry density calculation formula:

[0068] ρd=Vmd;

[0069] Among them, ρd is the dry density, m_d is the dry soil mass, and V is the sample volume;

[0070] Concrete density calculation formula:

[0071] Density: ρ = Vm;

[0072] Where ρ is the density, m is the mass of the concrete sample, and V is the volume of the sample.

[0073] In one or more embodiments of the present invention, data processing and analysis: monitoring data is transmitted to a monitoring center via a wireless communication module for real-time data processing and analysis. Big data analysis and artificial intelligence technology are used to identify gas leakage patterns, analyze data trends, and combine historical data and environmental models to conduct leakage risk assessment and early warning to provide decision support.

[0074] Through the above technical solution, the present invention has the following beneficial effects:

[0075] 1. This application comprehensively considers the state of the corridor by establishing an environmental model and the physical parameters of the buried corridor, and adapts to the gas leakage monitoring needs under different environmental conditions according to the state of the corridor. Due to the different environmental parameters of the corridor, it can flexibly switch among multiple monitoring methods according to the corresponding parameter changes, and adjust the monitoring method according to the environment in which the corridor is located.

[0076] 2. Further improve the accuracy and reliability of gas leakage monitoring to adapt to the needs of gas leakage monitoring under different environmental conditions. Due to the influence of environmental parameters on the monitoring status, the best monitoring method can be selected to monitor the status of pipeline corridors in different locations, providing multiple monitoring methods to flexibly respond to different leakage situations.

[0077] 3. This application determines the diffusion path and speed of gas leakage based on the physical parameters of the soil or concrete buried in the corridor and combines it with the environmental model. When conducting gas monitoring, it uses a variety of gas sensors to monitor the gas concentration inside and outside the corridor, comprehensively analyzes the gas leakage status, reduces maintenance costs, and improves stability and reliability.

[0078] 4. Combined with the impact of the environment on the characteristics of buried objects in the corridor, that is, the changes in the physical parameters of the soil and concrete buried in the corridor under different lighting, temperature, humidity and conditions, determine the diffusion state of gas leakage, realize real-time monitoring and data analysis for different gas diffusion states, timely warn and handle leakage incidents, and further improve the reliability of gas leakage monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 It is a system schematic diagram of the present invention. DETAILED DESCRIPTION

[0080] The following will disclose multiple embodiments of the present invention with the accompanying drawings. For the purpose of clear description, many practical details will be described together in the following description. However, it should be understood that these practical details should not be used to limit the present invention. In other words, in some embodiments of the present invention, these practical details are not necessary. And if it is possible to implement, the features of different embodiments can be applied interchangeably.

[0081] Unless otherwise defined, all words (including technical and scientific terms) used herein have their usual meanings, which can be understood by those familiar with this field. Furthermore, the definitions of the above words in commonly used dictionaries should be interpreted as the meanings consistent with the relevant fields of the present invention in the content of this specification. Unless otherwise clearly defined, these words will not be interpreted as idealized or overly formal meanings.

[0082] See also Figure 1 The present invention provides a vehicle-mounted gas leakage monitoring system for a petroleum and petrochemical pipeline gallery, which is used to monitor the gas leakage status of the pipeline gallery under different environmental conditions.

[0083] In one embodiment, a gas leak monitoring system comprises:

[0084] The environmental model consists of a temperature field model, a humidity field model, and a light intensity field model. The environmental parameters around the pipe gallery are monitored in real time through temperature sensors, humidity sensors, and light sensors. Based on the environmental data, a dynamic environmental model is established to predict the impact of environmental changes on gas leakage.

[0085] The tunnel parameter monitoring module obtains the physical parameters of the soil or concrete where the tunnel is buried, including permeability and density parameters;

[0086] The gas leakage model combines the buried physical parameters of the pipeline corridor with the environmental model to determine the diffusion path and speed of the gas leakage;

[0087] The gas sensor matrix consists of an internal collection matrix and an external collection matrix for monitoring the gas concentration inside and outside the corridor and comprehensively analyzing the gas leakage status.

[0088] The wireless communication module transmits the monitoring data to the monitoring center for data analysis and processing.

[0089] In this embodiment, the state of the buried location of the pipeline corridor is affected by the environmental state. Different light intensity, temperature and humidity changes will affect the leakage state of the pipeline corridor gas. The dynamic environment is determined by the environmental model to predict the impact of environmental changes on gas leakage.

[0090] Among them, the physical parameters of different types of buried soil or concrete of the corridor correspond to different permeability and density parameters. Under the changes of different environmental parameters, the leakage status is further calculated. According to the leakage status, the gas leakage status under different environmental conditions can be predicted to ensure the stability of the gas leakage status analysis.

[0091] In one embodiment, the diffusion path and speed of gas leakage are obtained according to the permeability and density of the monitored location in combination with the environmental model, and a gas leakage diffusion model is established according to the gas leakage status collected by the internal collection matrix of the pipe gallery and the external collection matrix of the pipe gallery to predict the gas diffusion behavior under different leakage amounts and environmental conditions;

[0092] Through big data analysis and artificial intelligence technology, gas leakage patterns can be identified, data trends can be analyzed, and real-time reports can be generated.

[0093] In this embodiment, a gas leakage diffusion model is established, which can comprehensively analyze the gas leakage status of the gas diffusion behavior under different leakage amounts and environmental conditions, and identify the gas leakage pattern and analyze the data trend through big data analysis and artificial intelligence technology, so as to generate real-time reports and analyze the gas status.

[0094] In one embodiment, environment model building includes:

[0095] Temperature field model: The temperature data around the pipe gallery is collected through multi-point temperature sensors, and a three-dimensional temperature field model is constructed using interpolation algorithms and data fitting technology. The temperature field model reflects the temperature changes in different seasons and time periods.

[0096] Humidity field model: The humidity data around the pipe gallery is collected through humidity sensors, and a humidity field model is constructed using multiple regression analysis and data fitting technology. The humidity field model reflects the humidity changes under different environmental conditions.

[0097] Light intensity field model: The light intensity data around the tunnel is collected through light sensors, and the light intensity field model is constructed using interpolation algorithms and data fitting technology. The light intensity field model reflects the changes in light under different time periods and weather conditions.

[0098] In this embodiment, the temperature field model has an important influence on gas diffusion, the humidity field has an important influence on the gas diffusion path and speed, and the light intensity field model has an important influence on the sensitivity of the gas sensor matrix. The three-dimensional environmental model is constructed by the three models. According to the changes of the three parameters, the influence of the environment on the gas diffusion path and speed can be determined, further ensuring the stability of gas leakage status monitoring.

[0099] In one embodiment, the gas sensor matrix comprises:

[0100] The internal data collection matrix of the pipe gallery is composed of infrared sensors, electrochemical sensors and semiconductor sensors, which are set at the node positions of the pipe gallery and equipped with protective covers to ensure the stability of the sensors.

[0101] The external data collection matrix of the pipe gallery is composed of infrared sensors and laser sensors, which are installed on the vehicle used to monitor gas leaks and monitor the pipe gallery location;

[0102] Gas leakage collection methods include real-time and data storage methods:

[0103] Data collection:

[0104] Real-time monitoring: The sensor collects gas concentration data in real time and transmits it to the monitoring center through wired or wireless communication modules;

[0105] Data storage: The monitoring center is equipped with data storage equipment to record and store real-time monitoring data for subsequent analysis;

[0106] Data processing:

[0107] Data cleaning: Clean the collected data to remove noise and outliers to ensure data quality;

[0108] Data analysis: Use big data analysis and artificial intelligence technology to analyze gas concentration trends and identify leakage patterns;

[0109] Environmental model combination: Combined with environmental models (temperature field, humidity field, light intensity field), comprehensive analysis of gas leakage diffusion path and speed;

[0110] Leakage warning:

[0111] Threshold setting: Set the warning threshold according to the safe concentration of different gases. When the gas concentration exceeds the threshold, the system will automatically alarm;

[0112] Multi-level warning: Set up a multi-level warning mechanism to trigger different levels of warning signals according to gas concentration and leakage severity;

[0113] Alarm processing: After receiving the warning signal, the monitoring center will promptly notify relevant personnel to conduct on-site inspection and processing;

[0114] Data Report:

[0115] Real-time report: Generate real-time monitoring report, record gas concentration changes and early warning information;

[0116] Historical data analysis: Generate historical data analysis reports regularly to summarize gas leakage situations and treatment results, and provide decision support.

[0117] Optionally, the external acquisition matrix installation method of the tunnel has two installation positions, one is a fixed position installation, that is, installed at a fixed position outside the tunnel, and the other is a mobile monitoring method, installed on a monitoring vehicle.

[0118] In one embodiment, infrared sensors and electrochemical sensors are installed in underground pipe corridors. The sensors are arranged at key nodes and high-risk areas, and stability is ensured by fixed installation and protective measures. The sensors collect gas concentration data in real time and transmit it to the monitoring center through a wireless communication module. The monitoring center analyzes the data in combination with the environmental model. When the gas concentration exceeds the warning threshold, the system automatically alarms and generates a real-time report.

[0119] In another embodiment, a mobile monitoring method is used in the underground pipe gallery. The monitoring vehicle is equipped with infrared sensors and laser sensors and patrols along the pipe gallery. The sensor collects gas concentration data in real time and transmits it to the monitoring center through a wireless communication module. The monitoring center combines environmental models and real-time data analysis to determine the location of gas leakage and notify relevant personnel to handle it through a multi-level early warning mechanism.

[0120] In one embodiment, the gas leakage state mode determination includes the following steps:

[0121] Soil parameter determination: The physical parameters of the soil buried in the tunnel, such as permeability, density and water content, are determined experimentally, and combined with the environmental model to determine the diffusion path and speed of gas leakage;

[0122] Concrete parameter determination: Physical parameters such as permeability, density and porosity of buried concrete in the tunnel are measured experimentally, and the diffusion path and speed of gas leakage are determined in combination with environmental models;

[0123] The gas concentration changes are monitored in real time through the gas sensor matrix. The sensor layout is determined according to the environmental model and the gas leakage diffusion model, and the monitoring coverage and sensitivity are measured;

[0124] The gas leakage status is determined based on the diffusion path and speed of the gas leakage.

[0125] In this embodiment, the gas leakage state includes:

[0126] Leakage of sealing parts: gas leakage caused by sealing failure or aging of sealing parts (such as valves, flanges, joints, etc.).

[0127] Characteristics: Usually a small hole leak with a small amount of leakage but may last for a long time.

[0128] Detection method: Use a highly sensitive gas sensor (such as an electrochemical sensor) for detection.

[0129] Pipeline or tank leakage: gas leakage caused by aging, corrosion, mechanical damage, etc.

[0130] Features: The leakage volume may be large, and the leakage location is not fixed and may occur at any part of the pipeline.

[0131] Detection method: Use infrared sensors or laser sensors for long-distance detection, combined with environmental models to determine the leak location.

[0132] Discharge of pressure relief components such as safety pressure reducing valves: gas discharge of pressure relief components such as safety pressure reducing valves, pressure reducing valves and safety valves under normal working or fault conditions.

[0133] Features: The discharge volume is large, usually a high-flow discharge in a short period of time.

[0134] Detection method: Use a high-flow gas sensor for detection, combined with a pressure sensor to monitor the working status of the pressure relief element.

[0135] Pinhole Leak: Gas leakage due to a tiny hole in a pipe or equipment.

[0136] Features: The leakage volume is small, but the leaked gas may spread quickly and be difficult to detect.

[0137] Detection method: Use ultrasonic sensors to detect high-frequency sound waves, or use highly sensitive gas sensors for detection.

[0138] Large leak: A gas leak caused by a rupture or extensive damage to a pipeline or equipment.

[0139] Features: Large leakage volume, leaked gas spreads rapidly, and can easily cause safety accidents.

[0140] Detection method: Use infrared imagers or laser sensors for large-scale monitoring, combined with environmental models for leakage diffusion analysis.

[0141] Instantaneous leakage: A large amount of gas leaks in a short period of time due to equipment failure or operating error.

[0142] Features: The leakage time is short, but the leakage volume is large, which may cause instantaneous accumulation of high-concentration gas.

[0143] Detection method: Use fast-response gas sensors for real-time monitoring and combine with data analysis systems for rapid early warning.

[0144] In one embodiment, the gas diffusion path and velocity are calculated based on the gas data inside the pipe gallery and the gas data outside the pipe gallery:

[0145] Data collection includes internal data and external data of the corridor:

[0146] Data inside the tunnel: Real-time monitoring of gas concentration through the internal data collection matrix of the tunnel.

[0147] Environmental parameters: collect environmental parameters such as temperature, humidity and pressure;

[0148] Pipeline gallery external data: monitor the gas concentration in the external environment through the pipeline gallery external acquisition matrix;

[0149] Environmental parameters: collect temperature, humidity, wind speed and wind direction data of the external environment;

[0150] The gas diffusion equation is used to describe the diffusion process of gas inside and outside the tunnel. The diffusion equation takes into account factors such as gas concentration gradient, temperature, humidity and wind speed.

[0151] The diffusion equation is discretized using the finite element method or the finite difference method to solve the change of the gas concentration field;

[0152] Set reasonable boundary conditions, gas concentration, temperature and humidity at the inlet and outlet of the tunnel to ensure the accuracy of numerical simulation;

[0153] Diffusion path and velocity calculation:

[0154] Path calculation: Based on the numerical simulation results, draw a gas concentration value line graph to determine the main path of gas diffusion;

[0155] Use the streamline method to track the movement path of gas molecules and determine the specific route of gas diffusion;

[0156] Speed ​​calculation:

[0157] Through the numerical simulation results, the concentration change rate of the gas at different locations is calculated to determine the gas diffusion rate;

[0158] The particle tracking method is used to simulate the motion of gas molecules and calculate the average velocity of gas diffusion.

[0159] In one embodiment, Fick's law is used to describe the diffusion process of methane inside and outside the tunnel:

[0160]

[0161] Where J is the diffusion flux, D is the diffusion coefficient, C is the gas concentration, and x is the position;

[0162] The finite element method is used to discretize the diffusion equation and solve the change of gas concentration field;

[0163] The gas concentration, temperature, and humidity at the tunnel inlet and outlet are input into the model as boundary conditions;

[0164] Path calculation:

[0165] Based on the numerical simulation results, draw the methane concentration contour map to determine the main path of gas diffusion;

[0166] Use the streamline method to track the movement path of methane molecules and determine the specific route of gas diffusion;

[0167] Speed ​​calculation:

[0168] Through the numerical simulation results, the concentration change rate of methane at different locations is calculated to determine the gas diffusion rate;

[0169] The particle tracking method is used to simulate the motion of methane molecules and calculate the average velocity of gas diffusion.

[0170] In this embodiment, the internal data of the pipe gallery is:

[0171] Gas concentration: The infrared sensor detected a methane concentration of 500ppm.

[0172] Environmental parameters: The temperature sensor shows that the temperature is 25℃, and the humidity sensor shows that the humidity is 60%.

[0173] External data of the pipeline gallery:

[0174] Gas concentration: The infrared sensor detected a methane concentration of 50ppm.

[0175] Environmental parameters: temperature is 28℃, humidity is 55%, wind speed is 3m / s, wind direction is southeast.

[0176] Environmental model building

[0177] Temperature field model:

[0178] Through the interpolation algorithm, the temperature data inside and outside the tunnel are fitted into a three-dimensional temperature field model.

[0179] Humidity field model:

[0180] The humidity data were fitted into a three-dimensional humidity field model using multiple regression analysis.

[0181] Wind speed and direction model:

[0182] The wind field distribution is simulated using a fluid dynamics model to determine the effects of wind speed and direction on gas diffusion.

[0183] Analysis of gas diffusion path and diffusion rate:

[0184] Diffusion path:

[0185] The simulation results show that methane diffuses outward from the leakage point along the pipeline corridor, with the main path being southeast, which is consistent with the influence of wind direction.

[0186] Diffusion rate: Calculation results show that the diffusion rate of methane inside the tunnel is 0.5m / s, and the diffusion rate outside the tunnel is 1.2m / s, which is greatly affected by wind speed.

[0187] Real-time monitoring: The monitoring center receives sensor data in real time, combines environmental models and numerical simulation results, and dynamically updates the gas diffusion path and speed.

[0188] In one embodiment, soil or concrete permeability is calculated:

[0189] Soil constant head permeability calculation formula:

[0190]

[0191] Where k is the permeability coefficient, Q is the amount of water passing through the soil sample, L is the sample length, A is the sample cross-sectional area, h is the hydraulic head difference, and t is time;

[0192] Soil variable head infiltration calculation formula:

[0193]

[0194] Where a is the cross-sectional area of ​​the test tube, L is the sample length, A is the cross-sectional area of ​​the sample, t is the time, h1 and h2 are the initial and final water heads respectively;

[0195] Concrete pressure penetration calculation formula:

[0196]

[0197] Where k is the permeability coefficient, Q is the amount of water passing through the concrete sample, A is the cross-sectional area of ​​the sample, ΔP is the water pressure difference, and t is time.

[0198] In one embodiment, soil or concrete density is calculated:

[0199] Soil wet density calculation formula:

[0200] ρw=Vmw;

[0201] Among them, ρw is the wet density, mw is the wet soil mass, and V is the sample volume;

[0202] Soil dry density calculation formula:

[0203] ρd=Vmd;

[0204] Among them, ρd is the dry density, m_d is the dry soil mass, and V is the sample volume;

[0205] Concrete density calculation formula:

[0206] Density: ρ = Vm;

[0207] Where ρ is the density, m is the mass of the concrete sample, and V is the volume of the sample.

[0208] In one embodiment, data processing and analysis: monitoring data is transmitted to the monitoring center through a wireless communication module for real-time data processing and analysis. Big data analysis and artificial intelligence technology are used to identify gas leakage patterns, analyze data trends, and combine historical data and environmental models to conduct leakage risk assessment and early warning to provide decision support.

[0209] Although the present invention is disclosed in conjunction with the above embodiments, it is not intended to limit the present invention. Anyone familiar with this technology can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be based on the definition of the attached claims.

Claims

1. A vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline corridors, characterized in that: include: The environmental model consists of a temperature field model, a humidity field model, and a light intensity field model. The environmental parameters around the pipe gallery are monitored in real time through temperature sensors, humidity sensors, and light sensors. Based on the environmental data, a dynamic environmental model is established to predict the impact of environmental changes on gas leakage. The tunnel parameter monitoring module obtains the physical parameters of the soil or concrete where the tunnel is buried, including permeability and density parameters; The gas leakage model combines the buried physical parameters of the pipeline corridor with the environmental model to determine the diffusion path and speed of the gas leakage; The gas sensor matrix consists of an internal collection matrix and an external collection matrix for monitoring the gas concentration inside and outside the corridor and comprehensively analyzing the gas leakage status. The wireless communication module transmits the monitoring data to the monitoring center for data analysis and processing.

2. The vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline corridor according to claim 1 is characterized in that: According to the permeability and density of the monitored location, combined with the environmental model, the diffusion path and speed of the gas leakage are obtained, and according to the gas leakage status collected by the internal and external collection matrices of the corridor, a gas leakage diffusion model is established to predict the gas diffusion behavior under different leakage amounts and environmental conditions; Through big data analysis and artificial intelligence technology, gas leakage patterns can be identified, data trends can be analyzed, and real-time reports can be generated.

3. The vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline corridor according to claim 2 is characterized in that: Environmental model building includes: Temperature field model: The temperature data around the pipe gallery is collected through multi-point temperature sensors, and a three-dimensional temperature field model is constructed using interpolation algorithms and data fitting technology. The temperature field model reflects the temperature changes in different seasons and time periods. Humidity field model: The humidity data around the pipe gallery is collected through humidity sensors, and a humidity field model is constructed using multiple regression analysis and data fitting technology. The humidity field model reflects the humidity changes under different environmental conditions. Light intensity field model: The light intensity data around the tunnel is collected through light sensors, and the light intensity field model is constructed using interpolation algorithms and data fitting technology. The light intensity field model reflects the changes in light under different time periods and weather conditions.

4. The vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline corridor according to claim 3 is characterized in that: The gas sensor matrix includes: The internal data collection matrix of the pipe gallery is composed of infrared sensors, electrochemical sensors and semiconductor sensors, which are set at the node positions of the pipe gallery and equipped with protective covers to ensure the stability of the sensors. Pipe gallery external data collection matrix: It is composed of infrared sensors and laser sensors, installed on a vehicle used to monitor gas leaks and monitors the location of the pipe gallery.

5. The vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline corridor according to claim 4 is characterized in that: The gas leakage status determination includes the following steps: Soil parameter determination: The physical parameters of the soil permeability, density and water content of the buried soil of the pipeline corridor are determined through experiments, and the diffusion path and speed of gas leakage are determined in combination with the environmental model; Concrete parameter determination: The physical parameters of the buried concrete of the tunnel, such as permeability, density and porosity, are determined experimentally, and the diffusion path and speed of gas leakage are determined in combination with the environmental model; The gas concentration changes are monitored in real time through the gas sensor matrix. The sensor layout is determined according to the environmental model and the gas leakage diffusion model, and the monitoring coverage and sensitivity are measured; The gas leakage status is determined based on the diffusion path and speed of the gas leakage.

6. The vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline corridor according to claim 5 is characterized in that: The gas diffusion path and velocity are calculated based on the gas data inside and outside the tunnel: Data collection includes internal data and external data of the corridor: Data inside the pipe gallery: Real-time monitoring of gas concentration through the collection matrix inside the pipe gallery; Environmental parameters: collect temperature, humidity and pressure environmental parameters; Pipeline gallery external data: monitor the gas concentration in the external environment through the pipeline gallery external acquisition matrix; Environmental parameters: collect temperature, humidity, wind speed and wind direction data of the external environment; The gas diffusion equation is used to describe the diffusion process of gas inside and outside the tunnel. The diffusion equation takes into account factors such as gas concentration gradient, temperature, humidity and wind speed. The diffusion equation is discretized using the finite element method or the finite difference method to solve the change of the gas concentration field; Set reasonable boundary conditions, gas concentration, temperature and humidity at the inlet and outlet of the tunnel to ensure the accuracy of numerical simulation; Diffusion path and velocity calculation: Path calculation: Based on the numerical simulation results, draw a gas concentration value line graph to determine the main path of gas diffusion; Use the streamline method to track the movement path of gas molecules and determine the specific route of gas diffusion; Speed ​​calculation: Through the numerical simulation results, the concentration change rate of the gas at different locations is calculated to determine the gas diffusion rate; The particle tracking method is used to simulate the motion of gas molecules and calculate the average velocity of gas diffusion.

7. The vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline corridor according to claim 6 is characterized in that: Use Fick's law to describe the diffusion process of methane inside and outside the pipeline corridor: Where J is the diffusion flux, D is the diffusion coefficient, C is the gas concentration, and x is the position; The finite element method is used to discretize the diffusion equation and solve the change of gas concentration field; The gas concentration, temperature, and humidity at the tunnel inlet and outlet are input into the model as boundary conditions; Path calculation: According to the numerical simulation results, a methane concentration line graph is drawn to determine the main path of gas diffusion; Use the streamline method to track the movement path of methane molecules and determine the specific route of gas diffusion; Speed ​​calculation: Through the numerical simulation results, the concentration change rate of methane at different locations is calculated to determine the gas diffusion rate; The particle tracking method is used to simulate the motion of methane molecules and calculate the average velocity of gas diffusion.

8. The vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline corridor according to claim 7 is characterized in that: Calculate soil or concrete permeability: Soil constant head permeability calculation formula: Where k is the permeability coefficient, Q is the amount of water passing through the soil sample, L is the sample length, A is the sample cross-sectional area, h is the hydraulic head difference, and t is time; Soil variable head infiltration calculation formula: Where a is the cross-sectional area of ​​the test tube, L is the sample length, A is the cross-sectional area of ​​the sample, t is the time, h1 and h2 are the initial and final water heads respectively; Concrete pressure penetration calculation formula: Where k is the permeability coefficient, Q is the amount of water passing through the concrete sample, A is the cross-sectional area of ​​the sample, ΔP is the water pressure difference, and t is time.

9. The vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline gallery according to claim 8 is characterized in that: Calculate soil or concrete density: Soil wet density calculation formula: ρw=Vmw; Among them, ρw is the wet density, mw is the wet soil mass, and V is the sample volume; Soil dry density calculation formula: ρd=Vmd; Among them, ρd is the dry density, m_d is the dry soil mass, and V is the sample volume; Concrete density calculation formula: Density: ρ = Vm; Where ρ is the density, m is the mass of the concrete sample, and V is the volume of the sample.

10. The vehicle-mounted gas leakage monitoring system for petroleum and petrochemical pipeline gallery according to claim 9, characterized in that: Data processing and analysis: The monitoring data is transmitted to the monitoring center through the wireless communication module for real-time data processing and analysis. Big data analysis and artificial intelligence technology are used to identify gas leakage patterns, analyze data trends, and combine historical data and environmental models to conduct leakage risk assessment and early warning to provide decision support.

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