Three-dimensional monitoring method, equipment and system for gas leakage

Abstract

The embodiment of the invention provides a three-dimensional monitoring method, equipment and system for gas leakage, and belongs to the technical field of gas leakage monitoring. The method comprises the steps of collecting working condition information corresponding to each monitoring dimension in a target monitoring scene, and performing monitoring network optimization layout of each monitoring dimension based on the working condition information; performing monitoring network configuration corresponding to each monitoring dimension based on the monitoring network optimization layout result, and acquiring real-time monitoring data based on the configured monitoring network communication transmission; based on the real-time monitoring data, performing leakage event identification and influence evaluation under each monitoring dimension to obtain an evaluation result; and carrying out preset coping scheme matching based on the obtained evaluation result, and executing the matched coping scheme. According to the scheme, the problems that monitoring network construction is limited to a safety monitoring level, related requirements of environmental pollution monitoring are not fully considered and a specific executable monitoring point position optimization layout scheme is lacked when gas leakage monitoring is carried out by an existing petrochemical enterprise are solved.

Description

Technical Field

[0001] This invention relates to the field of leakage monitoring technology, specifically to a three-dimensional gas leakage monitoring method, a three-dimensional gas leakage monitoring device, and a three-dimensional gas leakage monitoring system. Background Technology

[0002] Gas leaks are a major cause of serious accidents such as fires, explosions, and poisonings in petrochemical plants. To promptly detect and respond to potential leak risks, petrochemical companies have widely installed gas detectors within their production facilities. These devices can monitor changes in the concentration of flammable and toxic gases in real time. However, companies face a series of challenges in constructing a plant-level gas leak monitoring network.

[0003] To improve safety monitoring, petrochemical enterprises currently rely primarily on the "Design Standard for Combustible and Toxic Gas Detection Alarms in Petrochemical Industry" (GB50493-2019) to guide the installation of gas alarms. However, several problems exist, one of which is the lack of evaluation indicators for assessing the effectiveness of monitoring network construction. Furthermore, enterprises need to further optimize and improve the methods for deploying monitoring points to ensure the comprehensiveness and accuracy of the monitoring network.

[0004] Meanwhile, the environmental pollution monitoring needs have not been fully considered in the construction of plant-level gas leak monitoring networks. Current site deployment is limited to safety monitoring, neglecting the importance of environmental protection and pollution control. Therefore, petrochemical enterprises need to comprehensively consider environmental factors and incorporate environmental monitoring into the design and planning of monitoring networks to achieve timely monitoring and response to environmental pollution. Addressing the problems of existing gas leak monitoring networks in petrochemical enterprises being limited to safety monitoring and failing to fully consider environmental pollution monitoring needs, while also lacking specific and feasible optimized deployment schemes for monitoring points, a new gas leak monitoring solution needs to be proposed. Summary of the Invention

[0005] The purpose of this invention is to provide a three-dimensional gas leak monitoring method, equipment, and system to at least address the problems of existing petrochemical enterprises where gas leak monitoring network construction is limited to safety monitoring, fails to fully consider the relevant needs of environmental pollution monitoring, and lacks specific and feasible optimization plans for monitoring point deployment.

[0006] To achieve the above objectives, the first aspect of the present invention provides a three-dimensional gas leakage monitoring method applied to gas leakage monitoring in petrochemical sites. The method includes: collecting operating condition information corresponding to each monitoring dimension of the target monitoring area, and optimizing the deployment of the monitoring network for each monitoring dimension based on the operating condition information; configuring the monitoring network based on the optimized deployment result, and acquiring real-time monitoring data through communication transmission based on the configured monitoring network; identifying and assessing the impact of leakage events in each monitoring dimension based on the real-time monitoring data; matching preset response plans based on the impact assessment result, and executing the matched response plan.

[0007] Optionally, the monitoring dimensions include: a leak source monitoring dimension, used to monitor leak events occurring at the leak source location; a diffusion path monitoring dimension, used to monitor the degree of pollution of the target monitoring area by the leak event and the leaked material; and a boundary monitoring dimension, used to monitor the degree of pollution impact of the leak event and the leaked material on the external environment of the target monitoring area.

[0008] Optionally, the operating condition information corresponding to the leakage source monitoring dimension includes: the type of equipment with leakage risk within the target monitoring area, the location of the equipment with leakage risk, the type of leaked material with leakage risk, historical leakage data of the equipment with leakage risk, and the temperature and pressure parameters of the equipment with leakage risk; the operating condition information corresponding to the diffusion path monitoring dimension includes: the near-ground location or concentration accumulation location of the target monitoring area to which the leaked gas with explosion, combustion, or poisoning risk can diffuse, as well as the distribution concentration of the leaked material and historical airflow data at each location; the operating condition information corresponding to the boundary monitoring dimension includes: historical airflow data of the target monitoring area where the equipment with leakage risk is located, the boundary contour information of the target monitoring area, and the layout information of the accumulation area within a preset distance around the corresponding location.

[0009] Optionally, the optimization of the monitoring network deployment for each monitoring dimension based on the operating condition information includes: optimizing the monitoring network deployment for the leakage source monitoring dimension, including: determining the leakage risk level of each device with leakage risk based on the type of equipment with leakage risk in the target monitoring area, the type of leaked material with leakage risk, historical leakage data of the equipment with leakage risk, and temperature and pressure parameters of the equipment with leakage risk; determining monitoring factors based on the type of leaked material corresponding to each device with leakage risk, and determining the type of leakage source monitoring equipment based on the monitoring factors; determining the required detection coverage index based on the leakage risk level of each device with leakage risk; and optimizing the monitoring network deployment for the leakage source monitoring dimension based on the type of leakage source monitoring equipment, the location of the equipment with leakage risk, and the required detection coverage index, using a detection coverage evaluation method and following the principle of achieving the detection coverage index while minimizing the number of leakage source monitoring devices.

[0010] Optionally, the optimization of the monitoring network layout for each monitoring dimension based on the operating condition information includes: optimizing the monitoring network layout for the diffusion path monitoring dimension, including: taking leaked gases with explosion, combustion, or poisoning risks as monitoring factors; calculating the spatial concentration distribution data of each monitoring factor in the target monitoring area based on the near-ground location or concentration accumulation location of each monitoring factor that can diffuse to, as well as the corresponding leakage material distribution concentration and historical airflow data at each location; determining the key pollution areas of each monitoring factor based on the leakage material distribution concentration of each monitoring factor in the target monitoring area under different wind directions, using one or more enclosed areas where the leakage material distribution concentration exceeds the limit; determining the installation range of each diffusion monitoring device based on the key pollution areas of each monitoring factor; determining the type of diffusion monitoring device based on each monitoring factor; and optimizing the monitoring network layout for the diffusion path monitoring dimension based on the type of diffusion monitoring device and the installation range of each diffusion monitoring device, with the principle of having at least one diffusion monitoring device in each key pollution area under different wind directions, minimizing the total number of diffusion monitoring devices, and maximizing the spatial concentration distribution data at the location of the diffusion monitoring device.

[0011] Optionally, the step of calculating the spatial concentration distribution data of each monitoring factor in the target monitoring area based on the near-ground location or concentration accumulation location of each monitoring factor that can diffuse to the target monitoring area, and the corresponding leakage concentration and historical airflow data at each location, includes:

[0012] Based on the historical airflow data, the wind frequency coefficient and number of wind directions in the target monitoring area are determined; based on the wind frequency coefficient, the number of wind directions, and the concentration of leaked substances at each location, the spatial concentration distribution data of each monitoring factor in the target monitoring area are calculated, and the calculation rules are as follows:

[0013]

[0014] Where, r j Here are the concentration distribution data of the leaked material at each location for the j-th monitoring factor; a ij f represents the concentration of the leaked substance at the location of the pollution point corresponding to the j-th monitoring factor under the i-th wind direction; i Let N be the wind frequency coefficient for the i-th wind direction; N is the number of wind directions.

[0015] Optionally, for situations where diffusion monitoring equipment monitors multiple factors and needs to be deployed in overlapping areas of key pollution zones for multiple factors, to achieve the effect of simultaneously monitoring multiple leaked gases in multiple heavily polluted areas with a single diffusion monitoring device, it is necessary to calculate the weighted spatial concentration distribution data of multiple monitoring factors. The calculation rules are as follows:

[0016]

[0017] Where r represents the weighted spatial concentration distribution data of multiple monitoring factors; i∈[1,N], and N is the total number of different wind directions; f i Let a be the wind frequency coefficient for the i-th wind direction; j∈[1,M], where M is the total number of different monitoring factors; a ij This refers to the concentration data of leaked material at various locations under the i-th wind direction and for the j-th monitoring factor; j Let be the emission limit for the concentration at the plant boundary of the j-th monitoring factor.

[0018] Optionally, the step of optimizing the monitoring network deployment for each monitoring dimension based on the operating condition information includes: optimizing the monitoring network deployment for the boundary monitoring dimension, including: determining the upwind and downwind boundary points of the target monitoring area based on historical airflow data of the target monitoring area where the equipment with leakage risk is located and the boundary contour information of the target monitoring area; determining the sensitive boundary points of the target monitoring area based on the layout information of the clustering area within a preset distance around the corresponding location; determining each controlled boundary point of the target monitoring area based on the sensitive boundary points, the upwind boundary points, and the downwind boundary points; and performing the optimized deployment of the monitoring network for each controlled boundary point based on the principle that at least one set of boundary monitoring equipment is set up for each controlled boundary point.

[0019] Optionally, based on historical airflow data of the target monitoring area where the equipment with leakage risk is located and the boundary contour information of the target monitoring area, the upwind and downwind boundary points of the target monitoring area are determined, including: determining the prevailing wind direction based on historical airflow data of the target monitoring area where the equipment with leakage risk is located; taking the foremost point of the upwind boundary in the prevailing wind direction as the upwind boundary point; obtaining the vertical projection of the boundary contour information of the target monitoring area onto the device area on the ground, taking the line segment where the prevailing wind direction line overlaps with the vertical projection of the device area as the target line segment, calculating the location of the target line segment with the longest length, and taking the downwind endpoint of the line segment as the downwind boundary point; if the pollutant concentration distribution data in the three-dimensional space of the target monitoring area is known, defining the area where the vertical section of the prevailing wind direction overlaps with the three-dimensional space of the target monitoring area as the target area, calculating the location of the target area with the largest pollutant area integral concentration value, and taking the downwind endpoint of the vertical projection of the target area as the downwind boundary point.

[0020] Optionally, the step of configuring the monitoring network based on the optimized deployment results and acquiring real-time monitoring data based on the configured monitoring network communication transmission includes: determining the deployment type, quantity, and location of all monitoring devices within the target monitoring area provided by the optimized deployment results, and executing the on-site deployment of each monitoring device; responding to the start signal, executing the communication initialization of each monitoring device, verifying whether each monitoring device is communicating normally, and starting to acquire real-time monitoring data after the verification is passed.

[0021] Optionally, the step of identifying and assessing the impact of leak events based on the real-time monitoring data across various monitoring dimensions to obtain assessment results includes: determining and identifying a leak event based on monitoring data from the leak source monitoring dimension and the leak thresholds of each preset monitoring factor; determining the spatial impact range of the leak event by drawing a preset concentration threshold contour line centered on the location of the leak event using a spatial concentration interpolation algorithm after determining that a leak event has occurred, based on monitoring data from the diffusion path monitoring dimension and the spatial location of each diffusion monitoring device; and determining whether the leak event has a pollution impact on the external environment of the target monitoring area based on monitoring data from the boundary monitoring dimension and the preset pollution emission thresholds of each monitoring factor; wherein, the location of the leak event is the spatial location of the leak source monitoring device identified as a leak event.

[0022] Optionally, before identifying and assessing the impact of leakage events based on the real-time monitoring data under each monitoring dimension and obtaining the assessment results, the method further includes: identifying the monitoring device corresponding to each monitoring data and determining whether the corresponding monitoring device belongs to a monitoring network of a single monitoring dimension; if so, classifying the corresponding monitoring data into the monitoring network dataset of the corresponding monitoring dimension; if not, determining the number of monitoring networks in the monitoring dimension to which the corresponding monitoring device belongs, and performing a corresponding number of monitoring data copies based on the number of monitoring networks in the monitoring dimension to which the device belongs; classifying the copied monitoring data into the monitoring network datasets of each monitoring dimension to which the device belongs, with each monitoring network dataset of the monitoring dimension corresponding to one copied monitoring data.

[0023] Optionally, the step of matching a preset response plan based on the impact assessment results and executing the matched response plan includes: determining the location, type, and / or risk level of a leak based on the impact assessment results; matching a corresponding preset response plan based on the location, type, and / or risk level of the leak; wherein the preset response plan includes any one or more of the following: a graded early warning plan, a leak source cutoff plan, a leak material suppression plan, and an environmental remediation plan.

[0024] A second aspect of the present invention provides a three-dimensional gas leak monitoring device for use in gas leak monitoring at petrochemical sites. The device includes: a data acquisition unit for acquiring operating condition information corresponding to each monitoring dimension under a target monitoring scenario, and optimizing the deployment of the monitoring network for each monitoring dimension based on the operating condition information; a monitoring unit for configuring the monitoring network for each monitoring dimension based on the optimized deployment result, and acquiring real-time monitoring data through communication transmission based on the configured monitoring network; an evaluation unit for identifying and evaluating leak events and their impacts in each monitoring dimension based on the real-time monitoring data, and obtaining evaluation results; and an execution unit for matching a preset response plan based on the obtained evaluation results, and executing the matched response plan.

[0025] A third aspect of the present invention provides a three-dimensional gas leakage monitoring system for use in gas leakage monitoring at petrochemical sites, the system comprising the aforementioned three-dimensional gas leakage monitoring equipment.

[0026] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to perform the above-described three-dimensional gas leak monitoring method.

[0027] A fifth aspect of the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described three-dimensional gas leak monitoring method.

[0028] The sixth aspect of the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the above-described three-dimensional gas leakage monitoring method.

[0029] Through the above technical solution, the present invention includes a leak source monitoring network covering equipment at risk of leakage, a diffusion path monitoring network covering heavily polluted areas, and a boundary monitoring network covering the boundaries of the equipment. It also provides an optimized construction method for the monitoring network. This monitoring network takes into account both leak risk safety monitoring and leak pollution environmental monitoring. Internally, it achieves the monitoring and identification of target leak events and routine pollution; externally, it enables effective assessment of environmental pollution. The present invention achieves multi-dimensional gas leak monitoring, designing and constructing the monitoring network based on the actual conditions of the monitoring area, ensuring the adaptability of the monitoring network to the target monitoring area. It solves the problems of existing petrochemical enterprises where gas leak monitoring network construction is limited to safety monitoring, fails to fully consider the relevant needs of environmental pollution monitoring, and lacks specific and executable optimized deployment schemes for monitoring points.

[0030] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0031] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0032] Figure 1 This is a flowchart of the steps of a three-dimensional gas leakage monitoring method provided in one embodiment of the present invention;

[0033] Figure 2 This is a schematic diagram of a target line segment provided in one embodiment of the present invention;

[0034] Figure 3 This is a schematic diagram of a target surface region provided in one embodiment of the present invention;

[0035] Figure 4 This is a structural diagram of a gas leak three-dimensional monitoring device provided in one embodiment of the present invention. Detailed Implementation

[0036] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0037] Figure 1 This is a flowchart of a three-dimensional gas leak monitoring method provided in one embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides a three-dimensional gas leak monitoring method, the method comprising:

[0038] Step S10: Collect the operating condition information corresponding to each monitoring dimension of the target monitoring area, and optimize the deployment of the monitoring network for each monitoring dimension based on the operating condition information.

[0039] Specifically, the monitoring dimensions include: leak source monitoring dimension, used to monitor the leakage risk at the leak source location; diffusion path monitoring dimension, used to monitor the degree of pollution of the leaked material to the target monitoring area; and boundary monitoring dimension, used to monitor the degree of pollution impact of the leak on the external environment of the target monitoring area.

[0040] Furthermore, the operating condition information corresponding to the leakage source monitoring dimension includes: the type of equipment with leakage risk within the target monitoring area, the location of the equipment with leakage risk, and the type of leaked material with leakage risk; the operating condition information corresponding to the diffusion path monitoring dimension includes: the near-ground location or concentration accumulation location of the target monitoring area to which the leaked gas with explosion, combustion, or poisoning risk can diffuse, as well as the distribution concentration of the leaked material and historical airflow data at each location; the operating condition information corresponding to the boundary monitoring dimension includes: historical airflow data of the target monitoring area where the leaking equipment corresponding to the leaked gas with ambient air pollution risk is located, the boundary contour information of the target monitoring area, and the layout information of the accumulation area within a preset distance around the corresponding location.

[0041] Example 1:

[0042] The optimization of the monitoring network for leak source monitoring includes: determining the leakage risk level of each device based on the types of equipment at risk of leakage, the types of leaked materials at risk, historical leakage data of the devices at risk, and temperature and pressure parameters of the devices at risk; determining monitoring factors based on the types of leaked materials corresponding to each device at risk, and determining the types of leak source monitoring equipment based on the monitoring factors; determining the required detection coverage index based on the leakage risk level of each device at risk; and optimizing the monitoring network for leak source monitoring based on the types of leak source monitoring equipment, the locations of devices at risk, and the required detection coverage index, using detection coverage evaluation methods and adhering to the principle of achieving the detection coverage index while minimizing the number of leak source monitoring devices.

[0043] In one possible implementation, leaked gases posing risks such as combustion, explosion, or poisoning are used as leak monitoring factors. Based on the type of monitoring factor, leak-risk equipment involving that factor is selected as the coverage object. Gas detectors suitable for that factor are chosen as leak source monitoring equipment. The principle is to optimize the construction of a leak source monitoring network by minimizing the number of leak source monitoring equipment and achieving the detection coverage target for leak-risk equipment. The leak-risk equipment refers to in-use processing / storage / transportation production equipment within the facility that poses a leak risk. Based on different leak monitoring factors, the leakage hazard level and probability of leakage for each leak-risk equipment are assessed, and it is classified into high, medium, and low leak risk levels; that is, the same leak-risk equipment has different leak risk levels for different leak monitoring factors. The gas detectors suitable for that factor are used as leak source monitoring equipment; for example, a hydrogen sulfide gas detector is used as a leak source monitoring equipment because a combustible gas detector cannot detect hydrogen sulfide and is therefore not a leak source monitoring equipment for hydrogen sulfide. The detection coverage indicators for the leakage risk equipment are formulated according to different leakage risk levels, with specific coverage indicators for high, medium and low leakage risk equipment. When deploying leakage source monitoring equipment, priority should be given to covering high-level leakage risk equipment. It is recommended that the coverage indicator for high leakage risk equipment reach 95% and the coverage indicator for medium leakage risk equipment reach 80%.

[0044] Preferably, the coverage assessment method includes spatial analysis and scenario analysis, and the magnitude of the leakage source strength to be measured is determined according to the spatial analysis and scenario analysis. That is, the leakage source monitoring network takes leakage with the source strength of the above as the target leakage event, so as to achieve full coverage of the target leakage events of the leakage risk equipment.

[0045] In this embodiment of the invention, spatial analysis is a commonly used method for evaluating the coverage of a monitoring network. Spatial analysis allows for a comprehensive assessment of the distribution of monitoring points, determining the coverage area and overlap between them. When evaluating the coverage of a monitoring network, spatial analysis helps determine the density and location of monitoring points to ensure the network effectively covers the entire monitoring area and promptly detects potential leaks. Another method for evaluating monitoring network coverage is scenario analysis. Scenario analysis simulates leaks in different scenarios, including the size and location of the leak source and environmental conditions, to assess the monitoring network's ability to respond to different leak situations. Scenario analysis clarifies the strength of the leak source to be tested and identifies leaks with a strength of this level or higher as target leaks for the monitoring network, ensuring comprehensive coverage and improving its effectiveness and responsiveness. Combining spatial and scenario analysis allows for a more comprehensive evaluation of the monitoring network's coverage and the development of appropriate monitoring strategies and response measures for different leak situations. This comprehensive assessment method can effectively guide petrochemical enterprises in optimizing the selection and layout of monitoring points during the design and deployment of monitoring networks, improving the comprehensiveness and accuracy of the monitoring network, thereby effectively addressing potential leakage risks and ensuring the safety and stability of the production process.

[0046] Based on this technical solution, by clearly defining the magnitude of the leak source strength to be measured and using leak events exceeding that magnitude as target leak events, it is possible to ensure that the monitoring network can comprehensively cover the target leak events, thereby improving the effectiveness of the monitoring network. Simulating different leak scenarios through scenario analysis allows for the evaluation of the monitoring network's ability to respond to leak events under different conditions. This helps enterprises develop targeted monitoring strategies and countermeasures, improving the network's responsiveness. Spatial analysis helps determine the density and location of monitoring points, thereby optimizing the layout of these points and ensuring a broad and reasonable monitoring network coverage, improving its accuracy and comprehensiveness. In conclusion, using spatial analysis and scenario analysis methods to evaluate monitoring network coverage can effectively improve the design level and monitoring effect of gas leak monitoring networks in petrochemical enterprises, thus ensuring the safety, stability, and environmental friendliness of the production process.

[0047] Example 2:

[0048] The optimization of the monitoring network for diffusion pathway monitoring includes: using leaked gases with explosion, combustion, or poisoning risks as monitoring factors; calculating the spatial concentration distribution data of each monitoring factor in the target monitoring area based on the near-surface location or concentration accumulation location of each monitoring factor that it can diffuse to, as well as the corresponding leakage concentration and historical airflow data at each location; determining the key pollution areas for each monitoring factor based on the leakage concentration of each monitoring factor in the target monitoring area under different wind directions, using one or more enclosed areas where the leakage concentration exceeds the limit; determining the installation range of each diffusion monitoring device based on the key pollution areas of each monitoring factor; determining the type of diffusion monitoring device based on each monitoring factor; and optimizing the monitoring network for diffusion pathway monitoring based on the type of diffusion monitoring device and the installation range of each diffusion monitoring device, with the principle of having at least one diffusion monitoring device in each key pollution area under different wind directions, minimizing the total number of diffusion monitoring devices, and maximizing the spatial concentration distribution data at the location of the diffusion monitoring device.

[0049] In one possible implementation, leaked gases posing risks of combustion, explosion, or poisoning are used as leak monitoring factors. High-pollution points in heavily polluted areas of each leak monitoring factor are designated as diffusion pathway points, and monitoring stations are deployed to form a diffusion pathway monitoring network. For scenarios where a separate diffusion pathway monitoring network is deployed for each leak monitoring factor, firstly, the spatial concentration distribution data 'a' of each leak monitoring factor within the plant area under different wind directions is determined. Based on the fugitive emission boundary concentration limit 'l' and the wind frequency coefficient 'f' for each leak monitoring factor, the weighted spatial concentration distribution data 'r' is calculated. One or more enclosed areas where 'r' exceeds the limit 'g×1 / 5' are designated as one or more heavily polluted areas for that factor. The diffusion pathway points for that leak monitoring factor are then deployed at the locations with the highest 'r' values ​​within each heavily polluted area.

[0050] The step of calculating the spatial concentration distribution data of each monitoring factor in the target monitoring area based on the near-surface location or concentration accumulation location of each monitoring factor that can diffuse to the target monitoring area, and the corresponding leakage concentration and historical airflow data at each location, includes: determining the wind frequency coefficient and number of wind directions in the target monitoring area based on the historical airflow data; and calculating the spatial concentration distribution data of each monitoring factor in the target monitoring area based on the leakage concentration at each location using the wind frequency coefficient, the number of wind directions, and the leakage concentration at each location, with the calculation rules being:

[0051]

[0052] Where, r j Here is the spatial concentration distribution data for the j-th monitoring factor; a ij f represents the concentration of the leaked substance at the location of the pollution point corresponding to the j-th monitoring factor under the i-th wind direction; iLet N be the wind frequency coefficient for the i-th wind direction; N is the number of wind directions.

[0053] In one possible implementation, for scenarios where a diffusion path monitoring network is deployed to comprehensively monitor multiple leakage monitoring factors, i.e., a diffusion path point can simultaneously monitor multiple leakage monitoring factors, the spatial concentration distribution data of each leakage monitoring factor under different wind directions within the plant area are first determined. Based on the fugitive emission boundary concentration limit g and wind frequency coefficient f of each leakage monitoring factor, the weighted spatial concentration distribution data r of that leakage monitoring factor is calculated, as shown in the formula below. One or more enclosed areas where r exceeds 1 / 5 are designated as one or more heavily polluted areas. The diffusion path point of that leakage monitoring factor is deployed at the location with the largest r value within each heavily polluted area. For multiple leakage monitoring factors, the spatial concentration distribution data of the j-th leakage monitoring factor under the i-th wind direction at a certain location within the plant area is defined as a. ij And the wind frequency in that direction is f. i The concentration limit for this leakage monitoring factor is l. j The weighted spatial concentration distribution data r of multiple leakage monitoring factors at this location is calculated using the following formula:

[0054]

[0055] Where r represents the weighted spatial concentration distribution data of multiple monitoring factors; i∈[1,N], and N is the total number of different wind directions; f i Let a be the wind frequency coefficient for the i-th wind direction; j∈[1,M], where M is the total number of different monitoring factors; a ij This refers to the concentration data of leaked material at various locations under the i-th wind direction and for the j-th monitoring factor; j Let be the emission limit for the concentration at the plant boundary of the j-th monitoring factor.

[0056] Example 3:

[0057] The optimization of the monitoring network deployment at the boundary monitoring dimension includes: determining the upwind and downwind boundary points of the target monitoring area based on historical airflow data and boundary contour information of the target monitoring area where equipment with leakage risk is located; determining sensitive boundary points of the target monitoring area based on the layout information of the clustering area within a preset distance around the corresponding location; determining each controlled boundary point of the target monitoring area based on the sensitive boundary points, the upwind boundary points, and the downwind boundary points; and optimizing the monitoring network deployment for each controlled boundary point based on the principle of setting at least one set of boundary monitoring equipment for each controlled boundary point.

[0058] In one possible implementation, leaked gases posing a risk of ambient air pollution are used as pollution monitoring factors. Controlled boundary points are the prevailing upwind and downwind boundary points of the installation, and the boundary points of sensitive installations near office / residential areas. Appropriate environmental-grade low-concentration monitoring instruments are selected based on the pollution monitoring factors. Multiple monitoring instruments are used to form a pollution monitoring station, equipped with a meteorological five-parameter monitoring module. The principle is to install at least one boundary monitoring device at each controlled boundary point, thus optimizing the boundary monitoring network. Common pollution monitoring factors include non-methane hydrocarbons, VOCs, hydrogen sulfide, ammonia, nitrogen oxides, sulfur dioxide, ozone, odor concentration, and particulate matter.

[0059] Preferred, such as Figure 2 Based on historical airflow data and boundary contour information of the target monitoring area where the equipment with leakage risk is located, the upwind and downwind boundary points of the target monitoring area are determined. This includes: determining the prevailing wind direction based on historical airflow data of the target monitoring area where the equipment with leakage risk is located; taking the foremost point of the upwind boundary in the prevailing wind direction as the upwind boundary point; obtaining the vertical projection of the boundary contour information of the target monitoring area onto the device area on the ground; taking the line segment where the line of the prevailing wind direction overlaps with the vertical projection of the device area as the target line segment; calculating the location of the target line segment with the longest length; and taking the downwind endpoint of the line segment as the downwind boundary point.

[0060] Furthermore, such as Figure 3 For scenarios where the pollutant concentration distribution data within the three-dimensional space of the target monitoring area is clear, the area where the vertical section of the prevailing wind direction overlaps with the three-dimensional space of the target monitoring area is defined as the target area. The location of the target area with the largest pollutant area integral concentration value is calculated, and the downwind endpoint of the vertical projection of the target area is taken as the downwind boundary point.

[0061] Preferably, if the boundary points of the target monitoring area in the prevailing upwind and downwind directions overlap with the boundary points of the sensitive device or the straight-line distance between them is less than N meters, they can be merged into one controlled boundary point; it is recommended that N < 50.

[0062] In this embodiment of the invention, when the straight-line distance between the prevailing upwind and downwind boundary points and the sensitive device boundary points is less than N meters, they can be merged into a single controlled boundary point. This merging simplifies the monitoring network structure, reduces redundant monitoring point placement, and improves monitoring efficiency and data consistency. By merging controlled boundary points, excessive monitoring points in adjacent areas can be avoided, thereby optimizing the monitoring network layout. The merged controlled boundary points can better cover the monitoring area, reduce blind spots, and improve the comprehensiveness of the monitoring network. Merging controlled boundary points can reduce the investment in monitoring equipment and human resources, lowering monitoring costs. By rationally designing the monitoring network structure, the monitoring effect can be maximized while reducing monitoring operation and maintenance costs. Merging controlled boundary points simplifies the management and maintenance of the monitoring network and improves its response speed. Merging monitoring points reduces redundant data collection and processing, making the monitoring network more efficient and flexible. By merging controlled boundary points, interference and overlap between monitoring points can be reduced, improving the stability and accuracy of monitoring data. The stability of the monitoring network is crucial for the timely detection and response to potential leakage events.

[0063] Based on the technical solution of this invention, identifying the boundary points of the prevailing upwind and downwind directions and the boundary points of sensitive devices can effectively optimize the design and layout of gas leak monitoring networks in petrochemical enterprises, improving the comprehensiveness, accuracy, and efficiency of the monitoring network, thereby better ensuring the safety of the production process and environmental protection. In practical applications, petrochemical enterprises can combine spatial analysis and scenario analysis methods, comprehensively considering the layout and merging strategies of monitoring points to ensure that the monitoring network has a wide and reasonable coverage. By rationally setting controlled boundary points, enterprises can better address potential leak risks, improve the effectiveness and reliability of the monitoring network, and provide strong support for the safe operation of the production process.

[0064] Step S20: Configure the monitoring network based on the optimized deployment results, and obtain real-time monitoring data based on the configured monitoring network communication transmission.

[0065] Specifically, based on the results of the optimized deployment of the monitoring network, the deployment type, quantity, and location of all monitoring devices within the target monitoring area are determined, and the on-site deployment of each monitoring device is executed; in response to the start signal, the communication initialization of each monitoring device is executed, the normal communication of each monitoring device is checked, and real-time monitoring data is acquired after the check is passed.

[0066] In this embodiment of the invention, by optimizing the deployment results of the monitoring network, the deployment type and location of all monitoring devices within the target monitoring area can be determined. Based on the types of leakage monitoring factors, the deployment locations of the monitoring devices, and the monitoring dimensions they belong to, the optimal monitoring device types (such as combustible gas detectors, toxic gas detectors, TVOCs monitors, non-methane total hydrocarbon monitors, air quality monitoring stations, etc.) and locations (such as high-leakage risk areas, heavily polluted areas, upwind boundary points, etc.) are determined to achieve comprehensive monitoring coverage and efficient monitoring response. Based on the determined monitoring device deployment type and location plan, the deployment of each monitoring device is executed. Monitoring devices are set up within the target monitoring area according to the predetermined plan to ensure the integrity and effectiveness of the monitoring network. A reasonable deployment of monitoring devices can improve the sensitivity and accuracy of the monitoring system. Once the monitoring devices are deployed, a response start signal initiates communication initialization. Stable communication connections need to be established between monitoring devices to ensure real-time transmission of monitoring data and normal operation of the monitoring system. The communication initialization phase includes the establishment and testing of communication protocols between devices to ensure effective information exchange between monitoring devices. During the communication initialization phase, each monitoring device is reviewed to ensure its communication functionality. Through communication tests and data transmission verification between monitoring devices, it is confirmed that the monitoring devices can function normally and maintain connection with the monitoring system. Monitoring devices that pass the review will be included in the normal operation range of the monitoring system. Once all monitoring devices communicate normally and pass the review, the monitoring system begins acquiring real-time monitoring data. Real-time acquisition and analysis of monitoring data are the core functions of the monitoring system. Through timely processing and analysis of monitoring data, rapid identification and response to potential leakage events can be achieved, ensuring the safety of the production process.

[0067] Based on the technical solution of this invention, the gas leak monitoring system for petrochemical enterprises can achieve scientific planning and effective execution of monitoring equipment deployment, ensuring the comprehensiveness and accuracy of the monitoring network. Simultaneously, the communication initialization and real-time data acquisition of the monitoring equipment will improve the response speed and monitoring efficiency of the system, providing strong support for the safety management of the enterprise's production processes. The application of these technical details will effectively enhance the performance and reliability of the monitoring system, providing crucial guarantees for the safe production and environmental protection work of petrochemical enterprises.

[0068] Step S30: Based on the real-time monitoring data, identify and assess the impact of leakage events under each monitoring dimension to obtain assessment results.

[0069] Specifically, based on the real-time monitoring data, leakage events are identified and their impacts are assessed across various monitoring dimensions to obtain assessment results. This includes: identifying leakage events based on monitoring data from the leakage source monitoring dimension and the leakage thresholds of each preset monitoring factor; determining the spatial impact range of the leakage event based on monitoring data from the diffusion path monitoring dimension and the spatial location of each diffusion monitoring device, using a spatial concentration interpolation algorithm to draw a preset concentration threshold contour line centered on the location of the leakage event; and determining whether the leakage event has a pollution impact on the external environment of the target monitoring area based on monitoring data from the boundary monitoring dimension and the preset pollution emission thresholds of each monitoring factor. The location of the leakage event is the spatial location of the leakage source monitoring device identified as the leakage event.

[0070] In this embodiment of the invention, at the source of leakage monitoring, the system can accurately determine and identify the occurrence of leakage events by collecting and analyzing data from monitoring devices and combining it with the leakage thresholds of various preset monitoring factors. This process relies on high-precision sensors and intelligent algorithms to ensure timely detection of anomalies and reduce the rate of missed detections and false alarms. Secondly, once a leakage event is confirmed, the system generates a contour map of preset concentration thresholds centered on the location of the leakage event, based on data from the diffusion path monitoring dimension and the spatial location of each diffusion monitoring device, using a spatial concentration interpolation algorithm. This graphical method can intuitively show the diffusion range of the leaked substance in space, providing an important basis for rapid decision-making. Through accurate spatial impact range assessment, targeted emergency measures can be taken to control and reduce the impact of the leakage on the surrounding environment. In addition, the system also uses data from the boundary monitoring dimension and the preset pollution emission thresholds of various monitoring factors to determine whether the leakage event has caused pollution impact on the external environment of the device. This assessment step can help enterprises and management departments understand the environmental impact of leakage events in a timely manner, take necessary control measures, and ensure the protection of the external environment.

[0071] Specifically, the monitoring equipment corresponding to each monitoring data is identified, and it is determined whether the corresponding monitoring equipment belongs to a monitoring network of a single monitoring dimension. If so, the corresponding monitoring data is classified into the monitoring network dataset of the corresponding monitoring dimension. If not, the number of monitoring networks in the monitoring dimension to which the corresponding monitoring equipment belongs is determined, and the corresponding number of monitoring data copies are executed based on the number of monitoring networks in the monitoring dimension. The copied monitoring data is then classified into the monitoring network datasets of each monitoring dimension, and one copied monitoring data is obtained for each monitoring network dataset of each monitoring dimension.

[0072] In this embodiment of the invention, the monitoring system needs to identify the monitoring device corresponding to each piece of monitoring data. Through the unique identifier or data tag of the monitoring device, the system can accurately associate the monitoring data with the corresponding monitoring device. This step ensures the traceability and accuracy of the monitoring data. Some gases may require monitoring in multiple dimensions; for example, a gas may pose both an explosion risk and a pollution risk. If a separate monitoring device is set up for each monitoring network, the problem of simultaneous setup of monitoring devices will inevitably arise. Therefore, if monitoring of the same target in different dimensions is required at a certain location, it can be completed by a single monitoring device, and subsequent data processing only requires data copying.

[0073] Step S40: Based on the obtained assessment results, match the preset response plan and execute the matched response plan.

[0074] Specifically, the leak source monitoring network targets specific leak events in equipment at risk of leakage, employing safety-grade leak monitoring equipment such as gas detectors with high detection limits. The diffusion path monitoring network targets the degree of routine leakage pollution from equipment at risk of leakage and the scope of the leak impact of target leak events, employing environmental-grade pollution monitoring equipment such as gas monitors with low detection limits. Routine leaks refer to fugitive leaks caused by inadequate sealing. The boundary monitoring network targets the external pollution impact of the device, employing environmental-grade air quality monitoring equipment such as air quality monitoring stations with low detection limits. For target leak events, the leak source monitoring network detects the leak event; the diffusion path monitoring network identifies the scope of the leak event and, in conjunction with the leak source monitoring network, assists in improving the accuracy of leak identification and avoiding false alarms; the boundary monitoring network identifies whether the leak event has a pollution impact on the external environment of the device. For routine leaks, the diffusion path monitoring network monitors the degree of routine leakage pollution, and the boundary monitoring network monitors whether routine leaks have a pollution impact on the external environment of the device.

[0075] Furthermore, based on the high-pollution points in each heavily polluted area of ​​each leakage monitoring factor as diffusion pathways, multiple auxiliary diffusion pathways can be evenly distributed in the device area involving equipment at leakage risk. The recommended density of the auxiliary diffusion pathways is 1 / 10 to 1 / 20 of the leakage source monitoring network.

[0076] Furthermore, the process of matching and executing pre-defined response plans based on the impact assessment results includes: determining the location, type, and / or risk level of a leak based on the impact assessment results; matching the corresponding pre-defined response plan based on the location, type, and / or risk level of the leak; wherein the pre-defined response plan includes any one or more of the following: a graded early warning plan, a leak source cutoff plan, a leak substance suppression plan, and an environmental remediation plan.

[0077] In this embodiment of the invention, the system first analyzes the specific location of the leak event to determine the precise area where the leak occurred. This process helps to quickly pinpoint the source of the problem and provides direction for subsequent response measures. Furthermore, the system identifies the specific type of leak based on the characteristics of the leaked substance, such as a gas leak, a liquid leak, or other types of leaked substances. Simultaneously, the system assesses the risk level of the leak based on its scale, diffusion rate, and potential impact range. This risk level assessment is a key factor in selecting subsequent response strategies, ensuring the effectiveness and relevance of the response measures.

[0078] Furthermore, after obtaining the above assessment results, the system will select the most suitable solution from a pre-set solution library based on the specific location, type, and risk level of the leak. These pre-set solutions include, but are not limited to, the following:

[0079] 1) Tiered early warning scheme: Based on the risk level, different levels of early warning signals are automatically issued so that relevant personnel can respond quickly and take corresponding measures.

[0080] 2) Leakage source cutoff scheme: In the event of a serious leak, the system will trigger an emergency shutdown mechanism to automatically cut off the leakage source in order to prevent further losses.

[0081] 3) Leakage suppression scheme: The system can automatically activate measures to suppress the spread of leaked materials, such as deploying absorbents or activating pollution control equipment.

[0082] 4) Environmental remediation plan: For leaks that have already caused environmental impact, the system will activate an environmental remediation plan, including pollution cleanup and remediation measures.

[0083] Example 4:

[0084] For a leak source monitoring network covering equipment at risk of leakage, taking a catalytic cracking unit as an example, the leak monitoring factors are clearly defined as hydrogen sulfide, as well as propylene, propane, and butane. Since propylene, propane, and butane are all flammable gases and can be detected by flammable gas detectors, the target detector for hydrogen sulfide gas is set as a hydrogen sulfide gas detector, and the target detectors for propylene, propane, and butane are all flammable gas detectors. To simplify the process, propylene, propane, and butane can also be classified as flammable gas type 1 leak monitoring factors. That is, the leak monitoring factors for a catalytic cracking unit include both hydrogen sulfide and flammable gases.

[0085] A catalytic cracking unit includes 216 production equipment such as pumps, heat exchangers, towers, storage tanks, and compressors. The equipment and level of leakage risk involving hydrogen sulfide gas are assessed according to three levels: low, medium, and high. The equipment and level of leakage risk involving combustible gas are also assessed.

[0086] Based on the leakage monitoring factors and the leakage risk equipment and level, it is necessary to further clarify the coverage target of the leakage source monitoring network. It is recommended to set the coverage target of high leakage risk equipment at 95%, medium leakage risk equipment at 85%, and low leakage risk equipment at 80%, which can be considered as achieving effective coverage of leakage risk equipment.

[0087] Example 5:

[0088] The optimization and construction of a leakage source monitoring network for covering leakage risk devices is based on the principle of minimizing the number of target detectors while achieving the required coverage rate for leakage risk devices. Specifically, this involves rationally deploying the installation locations of target detectors to achieve effective coverage of leakage risk devices with the minimum number of detectors. Full coverage of leakage risk devices specifically includes a coverage rate of 95% for high leakage risk devices, 85% for medium leakage risk devices, and 80% for low leakage risk devices.

[0089] For newly built production facilities, the leakage risk equipment and levels of similar facilities can be statistically analyzed to identify the leakage risk equipment and levels of the newly built production facility. The scenario-based evaluation method can be selected as the evaluation method for coverage indicators. Through optimized point deployment, full coverage of leakage risk equipment can be achieved with the fewest target detectors. For different leakage monitoring factors, target detectors need to be selected separately and a leakage source monitoring network needs to be constructed. If a target detector can monitor two or more leakage monitoring factors at the same time, the two or more leakage monitoring factors can be merged into one leakage monitoring factor.

[0090] For production facilities with existing monitoring networks, the optimization of their leak source monitoring network needs to be carried out on the basis of the original monitoring network. A feasible implementation method is provided below:

[0091] A certain catalytic cracking unit has installed 65 combustible gas alarms and identified 126 leakage risk devices that are involved in combustible gas leakage. All of these are medium leakage risk devices, and the set coverage target for medium leakage risk devices is 85%.

[0092] Based on the scenario analysis method, 1000 combustible gas leakage risk scenarios were set up around 126 leakage risk devices. According to the coverage index, at least 850 leakage risk scenarios need to be covered. Analysis shows that the existing 65 combustible gas alarms have achieved effective coverage of 450 of these leakage scenarios. Compared with the coverage index, there are still 400 leakage scenarios missing. Therefore, the optimization and construction of the leakage source monitoring network should aim to achieve coverage of at least 400 of the remaining 550 leakage scenarios (excluding the 450 already covered).

[0093] Example 6:

[0094] The coverage assessment method includes spatial analysis and scenario analysis. The scenario method requires specifying the parameters of the specific leakage scenario, including the location of the leakage source, ambient air wind speed and direction, leakage components, material temperature and pressure, leakage orifice size and angle, and leakage source strength. The set leakage source strength is the magnitude of the leakage source strength to be measured. The specific leakage event is the leakage of a certain material at a certain source strength. For example, a 50 kg / h leakage of propylene material, that is, a leakage of propylene with a leakage risk monitoring factor exceeding 50 kg / h is defined as the target leakage event.

[0095] For the spatial method, the specific coverage area of ​​each target detector must first be determined. Currently, commonly used methods include the coverage area of ​​an 8m diameter sphere for toxic gases and the coverage area of ​​a 10m diameter sphere for combustible gases. The source strength can be calculated according to the definition of leakage and the calculation formula of leakage Q (gas leakage, unit kg / s) provided in the intelligent factory safety monitoring effectiveness assessment method.

[0096] Example 7:

[0097] Construction of a monitoring network for diffusion pathways covering heavily polluted areas.

[0098] To construct a diffusion pathway monitoring network, it is necessary to identify the leakage monitoring factors and the heavily polluted areas of each leakage monitoring factor, and to deploy monitoring stations to form a diffusion pathway monitoring network, with the high-pollution points in each heavily polluted area as diffusion pathway points.

[0099] Heavily polluted areas are areas with high concentrations of various leak monitoring factors that diffuse within the device due to reasons such as fugitive leaks. In other words, the heavily polluted areas are different for different leak monitoring factors and need to be identified one by one.

[0100] To improve the auxiliary effect of the diffusion path monitoring network in identifying target leakage events, based on the high pollution points in each heavily polluted area of ​​each leakage monitoring factor as diffusion path points, multiple auxiliary diffusion path points can be evenly distributed in the device area involving equipment with leakage risk. The recommended distribution density of the auxiliary diffusion path points is 1 / 10 to 1 / 20 of that of the leakage source monitoring network.

[0101] Example 8:

[0102] For a certain production facility, the following feasible method is provided to obtain spatial concentration distribution data of hydrogen sulfide gas:

[0103] Using a grid size of 10m × 10m × 10m, the three-dimensional space of the production unit is divided into grids, assuming that it can be divided into 245 reachable grid points. The hydrogen sulfide gas concentration of each grid is collected. A hydrogen sulfide gas monitor is selected, with a detection limit not higher than 10ppb. To improve detection efficiency, it is recommended that the response time not exceed 2 minutes. The annual wind frequency ratio of the area where the production unit is located is set as follows: east wind 25%, north wind 20%, northeast wind 15%, south wind 20%, and southeast wind 10%.

[0104] Hydrogen sulfide gas concentrations were collected at each reachable grid point under east, north, northeast, south, and southeast wind conditions. The detection time for a single grid point was 3 minutes. The maximum concentration value and coordinates at that location were recorded, which is the known spatial concentration distribution data under that wind direction.

[0105] Based on the known spatial concentration distribution data, the spatial interpolation algorithm is used to predict the concentration values ​​at other unsampled spatial locations, thus obtaining the spatial concentration distribution data of hydrogen sulfide.

[0106] Example 9:

[0107] In scenarios where each leakage monitoring factor has its own separate diffusion path monitoring network, for The calculations were performed, setting the annual wind frequency ratio of the area where the production unit is located to be 25% east wind, 20% north wind, 15% northeast wind, 20% south wind, and 10% southeast wind, and the spatial concentration distribution data under each wind direction were obtained.

[0108] For each grid point, calculate the weighted spatial concentration distribution data r. j ,Right now

[0109] A certain grid point r j = (East wind condition concentration value × 25% + North wind condition concentration value × 20% + Northeast wind condition concentration value × 15% + South wind condition concentration value × 20% + Southeast wind condition concentration value × 10%) ÷ (25% + 20% + 15% + 20% + 10%) for this grid point.

[0110] Example 10:

[0111] If a heavily polluted area is caused by a leak from a single known leak point, rather than by spillage leaks from multiple sealed points, and thus cannot characterize the normal leakage level of the area, then the area may not be defined as a diffusion pathway point, and timely repairs should be carried out.

[0112] Example 11:

[0113] Construction of a boundary monitoring network covering the boundaries of sensitive devices.

[0114] To construct a boundary monitoring network covering the boundaries of sensitive devices, it is necessary to identify the pollution monitoring factors and controlled boundary points, select environmental-grade low-concentration monitoring instruments suitable for the pollution monitoring factors, establish multiple monitoring instruments to form a pollution monitoring station and equip it with a meteorological five-parameter monitoring module, with the aim of maximizing the capture of leaked pollution, and optimize the construction of the boundary monitoring network by deploying pollution monitoring stations one-to-one according to the controlled boundary points.

[0115] The pollution monitoring factors are leaked gases that pose a risk of ambient air pollution. Common pollution monitoring factors include non-methane total hydrocarbons, VOCs, hydrogen sulfide, ammonia, nitrogen oxides, sulfur dioxide, ozone, odor concentration, particulate matter, etc. If a leaked gas present in a device does not pose a risk of ambient air pollution or has a low risk of pollution, it may not be considered a pollution monitoring factor, such as methane gas.

[0116] The following limits of detection can be selected for common pollution monitoring factors:

[0117] The detection limit for non-methane total hydrocarbons is not greater than 100 μg / m³. 3 VOCs detection limit is not greater than 100 ug / m³ 3 The detection limit for hydrogen sulfide is no greater than 20 μg / m³. 3 The detection limit for ammonia is no more than 50 μg / m³. 3 The detection limit for nitrogen oxides is no more than 30 μg / m³. 3 The detection limit for sulfur dioxide is no greater than 10 μg / m³. 3 The ozone detection limit is no more than 10 μg / m³. 3 The detection limit for particulate matter is no greater than 10 μg / m³. 3 .

[0118] Figure 4 This is a system structure diagram of a three-dimensional gas leak monitoring device provided in one embodiment of the present invention. Figure 4As shown, this invention provides a three-dimensional gas leak monitoring device for use in gas leak monitoring at petrochemical sites. The device includes: a data acquisition unit for acquiring operating condition information corresponding to each monitoring dimension under the target monitoring scenario, and optimizing the deployment of the monitoring network for each monitoring dimension based on the operating condition information; a monitoring unit for configuring the monitoring network for each monitoring dimension based on the optimized deployment result, and acquiring real-time monitoring data through communication transmission based on the configured monitoring network; an evaluation unit for identifying and evaluating leak events and their impacts in each monitoring dimension based on the real-time monitoring data, and obtaining evaluation results; and an execution unit for matching preset response plans based on the obtained evaluation results, and executing the matched response plan.

[0119] The present invention also provides a three-dimensional gas leak monitoring system, the system including the above-mentioned three-dimensional gas leak monitoring equipment.

[0120] This invention also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the aforementioned three-dimensional gas leak monitoring method.

[0121] The present invention also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The electronic device is characterized in that the processor executes the computer program to implement the above-described three-dimensional gas leakage monitoring method.

[0122] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described three-dimensional gas leakage monitoring method.

[0123] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0124] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details described above. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe the various possible combinations.

[0125] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, they should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A three-dimensional gas leakage monitoring method, applied to gas leakage monitoring in petrochemical sites, characterized in that, The method includes: Collect operating condition information corresponding to each monitoring dimension of the target monitoring area, and optimize the deployment of the monitoring network for each monitoring dimension based on the operating condition information; Based on the optimized deployment results of the monitoring network, the monitoring network is configured, and real-time monitoring data is obtained through communication transmission based on the configured monitoring network. Based on real-time monitoring data, leakage events are identified and their impact is assessed across various monitoring dimensions; Based on the impact assessment results, pre-set response plans are matched and then implemented.

2. The method according to claim 1, characterized in that, The monitoring dimensions include: Leak source monitoring dimension is used to monitor leakage events occurring at the location of the leak source; The diffusion pathway monitoring dimension is used to monitor leakage events and the degree of contamination of the leaked material in the target monitoring area. Boundary monitoring dimension is used to monitor leakage events and the extent of pollution impact of leaked materials on the external environment of the target monitoring area.

3. The method according to claim 2, characterized in that, The operating condition information corresponding to the leakage source monitoring dimension includes: The types of equipment at risk of leakage within the target monitoring area, the locations of equipment at risk of leakage, the types of leaked material at risk of leakage, historical leakage data of equipment at risk of leakage, and temperature and pressure parameters of equipment at risk of leakage; The operating condition information corresponding to the diffusion path monitoring dimension includes: The near-ground location or concentration accumulation location of the leaked gas that poses an explosion risk, combustion risk, or poisoning risk within the target monitoring area, as well as the corresponding distribution concentration of the leaked substance and historical airflow data for each location; The operating condition information corresponding to the boundary monitoring dimension includes: Historical airflow data of the target monitoring area where the equipment with leakage risk is located, boundary contour information of the target monitoring area, and layout information of the gathering area within a preset distance around the corresponding location.

4. The method according to claim 3, characterized in that, The optimization and deployment of the monitoring network based on the operating condition information for each monitoring dimension includes: Optimize the deployment of the monitoring network at the leak source detection level, including: Based on the types of equipment with leakage risk in the target monitoring area, the types of leaked substances with leakage risk, historical leakage data of equipment with leakage risk, and temperature and pressure parameters of equipment with leakage risk, the leakage risk level of each equipment with leakage risk is determined. Based on the type of leaked substance corresponding to each device with leakage risk, the monitoring factors are determined, and the type of monitoring device for the leakage source is determined based on the monitoring factors. The required detection coverage rate is determined based on the leakage risk level of each device with leakage risk. Based on the type of leakage source monitoring equipment, the location of equipment with leakage risk, and the required detection coverage index, the monitoring network for leakage source monitoring is optimized using the detection coverage assessment method, following the principle of achieving the detection coverage index while minimizing the number of leakage source monitoring devices.

5. The method according to claim 3, characterized in that, The optimization and deployment of the monitoring network based on the operating condition information for each monitoring dimension includes: Optimize the deployment of the monitoring network for diffusion pathway monitoring, including: Leaked gases that pose risks of explosion, combustion, or poisoning are used as monitoring factors. Based on the near-ground location or concentration accumulation location of each monitoring factor in the target monitoring area, as well as the corresponding distribution concentration of the leaked material and historical airflow data at each location, the spatial concentration distribution data of each monitoring factor in the target monitoring area is calculated. Based on the distribution concentration of leaked substances of each monitoring factor in the target monitoring area under different wind directions, one or more closed areas where the distribution concentration of leaked substances exceeds the limit are used to determine the key pollution areas of each monitoring factor. The installation range of each diffusion monitoring device is determined based on the key pollution areas of each monitoring factor; The type of diffusion monitoring equipment is determined based on each monitoring factor; Based on the type of diffusion monitoring equipment and the installation range of each diffusion monitoring equipment, the monitoring network for diffusion pathway monitoring is optimized according to the principle that each key pollution area under different wind directions should have at least one diffusion monitoring equipment, the total number of diffusion monitoring equipment should be minimized, and the spatial concentration distribution data of the diffusion monitoring equipment deployment location should be maximized.

6. The method according to claim 5, characterized in that, The calculation of spatial concentration distribution data of each monitoring factor in the target monitoring area based on the near-ground location or concentration accumulation location of each monitoring factor that can diffuse to the target monitoring area, and the corresponding leakage concentration and historical airflow data at each location, includes: Based on the historical airflow data, determine the wind frequency coefficient and number of wind directions for each wind direction in the target monitoring area; Based on the wind frequency coefficient, the number of wind directions, and the concentration distribution of leaked substances at each location, the spatial concentration distribution data of each monitoring factor in the target monitoring area are calculated. The calculation rule is as follows: Where, r j The data represent the concentration distribution of leaked material at each location for the j-th monitoring factor. a ij Let be the concentration of the leaked material at the location of the pollution point corresponding to the j-th monitoring factor under the i-th wind direction; f i Let be the wind frequency coefficient under the i-th wind direction; N represents the number of wind directions.

7. The method according to claim 6, characterized in that, The method further includes: For diffusion monitoring devices that monitor multiple factors and need to be deployed in overlapping areas of key pollution zones for these factors, to achieve simultaneous monitoring of multiple leaked gases in multiple heavily polluted areas by a single device, it is necessary to calculate the weighted spatial concentration distribution data of multiple monitoring factors. The calculation rules are as follows: Where r represents the weighted spatial concentration distribution data of multiple monitoring factors; i∈[1,N], where N is the total number of different wind directions; f i Let be the wind frequency coefficient for the i-th wind direction; j∈[1,M], where M is the total number of different monitoring factors; a ij This refers to the concentration data of the leaked material at each location under the i-th wind direction and for the j-th monitoring factor; l j Let be the emission limit for the concentration at the plant boundary of the j-th monitoring factor.

8. The method according to claim 3, characterized in that, The optimization and deployment of the monitoring network based on the operating condition information for each monitoring dimension includes: Optimize the deployment of the monitoring network for boundary monitoring dimensions, including: Based on historical airflow data of the target monitoring area where the equipment with leakage risk is located and the boundary contour information of the target monitoring area, the upwind and downwind boundary points of the target monitoring area are determined. The sensitive boundary points of the target monitoring area are determined based on the layout information of the cluster area within a preset distance around the corresponding location. Based on the sensitive boundary points, the upwind boundary points, and the downwind boundary points, each controlled boundary point of the target monitoring area is determined; Based on the principle of setting up at least one set of boundary monitoring equipment at each controlled boundary point, the monitoring network of each controlled boundary point is optimized and deployed.

9. The method according to claim 8, characterized in that, Based on historical airflow data and boundary contour information of the target monitoring area where the equipment with leakage risk is located, the upwind and downwind boundary points of the target monitoring area are determined, including: Determine the prevailing wind direction based on historical airflow data of the target monitoring area where equipment with leakage risk is located; The foremost point of the upwind boundary in the prevailing wind direction is defined as the upwind boundary point. Obtain the boundary contour information of the target monitoring area and project it vertically onto the device area on the ground. Take the line segment where the straight line of the prevailing wind direction overlaps with the vertical projection of the device area as the target line segment. Calculate the location of the target line segment with the longest length and take the downwind endpoint of the line segment as the downwind boundary point. If the pollutant concentration distribution data in the three-dimensional space of the target monitoring area is known, the area that overlaps with the three-dimensional space of the target monitoring area at the vertical section of the prevailing wind direction is defined as the target area. The location of the target area with the largest pollutant area integral concentration value is calculated, and the downwind endpoint of the vertical projection of the target area is taken as the downwind boundary point.

10. The method according to claim 1, characterized in that, The process of configuring the monitoring network based on the optimized deployment results and acquiring real-time monitoring data through communication transmission via the configured monitoring network includes: Based on the results of the optimized deployment of the monitoring network, determine the deployment type, quantity, and location of all monitoring devices within the target monitoring area, and execute the on-site deployment of each monitoring device; In response to the start signal, the system performs communication initialization for each monitoring device, verifies whether each monitoring device is communicating normally, and begins acquiring real-time monitoring data after the verification is passed.

11. The method according to claim 1, characterized in that, Based on the real-time monitoring data, leakage events are identified and their impact is assessed across various monitoring dimensions to obtain assessment results, including: Based on the monitoring data from the leak source monitoring dimension, and combined with the leak thresholds of each preset monitoring factor, a leak event is identified. After a leak event is determined to have occurred, based on monitoring data from the diffusion pathway monitoring dimension and the spatial location of each diffusion monitoring device, a spatial concentration interpolation algorithm is used to draw a contour line with a preset concentration threshold centered on the location of the leak event, thus determining the spatial impact range of the leak event. Based on monitoring data from the boundary monitoring dimension and the preset pollution emission thresholds for each monitoring factor, it is determined whether the leak event has a pollution impact on the external environment of the target monitoring area. The location where the leakage event occurred is the spatial location of the leakage source monitoring device that was identified as a leakage event.

12. The method according to claim 1, characterized in that, Before obtaining the assessment results by identifying leakage events and assessing their impact across various monitoring dimensions based on the real-time monitoring data, the method further includes: Identify the monitoring devices corresponding to each monitoring data point and determine whether the corresponding monitoring device belongs to a monitoring network of a single monitoring dimension; If so, the corresponding monitoring data will be classified into the monitoring network dataset of the corresponding monitoring dimension; If not, determine the number of monitoring networks in the monitoring dimension to which the corresponding monitoring device belongs, and perform the corresponding number of monitoring data copies based on the number of monitoring networks in the monitoring dimension to which the device belongs; The copied monitoring data are classified into monitoring network datasets of their respective monitoring dimensions, and one copy of the monitoring data is obtained for each monitoring network dataset of each monitoring dimension.

13. The method according to claim 1, characterized in that, The process of matching pre-defined response plans based on the impact assessment results and executing the matched response plans includes: Based on the impact assessment results, determine the location, type, and / or risk level of any leaks that pose a risk. Based on the leak location, leak type, and / or leak risk level, a corresponding preset response plan is matched; wherein... The preset response plan includes any one or more of the following: a graded early warning plan, a leak source cutoff plan, a leak material suppression plan, and an environmental remediation plan.

14. A three-dimensional gas leak monitoring device, applied to gas leak monitoring in petrochemical sites, characterized in that, The device includes: The data acquisition unit is used to acquire the operating condition information corresponding to each monitoring dimension of the target monitoring area, and to optimize the deployment of the monitoring network for each monitoring dimension based on the operating condition information. The monitoring unit is used to configure the monitoring network for each monitoring dimension based on the optimized deployment results of the monitoring network, and to obtain real-time monitoring data based on the configured monitoring network communication transmission. The evaluation unit is used to identify leakage events and assess their impact based on the real-time monitoring data across various monitoring dimensions, and to obtain evaluation results. The execution unit is used to match preset response plans based on the obtained evaluation results and execute the matched response plans.

15. A three-dimensional gas leak monitoring system, applied to gas leak monitoring in petrochemical sites, characterized in that, The system includes the gas leak three-dimensional monitoring device as described in claim 14.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the gas leak three-dimensional monitoring method as described in any one of claims 1-13.

17. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the gas leakage three-dimensional monitoring method according to any one of claims 1-13.

18. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the gas leakage three-dimensional monitoring method according to any one of claims 1-13.

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