A rapid gas leak location and handling system based on swarm intelligence

Abstract

This application discloses a rapid gas leak location and handling system based on swarm intelligence, comprising: several aircraft for obtaining optimal flight routes and executing flight commands, wherein the optimal flight route refers to the inspection route with the shortest flight distance from the starting point to the endpoint and the fewest overlapping flight segments with other aircraft; a laser methane telemetry module for monitoring methane concentration, with at least one laser methane telemetry module installed on the bottom of each aircraft; a coordinate module for acquiring aircraft coordinates; a curve plotting module for plotting a curve comparing aircraft coordinates and methane concentration; and a judgment and processing module for determining the gas leak location and executing an emergency handling plan when the gas concentration detected by the laser telemetry module array exceeds a preset lower threshold. This system can locate the leak source more efficiently and accurately, greatly improving inspection efficiency and reducing inspection costs.

Description

Technical Field

[0001] This application relates to the field of industrial security monitoring technology, and in particular to a rapid gas leak location and handling system based on swarm intelligence. Background Technology

[0002] Currently, urban gas pipelines are facing increasingly serious problems of corrosion and aging. In addition, illegal construction, unauthorized encroachment, and blind excavation around gas pipelines and facilities are rampant despite repeated bans, resulting in damage to gas pipelines and facilities and frequent gas leaks, posing a huge challenge to urban safety.

[0003] Currently, gas information technology projects mainly employ static, discrete sampling methods, enabling only monitoring and early warning functions. Due to high construction costs, these projects are typically limited to small-scale technical upgrade demonstrations and cannot achieve full coverage of the gas pipeline network. This falls far short of the required "real-time monitoring, timely early warning, and effective response." Therefore, there is an urgent need to adopt new technologies to reduce costs and improve efficiency to ensure the safe operation of urban gas pipelines. Summary of the Invention

[0004] This specification provides an embodiment of a gas leak rapid location and handling system based on swarm intelligence, which is used to solve the problems of high cost or low efficiency caused by monitoring large-scale gas pipeline networks in the prior art.

[0005] The technical solutions provided in the embodiments of this specification are as follows:

[0006] This application provides a gas leak rapid location and handling system based on swarm intelligence, including:

[0007] Several aircraft are used to obtain the optimal flight route and execute flight commands. The optimal flight route is the inspection route that has the shortest flight distance from the start point to the end point for each aircraft and the fewest overlapping flight segments with other aircraft.

[0008] A laser methane telemetry module is used to monitor methane concentration, and at least one of the laser methane telemetry modules is installed on the bottom of each of the aircraft.

[0009] The coordinate module is used to obtain the coordinates of the aircraft.

[0010] The curve plotting module is used to plot the curve comparing the aircraft coordinates with the methane concentration.

[0011] The judgment and processing module is used to determine the gas leak location and execute the emergency response plan when the gas concentration detected by the laser telemetry module array exceeds the preset lower threshold.

[0012] Furthermore, obtaining the optimal flight route includes:

[0013] The patrol area is divided into several grid cells and uniformly numbered;

[0014] The drone selects the corresponding grid cell to obtain the optimal flight route through broadcast negotiation.

[0015] Furthermore, the broadcast negotiation method for selecting the corresponding grid cell includes:

[0016] All members of a drone swarm form a distributed network via wireless communication.

[0017] If one of the drones does not receive an objection message when it applies for patrol route N, the application is successful, and it broadcasts information to other drones that the grid cells of route N are occupied.

[0018] Once the N-route inspection task is completed, the patrol status table is updated and a broadcast message indicating that the N-route inspection is complete is sent to other drones.

[0019] Furthermore, the broadcast negotiation method for selecting the corresponding grid cell also includes:

[0020] If at least two drones request to patrol the M route, an objection message will be received;

[0021] The cruise distance and flight time of each drone on route M are obtained. The drone with the lower data is excluded from the application, and the drone with the best data can reapply. If no objection is received, the application is successful.

[0022] Furthermore, the drone is equipped with a laser methane telemetry module mounted directly below the center of the fuselage and below each rotor.

[0023] Furthermore, each laser methane telemetry module is connected to the drone via a small turntable.

[0024] Furthermore, obtaining the aircraft coordinates includes: equipping the UAV with a high-precision GPS and laser ranging module; and obtaining the latitude and longitude coordinates of the measurement points of the laser methane telemetry module based on the UAV's flight altitude measured by the high-precision GPS and laser ranging modules, and the turntable angle data of each rotor telemetry module.

[0025] Furthermore, determining the location of the gas leak includes:

[0026] Based on subtle differences in gas concentration, the location of potential leak sources can be determined;

[0027] Adjust the drone's cruise route to ensure it heads precisely towards the leak source;

[0028] Measures such as lowering the drone's flight altitude or adjusting the angle between the telemetry module and the vertical direction can be taken to reduce the scanning range;

[0029] With the help of pressure data uploaded by smart pressure gauges on the gas pipeline, the source of the leak was finally located.

[0030] Furthermore, the emergency response plan includes:

[0031] The system sends a command to the intelligent safety valve to immediately interrupt the gas supply in the leak source pipeline, activates the valve of the backup pipeline to continue supplying gas through the backup channel, and sends the specific location information of the faulty pipeline section to the backend, prompting relevant departments to carry out repairs or replacements as soon as possible.

[0032] Furthermore, the drone is equipped with a 720° 3D panoramic high-definition camera to acquire scene data in real time and make informed decisions.

[0033] The above-mentioned technical solutions adopted in the embodiments of this application can achieve the following beneficial effects: they can locate the leakage source more efficiently and accurately, greatly improve the inspection efficiency, and reduce the inspection cost. Attached Figure Description

[0034] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0035] Figure 1 This is a schematic diagram of the overall structure provided for the embodiments of this specification;

[0036] Figure 2 A schematic diagram of grid cell numbering provided for embodiments of this specification;

[0037] Figure 3 A schematic diagram showing the horizontal distribution of a laser methane telemetry module mounted on a quadcopter drone, as provided in an embodiment of this specification.

[0038] Figure 4 This is a schematic diagram illustrating the range that can be monitored by a small turntable, as provided in the embodiments of this specification.

[0039] Figure 5 The monitoring range at a flight altitude of 95 meters is provided for the embodiments of this specification;

[0040] Figure 6 This is a schematic diagram illustrating the monitoring effect provided in the embodiments of this specification. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0042] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0043] This specification provides an embodiment of a rapid gas leak location and handling system based on swarm intelligence. Please refer to [link / reference]. Figure 1 As shown, it includes an aircraft 1, a laser methane telemetry module 2, a coordinate module 3, a curve plotting module 4, and a judgment and processing module 5.

[0044] The system includes several aircraft, which are used to obtain the optimal flight route and execute flight commands. The optimal flight route is the inspection route that has the shortest flight distance from the start point to the end point and the fewest overlapping flight segments with other aircraft. The aircraft include, but are not limited to, quadcopters and octagonal aircraft.

[0045] In one possible implementation, such as Figure 2 As shown, obtaining the optimal flight route includes: dividing the cruise area into several grid cells and numbering them uniformly; the UAV selects the corresponding grid cell through broadcast negotiation to obtain the optimal flight route.

[0046] To further explain, the broadcast negotiation method for selecting the appropriate grid cell includes: all members of the drone swarm form a distributed network through wireless communication; if one drone applies for a patrol route N without receiving an objection message, the application is successful, and a broadcast message indicating that the grid cell for route N is occupied is sent to other drones; after the inspection task of route N is completed, the patrol status table is updated and a broadcast message indicating that the inspection of route N is completed is sent to other drones.

[0047] Specifically, when facing vast inspection areas, the multi-drone collaborative approach significantly improves inspection efficiency. During the assignment of patrol tasks, the system divides the entire patrol area into several grid cells and assigns them unique numbers, then imports this information into the drone swarm. Each drone selects the appropriate grid cell to perform the inspection task through broadcast negotiation. All members of the drone swarm form a distributed network via wireless communication. Suppose a member wants to perform the inspection task of grid cell N, it will first broadcast a request to other members in the network. If no objection is received within a specified time, the request is considered successful. The member immediately broadcasts a message to other members indicating that grid cell N is already occupied (currently patrolling). Other members record this message to avoid task conflicts.

[0048] In addition, when the inspection task of grid cell N is completed, the member who performed the task will broadcast a message to other members indicating that grid cell N has been inspected. Upon receiving this message, other members will record it and update the "Area Inspection Status Table" in real time to ensure efficient information synchronization and avoid unnecessary work.

[0049] In another possible implementation, if at least two drones apply to cruise route M, an objection message will be received; the cruise distance and flight time of all drones cruising route M will be obtained respectively, the drone with the lower data will withdraw its application, and the drone with the best data will reapply. If no objection message is received, the application will be successful.

[0050] Specifically, when two or more members simultaneously apply to execute the inspection task of grid cell M, they may receive objections from each other. In this case, the conflicting members enter a negotiation phase. The arbitration algorithm makes a decision based on data such as distance differences and endurance differences, using a survival-of-the-fittest principle. The weaker member voluntarily withdraws from the competition, while the stronger member resubmits the application for the inspection task of grid cell M. If there are no objections, the application is successful; if there are objections, the process continues.

[0051] The laser methane telemetry module is used to monitor methane concentration, and at least one laser methane telemetry module is installed on the bottom of each aircraft.

[0052] In one possible implementation, please refer to Figure 3As shown, this embodiment uses a quadcopter drone, with a laser methane telemetry module mounted directly below the center of the fuselage and under each rotor. This allows for simultaneous multi-point data acquisition, increasing the coverage area of ​​a single flight and enabling rapid location of the leak source based on concentration distribution patterns, providing crucial reference data for cruise path planning. Depending on the application scenario and requirements, quadcopter, hexacopter, and octacopter drones can be selected. The choice is based on need and is not limited here.

[0053] In one possible implementation, each laser methane telemetry module is connected to the UAV via a small turntable. It can rotate freely 360° horizontally and 90° vertically. By adjusting the horizontal and vertical angles of the telemetry modules mounted under the rotor, the scanning width can be dynamically adjusted, thereby achieving efficient and accurate inspection. Figure 4 As shown.

[0054] A coordinate module is used to obtain the coordinates of the aircraft. For example, a drone may be equipped with a high-precision GPS and laser ranging module. Based on the drone's flight altitude measured by the high-precision GPS and laser ranging modules, and the turntable angle data of each rotor telemetry module, the latitude and longitude coordinates of the measurement points of the laser methane telemetry module can be obtained. In specific applications, such as... Figure 5 As shown, the flight altitude and the angle between the telemetry module are adjusted according to the actual situation on site. The flight altitude is set to 95 meters, the horizontal orientation of the rotor telemetry module is kept away from the center of the UAV, and the vertical direction is at an angle of 6° with the axis. Then the scanning width is about 20 meters. With this configuration, it is generally possible to cover a grid inspection area with a width of 500 meters after 25 flights.

[0055] The curve plotting module is used to plot a curve comparing the aircraft coordinates with the methane concentration.

[0056] The judgment and processing module is used to determine the gas leak location and execute the emergency response plan when the gas concentration detected by the laser telemetry module array exceeds the preset lower threshold.

[0057] In one possible implementation, determining the location of a gas leak includes: obtaining the orientation of potential leak sources based on subtle differences in gas concentration; adjusting the drone's cruise route to precisely head towards the leak source; reducing the drone's flight altitude or adjusting the angle between the telemetry module and the vertical direction to narrow the scanning range; and supplementing this with pressure data uploaded by smart pressure gauges on the gas pipeline to ultimately pinpoint the leak source.

[0058] Specifically, when the gas concentration detected by the laser telemetry module array exceeds a preset lower threshold, the system immediately performs in-depth analysis of data from various sensors. Based on subtle differences in gas concentration, it intelligently infers the location of potential leak sources and quickly adjusts the drone's cruise route to precisely head towards the leak source. In the final stage of leak point localization, to accelerate the location process, measures such as lowering the drone's flight altitude or adjusting the angle between the telemetry module and the vertical direction can be taken to narrow the scanning range. Simultaneously, real-time concentration data is sent to other members of the drone swarm as an important reference for their path planning. This strategy not only improves the efficiency and accuracy of leak detection but also enhances the collaborative capabilities of the entire drone swarm.

[0059] Once the inspection of a grid cell is completed, the corresponding grid status is carefully marked, primarily including both leak and non-leakage scenarios. If a leak is detected, relevant data, such as the concentration distribution in the leak area and high-risk leak points, will be shared immediately. In cases where a gas leak spans multiple grid cells, a second round of detailed supplementary inspections will be conducted on the leaking grid after the initial inspection. The core of this round of inspections is to further pinpoint the leak source. By conducting joint static data collection and observation of the leak area over a certain period, eliminating interference from airflow or other factors, and supplementing this with pressure data uploaded by smart pressure gauges on the gas pipeline, the leak source is ultimately located.

[0060] Another possible implementation includes an emergency response plan that involves sending a command to the smart safety valve to immediately interrupt the gas supply in the leak source pipeline, activating the valve on the backup pipeline to continue supplying gas through the backup channel, and sending the specific location information of the faulty pipeline section to the backend to prompt relevant departments to carry out repairs or replacements as soon as possible.

[0061] Specifically, once the leak source is precisely located, the drone will send a command to the intelligent safety valve to immediately interrupt the gas supply in the current pipeline and activate the valve on the backup pipeline to continue gas supply through the backup channel. After successfully switching the gas supply line, the system will continuously and dynamically monitor the gas concentration in the leak area. If the gas concentration is detected to gradually decrease, it indicates that the emergency measures have effectively controlled the situation. At this time, the system will send the specific location information of the faulty pipeline section to the backend, prompting relevant departments to carry out repairs or replacements as soon as possible. This process not only achieves real-time monitoring and early warning of potential risks but also ensures immediate on-site response and handling, thereby eliminating or reducing the risk of accidents in the shortest possible time.

[0062] To further clarify, when the gas leak source is precisely located near a gas processing plant or outdoor overhead pipeline, the system's on-site emergency response mechanism is immediately activated. The drone-based spraying system responds rapidly, spraying a dense mist of water to mix the gas with air, effectively reducing the gas concentration and ensuring it falls below the lower explosive limit, thereby eliminating the risk of a gas explosion. Simultaneously, the increased water mist also raises air humidity, which not only helps reduce the probability of static sparks but also further reduces the risk of a gas explosion, providing more comprehensive safety assurance on-site.

[0063] Preferably, the drone is equipped with a 720° 3D panoramic high-definition camera for real-time scene acquisition and informed decision-making. For example, each drone is equipped with a 720° 3D panoramic high-definition camera and image-based deep learning algorithms. This enables the drone to quickly identify various complex hazards, including malicious human attacks and dangerous scenes in the natural environment. Once a threat is detected, the drone immediately adjusts its flight strategy to ensure the equipment is not hijacked or damaged. Furthermore, in applications involving locating leaks in overhead pipelines, the drone can spray a specific concentration of soap solution onto the target area and then use real-time image analysis to quickly and accurately locate the leak.

[0064] The following is a case study in practical implementation. Assume the inspection target is a rectangular area with dimensions of 6000 meters on each side and 1000 meters on the other. The system platform divides this area evenly into 6 grid units, each with dimensions of 2000 meters on each side and 500 meters on the other side, and then... Figure 2 The drones are numbered as shown. This inspection mission will be carried out by a cluster (or formation) of four quadcopter drones, numbered A, B, C, and D. To ensure the accuracy of the inspection, the system requires that the scanning width of each drone during its cruise does not exceed 25 meters, and the coordinate information of the scanned area and the specific grid information will be imported into the drone cluster.

[0065] After the patrol mission is assigned to the drone swarm, each drone autonomously negotiates and selects the grid cell to be inspected for the first time. For example, drone A selects grid cell number 1, drone B selects grid cell number 2, drone C selects grid cell number 3, and drone D selects grid cell number 4. Since there is no conflict, all applications are approved at once. Then each drone autonomously plans its flight route based on the location of the target grid cell.

[0066] When performing inspection tasks in each grid cell, the UAV automatically adjusts its flight altitude and the angle between the telemetry module and the system requirements, taking into account the actual site conditions. Figure 5As shown, with the flight altitude set at 95 meters, the horizontal orientation of the rotor telemetry module is kept away from the center of the UAV, and the vertical direction is at an angle of 6° with the axis. The scanning width is approximately 20 meters. With this configuration, it is generally possible to cover a grid inspection area with a width of 500 meters in 25 flights.

[0067] During the patrol, once UAV B detects that the concentration of leaked gas exceeds the preset lower warning threshold, it will immediately activate the leak source tracking mechanism. This involves reducing flight speed and adjusting the flight direction based on sensor array data and leak location assessments, aiming to precisely locate the point with the highest methane gas concentration within the grid area. Once the maximum gas concentration is identified, if this concentration reaches or exceeds the upper warning threshold, the UAV will quickly initiate on-site emergency response measures, including valve activation, sealing, and spraying. Conversely, if the highest concentration does not reach the upper warning threshold, the UAV will continue to patrol the uncovered areas within the grid according to the predetermined strategy, ensuring data integrity and continuity.

[0068] Suppose that drone A completes the inspection task of grid cell number 1 ahead of the other members of the cluster, while the other members are still busy on their respective inspection routes. At this moment, drone A quickly changes its target and successfully requests and begins the inspection of grid cell number 5. Following closely behind, drone C, after completing the inspection of grid cell number 3, also successfully shifts its target to grid cell number 6. Soon after, drones D and B complete the inspection tasks of grid cells numbered 4 and 2 respectively. At this point, all areas to be inspected have been covered.

[0069] Suppose that in this series of inspections, only grid cell numbered 2 was found to have a gas leak. Therefore, drones D and B immediately re-inspected the leak area of ​​that grid cell and subdivided it into two independent sub-cells. Through an efficient negotiation mechanism, each drone was responsible for one sub-area, collecting data and continuously tracking the point of maximum concentration, ensuring the accuracy of the monitoring and avoiding misjudgments caused by air diffusion or other factors.

[0070] After the first round of inspections, all data was comprehensively analyzed. The results showed that grid cells numbered 2 and 5 both had excessive gas concentrations. Therefore, in the second round of inspections, drones D and B jointly conducted a more in-depth inspection of grid cell number 2, while drones A and C were responsible for a re-inspection of grid cell number 5. The four drones shared data in real time, forming a closely collaborative system. This continuous, real-time data analysis allowed for a more accurate depiction of the gas distribution in the leak area and the most likely location of the leak source.

[0071] This system ingeniously integrates the significant advantages of TDLAS laser telemetry technology, including its long-range detection capability, high-precision measurement performance, fast response time, and excellent anti-interference ability. Simultaneously, by combining it with the swarm intelligence of UAV clusters, it achieves an efficient monitoring strategy: starting from single-point sampling, extending to lines, and then expanding to areas, it generates real-time, intuitive images of gas concentration and its coordinate distribution within the inspected area. Figure 6 This is a simplified illustration. This innovative method allows regulators to clearly understand the situation on-site.

[0072] Furthermore, the collaborative operation mode of multiple drones provides the ability to overlook the entire situation from a higher perspective, thereby locating the leak source more efficiently and accurately, and enabling rapid response. Thanks to the powerful scalability of drone swarms, the number of drones can be flexibly adjusted according to the scope of the inspection task, ensuring adaptability to a wider range of monitoring needs.

[0073] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

[0074] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0075] Therefore, this application also proposes a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the methods described in any embodiment of this application.

[0076] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0077] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0078] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0079] Furthermore, this application also proposes an electronic device (or computing device) including 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 method described in any embodiment of this application.

[0080] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory. Memory may include non-persistent memory in computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media. Computer-readable media includes both permanent and non-persistent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information that can be accessed by the computing device. As defined in this article, computer-readable media do not include transient media, such as modulated data signals and carrier waves.

[0081] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0082] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when an element is “connected” or “coupled” to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein may include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0083] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical, technical, and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0084] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A rapid gas leak location and handling system based on swarm intelligence, characterized in that, include: Several aircraft are used to obtain the optimal flight route and execute flight commands. The optimal flight route is the inspection route that has the shortest flight distance from the start point to the end point for each aircraft and the fewest overlapping flight segments with other aircraft. A laser methane telemetry module is used to monitor methane concentration, and at least one of the laser methane telemetry modules is installed on the bottom of each of the aircraft. The coordinate module is used to obtain the coordinates of the aircraft. The curve plotting module is used to plot the curve comparing the aircraft coordinates with the methane concentration. The judgment and processing module is used to determine the gas leak location and execute the emergency response plan when the gas concentration detected by the laser telemetry module array exceeds the preset lower threshold. The process of obtaining the optimal flight route includes: dividing the cruise area into several grid cells and uniformly numbering them; the several aircraft autonomously selecting the corresponding grid cells through broadcast negotiation to form the optimal flight route; The laser methane telemetry module is arranged in an array, specifically: one laser methane telemetry module is mounted on the underside of the center of the UAV and on the underside of each rotor. The process of determining the location of a gas leak includes: obtaining the location of a potential leak source based on differences in gas concentration; adjusting the drone's cruise route to move towards the leak source; reducing the drone's flight altitude or adjusting the angle between the telemetry module and the vertical direction to narrow the scanning range; and supplementing this with pressure data uploaded by smart pressure gauges on the gas pipeline to ultimately pinpoint the leak source. The emergency response plan includes: issuing a command to the intelligent safety valve to interrupt the gas supply in the leak source pipeline and activating the valve of the backup pipeline to continue supplying gas through the backup channel; when the leak source is located in the vicinity of a gas treatment plant or an outdoor overhead pipeline, controlling the drone spraying system to spray water mist to reduce the gas concentration; and sending the specific location information of the faulty pipeline section to the backend.

2. The gas leak rapid location and handling system based on swarm intelligence according to claim 1, characterized in that, The broadcast negotiation method for selecting the corresponding grid cell includes: All members of a drone swarm form a distributed network via wireless communication. If one of the drones does not receive an objection message when it applies for patrol route N, the application is successful, and it broadcasts information to other drones that the grid cells of route N are occupied. Once the N-route inspection task is completed, the patrol status table is updated and a broadcast message indicating that the N-route inspection is complete is sent to other drones.

3. The gas leak rapid location and handling system based on swarm intelligence according to claim 1, characterized in that, The selection of the corresponding grid cell in the broadcast negotiation method also includes: If at least two drones request to patrol the M route, an objection message will be received; The cruise distance and flight time of each drone on route M are obtained. The drone with the lower data is excluded from the application, and the drone with the best data can reapply. If no objection is received, the application is successful.

4. The gas leak rapid location and handling system based on swarm intelligence according to claim 1, characterized in that, The drone is equipped with a laser methane telemetry module mounted directly below the center of the fuselage and under each rotor.

5. A rapid gas leak location and handling system based on swarm intelligence as described in claim 1, characterized in that, Each laser methane telemetry module is connected to the UAV via a small turntable.

6. The gas leak rapid location and handling system based on swarm intelligence according to claim 1, characterized in that, Obtaining the aircraft coordinates involves: equipping the UAV with a high-precision GPS and laser ranging module; and obtaining the latitude and longitude coordinates of the measurement points of the laser methane telemetry module based on the UAV's flight altitude measured by the high-precision GPS and laser ranging modules, as well as the turntable angle data of each rotor telemetry module.

7. A rapid gas leak location and handling system based on swarm intelligence as described in claim 1, characterized in that, The drone is equipped with a 720° 3D panoramic high-definition camera to acquire real-time scene data and make informed decisions.

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