Pipeline transportation carbon dioxide leakage detection and capture system

Abstract

According to the pipeline transportation carbon dioxide leakage detection and capture system provided by the invention, multiple sensors are deployed at key nodes of a pipeline to monitor environmental data in real time, and when leakage is detected according to the monitoring data, the unmanned aerial vehicle is immediately dispatched to carry out field verification; a leakage point is identified based on the infrared image data of the unmanned aerial vehicle, and the unmanned aerial vehicle is controlled to capture carbon dioxide at the leakage point; and after it is confirmed that leakage of the leakage point is effectively controlled, a maintenance processing center is notified to arrange maintenance of the leakage point and recovery of cooled carbon dioxide. According to the method, the response speed and accuracy of leakage detection can be improved, the situations of manual intervention and false alarm are reduced, and especially in a complex environment and a large-scale pipeline network, leakage points can be quickly and accurately found and processed. In addition, the system also has high flexibility and expansibility, can be modified and upgraded according to actual requirements, adapts to various operation environments and detection scenes, and improves the pipeline transportation safety.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon dioxide detection, and in particular to a pipeline transportation carbon dioxide leakage detection and capture system. Background Art

[0002] As an important greenhouse gas, carbon dioxide is widely used in many industrial processes, especially in the oil, natural gas and chemical industries. At the same time, carbon dioxide is also widely used in carbon dioxide capture and storage (CCS) technology to reduce greenhouse gas emissions. Since carbon dioxide has a strong greenhouse effect, its leakage poses a potential hazard to the environment and human health. Therefore, it is particularly important to study the detection and capture technology of carbon dioxide leakage. In the transportation process of carbon dioxide, pipeline transportation is one of the most common methods. However, due to factors such as pipeline aging, improper operation, and external interference, carbon dioxide leakage has become a more serious problem. This may not only lead to the waste of gas resources, but also cause serious pollution to the surrounding environment. Since carbon dioxide is colorless and odorless when leaking, traditional leak detection methods usually have problems with delayed response and inaccurate positioning. Therefore, the development of more efficient and accurate carbon dioxide leak detection technology has become an urgent need.

[0003] Currently, CO2 leak detection technologies primarily focus on sensor monitoring, infrared detection, and acoustic sensing. Sensor technologies typically rely on real-time monitoring with pressure, temperature, or gas concentration sensors. While these methods can detect leaks to a certain extent, they often struggle to precisely locate leaks due to limitations in sensor deployment range and response speed, and can result in false alarms or missed detections in harsh environments. Infrared technology, which can detect CO2 leaks using thermal imaging cameras, offers good localization capabilities. However, due to limitations in coverage and environmental interference, it often requires manual intervention and subsequent processing, and exhibits low accuracy and response speed. Acoustic technology, which monitors pipeline vibrations and sound wave changes to infer leak locations, can also be affected by noisy environments. Existing detection technologies suffer from numerous shortcomings, particularly in terms of real-time performance, accuracy, and comprehensiveness, leaving significant room for improvement. This makes current technologies unable to meet the growing demand for efficient leak detection. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a pipeline transportation carbon dioxide leakage detection and capture system to solve the technical problems of the existing pipeline carbon dioxide leakage detection method such as poor accuracy, poor real-time performance, slow response speed and small coverage.

[0005] To achieve the above-mentioned and other related objectives, the present invention provides a pipeline transport carbon dioxide leak detection and capture system, comprising: an environmental monitoring center, including environmental monitoring modules disposed at multiple key points within the pipeline, for collecting environmental data from each key point within the pipeline in real time; an unmanned aerial vehicle (UAV) operation center, including multiple UAVs equipped with infrared cameras and carbon dioxide capture devices, for collecting thermal images using the infrared cameras and cooling leaked carbon dioxide using the carbon dioxide capture devices; a maintenance and processing center, for arranging repairs to the leak points and recovering the cooled carbon dioxide; and a data processing and control center, connected to the environmental monitoring center, the UAV operation center, and the maintenance and processing center, for dispatching one or more UAVs, based on the environmental data from each key point within the pipeline, to the vicinity of the key point where a leak is determined to have occurred, to collect thermal images in real time, and, after determining the leak point based on the thermal imaging images, to control the closure of valves near the leak point and the activation of the capture device of the corresponding UAV to cool the leaked carbon dioxide from the leak point. After confirming that the leak at the leak point has been effectively controlled, the UAVs are controlled to stop cooling and notify the maintenance and processing center to arrange repairs to the leak point and recover the cooled carbon dioxide.

[0006] In one embodiment of the present invention, each environmental detection module includes: a pressure sensor for real-time monitoring of pressure changes near the current key point in the pipeline; a temperature sensor for real-time monitoring of temperature changes near the current key point in the pipeline; and a carbon dioxide concentration sensor for real-time monitoring of carbon dioxide concentration near the current key point in the pipeline.

[0007] In one embodiment of the present invention, the data processing and control center includes: a signal center and a data center connected to the signal center; wherein, the data center determines whether there is a leak near a key point based on the environmental data of each key point in the pipeline, and when it is determined that there is a leak near a key point, the signal center dispatches a drone to arrive near the relevant key point to collect thermal imaging images in real time; the data center determines the leakage point based on the thermal imaging image collected by the drone, and the signal center controls the pipeline control system to close the valve near the leakage point and controls the drone to cool the carbon dioxide leaked from the leakage point; after the data center confirms that the leakage at the leakage point is effectively controlled, the signal center controls the drone to stop cooling and notifies the maintenance processing center to repair the leakage point and recycle the cooled carbon dioxide.

[0008] In one embodiment of the present invention, the signal center includes: a data receiving and preprocessing module, which is used to receive the environmental data collected in real time by each environmental detection module, detect and filter the abnormal data, and send the preprocessed normal environmental data to the data center; it is also used to receive thermal imaging images collected in real time by drones, and send the thermal imaging images to the data center; a drone scheduling module, which is used to dispatch one or more drones to arrive at relevant key points to collect thermal imaging images in real time when the data center determines that there is a leak at a key point; an emergency disposal control module, which is used to send an emergency disposal signal after the data center determines the leak point, so as to control the pipeline control system to close the valve near the leak point and control the drone to open the carbon dioxide capture device; a maintenance processing control module, which is used to send a cooling stop control signal to the drone to control the drone to stop cooling after the data center confirms that the leak at the leak point has stopped, and send a maintenance processing signal to the maintenance processing center to control the maintenance processing center to arrange for repair of the leak point and recovery of the cooled carbon dioxide.

[0009] In one embodiment of the present invention, the data center includes: a data storage module for storing normal environmental data and thermal imaging images of each key point sent by the signal center; a leakage judgment module, connected to the data storage module, for judging whether there is a leakage at a key point based on the normal environmental data of each key point based on preset rules, and notifying the signal center when it is judged that there is a leakage at a key point, so as to dispatch a drone to arrive at the relevant key point to collect thermal imaging images in real time; a leakage point identification module, connected to the data storage module, for using a target detection algorithm to analyze the thermal imaging image to identify the leakage point, and notifying the signal center to control the pipeline control system to close the valve near the leakage point and control the corresponding drone to cool the carbon dioxide leaked from the leakage point; a leakage effective control judgment module, for judging whether the leakage at the leakage point is effectively controlled based on the real-time collected environmental data and thermal imaging images, and after judging that it is effectively controlled, notifying the signal center to control the drone to stop cooling and notify the maintenance processing center to repair the leakage point and recycle the cooled carbon dioxide.

[0010] In one embodiment of the present invention, each drone is configured to locate a relevant key point using a GPS module after being dispatched by the signal center, and upon arriving at the key point, to capture the heat source of the leakage point in real time using an infrared camera, generate a thermal imaging image, and transmit the image to the data center; upon receiving an emergency disposal signal from the signal center, the drone activates a carbon dioxide capture device to spray liquid nitrogen at the leakage point, converting the leaked carbon dioxide into liquid or solid carbon dioxide; upon receiving a cooling stop control signal from the signal center, the drone stops spraying and activates a vacuum pump to recover non-gaseous carbon dioxide; wherein the amount of liquid nitrogen sprayed is automatically adjusted based on the size of the leakage and the spraying area.

[0011] In one embodiment of the present invention, the maintenance processing center is used to repair the pipeline and recover the cooled carbon dioxide after receiving the maintenance processing signal from the signal center; it is also used to replace the liquid nitrogen of the carbon dioxide capture device and use an inventory management system to track the use of the carbon dioxide capture device propellant in real time.

[0012] In one embodiment of the present invention, the data center is also used to determine whether the currently scheduled drone has the ability to control the leakage point based on the environmental data and thermal imaging images collected by the drone in real time, and when it is determined that it does not have the control capability, notify the signal center to call other drones for collaborative work.

[0013] In one embodiment of the present invention, the system further includes: a visualization center connected to the data center, for displaying environmental data of key points in the pipeline, drone mission execution status and mission progress through real-time charts, dashboards and heat maps.

[0014] In one embodiment of the present invention, when the signal center determines that leakage occurs at multiple key points at the same time in the data center, the signal center sets priorities according to the severity of the leakage and dispatches drones according to the priority.

[0015] As described above, the present invention is a pipeline transportation carbon dioxide leak detection and capture system with the following beneficial effects: the present invention monitors environmental data in real time by deploying multiple sensors at key nodes of the pipeline, and detects whether a leak occurs based on the monitoring data; once a leak is detected, a drone is immediately dispatched to collect infrared image data for on-site verification, and the leak point is identified based on the infrared image data and the drone is controlled to capture and process the carbon dioxide at the leak point; after confirming that the leak at the leak point is effectively controlled, the maintenance processing center is notified to arrange for repairs to the leak point and the recovery of the cooled carbon dioxide. The present invention can improve the response speed and accuracy of leak detection, reduce manual intervention and false alarms, and can quickly and accurately detect and process leak points, especially in complex environments and large-scale pipeline networks. In addition, the system is also highly flexible and scalable, and can be modified and upgraded according to actual needs, adapting to a variety of operating environments and detection scenarios, and improving pipeline transportation safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Shown is a structural schematic diagram of a pipeline transportation carbon dioxide leakage detection and capture system in one embodiment of the present invention.

[0017] Figure 2 Shown is a structural schematic diagram of a pipeline transportation carbon dioxide leakage detection and capture system in one embodiment of the present invention.

[0018] Figure 3Shown is a schematic diagram of the working process of a pipeline transportation carbon dioxide leakage detection and capture system in one embodiment of the present invention. DETAILED DESCRIPTION

[0019] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0020] It should be noted that in the following description, reference is made to the accompanying drawings, which describe several embodiments of the present invention. It should be understood that other embodiments may be used and that mechanical, structural, electrical and operational changes may be made without departing from the spirit and scope of the present invention. The following detailed description should not be considered restrictive, and the scope of the embodiments of the present invention is limited only by the claims of the published patents. The terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. Spatially related terms, such as "upper", "lower", "left", "right", "below", "below", "lower", "above", "upper", etc., may be used in the text to facilitate the description of the relationship between one element or feature shown in the figure and another element or feature.

[0021] Throughout this specification, when a part is said to be "connected" to another part, this includes not only "direct connection" but also "indirect connection" with other elements interposed therebetween. Furthermore, when a part is said to "include" a certain component, unless otherwise stated, this does not exclude the inclusion of such other components but rather implies that the part may include such other components.

[0022] The terms "first," "second," and "third" are used to describe various parts, components, regions, layers, and / or segments, but are not intended to be limiting. These terms are used solely to distinguish one part, component, region, layer, or segment from another. Therefore, a reference to a first part, component, region, layer, or segment below may also refer to a second part, component, region, layer, or segment without departing from the scope of the present invention.

[0023] Furthermore, as used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It should be further understood that the terms "comprise", "include" indicate the presence of the described features, operations, elements, components, items, kinds, and / or groups, but do not exclude the presence, occurrence, or addition of one or more other features, operations, elements, components, items, kinds, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Thus, "A, B, or C" or "A, B, and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B, and C". Exceptions to this definition occur only when the combination of elements, functions, or operations is inherently mutually exclusive in some way.

[0024] The present invention provides a pipeline transportation carbon dioxide leak detection and capture system. The system deploys multiple sensors at key pipeline nodes to monitor environmental data in real time, and uses the monitoring data to detect leaks. Once a leak is detected, a drone is immediately dispatched to collect infrared image data for on-site verification. The leak point is identified based on the infrared image data, and the drone is controlled to capture and process the carbon dioxide at the leak point. After confirming that the leak at the leak point is effectively controlled, the maintenance processing center is notified to arrange for repairs to the leak point and for the cooled carbon dioxide to be recovered. The present invention can improve the response speed and accuracy of leak detection, reduce manual intervention and false alarms, and can quickly and accurately detect and process leaks, particularly in complex environments and large-scale pipeline networks. Furthermore, the system is highly flexible and scalable, and can be modified and upgraded according to actual needs, adapting to a variety of operating environments and detection scenarios, thereby improving pipeline transportation safety.

[0025] The following is a detailed description of the embodiments of the present invention with reference to the accompanying drawings so that those skilled in the art can easily implement the present invention. The present invention can be embodied in many different forms and is not limited to the embodiments described herein.

[0026] like Figure 1 A schematic structural diagram of a pipeline transport carbon dioxide leakage detection and capture system according to an embodiment of the present invention is shown.

[0027] The system comprises: Environmental Monitoring Center 1 includes environmental monitoring modules installed at key locations within the CO2 transport pipeline, such as elbows, tees, near valves, and at evenly spaced points along the length of the pipeline. These key locations are selected based on the pipeline's structural characteristics and leakage risk assessment to ensure comprehensive coverage of areas where leaks may occur. The environmental monitoring modules are capable of collecting a variety of environmental data in real time, including but not limited to CO2 concentration, temperature, and pressure. Through high-precision sensors, they can accurately capture subtle changes in the environment at key points within the pipeline, providing a reliable basis for subsequent leak detection.

[0028] Drone Work Center 2 includes multiple drones, each equipped with an infrared camera and a CO2 capture device. The drones' infrared cameras feature high-resolution, high-sensitivity designs, enabling clear thermal imaging under varying lighting conditions. The drones' CO2 capture devices, with their efficient cooling and capture capabilities, can quickly cool down leaked CO2.

[0029] Maintenance and processing center 3, used to arrange leak repairs and recycle cooled carbon dioxide; The data processing and control center 4, connected to the environmental monitoring center 1, the drone operation center 2, and the maintenance processing center 3, receives real-time environmental data from each environmental monitoring module. It then uses data analysis algorithms and models to analyze the collected environmental data and determine whether there is a risk of leakage near a critical point within the pipeline. When a potential leak is detected near a critical point, one or more drones are intelligently dispatched to quickly arrive near that critical point to collect real-time thermal imaging images. After accurately identifying the leak point based on the thermal imaging images, a command is sent to the pipeline control system to close the valve near the leak point, preventing further gas leakage. Simultaneously, a command is sent to the corresponding drone to activate the capture device, initiating the CO2 cooling process. The data processing and control center 4 transmits the real-time environmental data and thermal imaging images collected by the drones during the cooling process to the data center. The data center uses real-time environmental data feedback and thermal image analysis to confirm whether the leak at the leak point is effectively controlled. Once the leak is confirmed to be effectively controlled, the drone is promptly controlled to stop the cooling operation, and a notification is sent to the maintenance processing center 3 to recover the cooled CO2 and arrange for maintenance personnel to repair the leak point.

[0030] In one embodiment, each environment detection module includes: a pressure sensor, a temperature sensor, and a carbon dioxide concentration sensor.

[0031] When a pipeline is operating normally, the internal pressure remains within a relatively stable range. However, if an abnormality such as a leak or damage occurs, the pressure balance within the pipeline will be disrupted, causing abnormal fluctuations. Therefore, a pressure sensor is required to monitor pressure changes near key points within the pipeline in real time. This pressure sensor can utilize piezoresistive sensor technology, in which the resistance of the sensing membrane, its core component, changes with pressure. By precisely detecting tiny changes in the sensing membrane's resistance and converting them into a measurable electrical signal, real-time sensing of pressure changes is achieved.

[0032] During normal operation, the temperature inside and around a pipeline remains relatively stable. However, abnormal events such as leaks can cause the temperature around the pipeline to rise or fall abnormally. Therefore, temperature sensors are required to monitor temperature changes near key points within the pipeline in real time. These sensors can be thermocouples or RTDs (resistance temperature detectors). Thermocouples operate based on the thermoelectric effect: when two metals have different temperatures at their junctions in a closed circuit, a thermoelectric potential is generated. The temperature can be determined by measuring this potential. RTD sensors, on the other hand, utilize the temperature-dependent resistance of metals to precisely calculate temperature.

[0033] When a pipeline leak occurs, the carbon dioxide concentration near the leak point typically rises dramatically. Therefore, a carbon dioxide concentration sensor is required to monitor the carbon dioxide concentration near key points within the pipeline in real time. This sensor can utilize non-dispersive infrared (NDIR) sensor technology. NDIR sensors detect gas concentration based on the absorption characteristics of carbon dioxide molecules of specific wavelengths of infrared light. When infrared light passes through a gas sample containing carbon dioxide, the carbon dioxide molecules absorb the specific wavelengths of infrared light. By measuring the intensity change of the unabsorbed infrared light, the carbon dioxide concentration can be accurately calculated.

[0034] Through the collaborative work of pressure sensors, temperature sensors, and carbon dioxide concentration sensors, the environmental monitoring modules provide comprehensive, real-time monitoring of environmental data within the pipeline. By analyzing these data for abnormal changes in the early stages of a leak, the system can identify problems and issue early warnings, buying valuable time for subsequent emergency response, effectively minimizing potential losses and ensuring the safe and stable operation of the pipeline system.

[0035] In one embodiment, the data processing and control center 4 includes: a signal center and a data center connected to the signal center; The signal center receives real-time environmental data from environmental monitoring modules located at key points within the pipeline, ensuring timely understanding of the pipeline's operating environmental status. The data center promptly forwards this environmental data to the data center for analysis and processing, and receives feedback from the data center, including judgments and decision-making recommendations, such as whether a leak has occurred and the location of the leak. Based on the data center's determination of whether a leak has occurred at a key point, the center sends a dispatch instruction to the drone control center, dispatching a drone to the relevant key point to perform a task. The center also receives and forwards data such as the drone's flight status and thermal imaging images back to the data center. The data center identifies the leak point based on the thermal imaging images captured by the drone. The signal center then controls the pipeline control system to close valves near the leak point and control the drone to cool the leaked carbon dioxide. Once the data center confirms that the leak has been effectively controlled based on the real-time environmental data and the thermal imaging images captured by the drone, the signal center controls the drone to stop cooling and sends a maintenance notification to the maintenance processing center 3, informing it of the leak point location, leak status, and measures taken. The center also receives feedback from the maintenance processing center 3 to coordinate subsequent repairs and recovery efforts.

[0036] In one embodiment, the signal center uses the GPS positioning system to select the nearest drone based on the key leak point information identified by the data center. To improve positioning accuracy, differential GPS technology is used to locate and dispatch the drone, ensuring it can quickly and accurately reach the key leak point. The dispatched drone continuously receives satellite signals through its equipped GPS module, accurately determines its own position and the target anomaly location based on geographic coordinates, plans a flight route, and proceeds to the leak point. Upon arriving at the leak point, the drone uses its onboard infrared camera and infrared thermal imaging technology to precisely locate the leak source. The infrared camera captures the heat source at the leak point in real time, generating a thermal image. Regardless of lighting conditions, the thermal image clearly shows the leak area with large temperature differences. The data center analyzes this image to further determine the specific location and size of the leak point. Upon receiving an emergency response signal from the signal center, the drone activates its carbon dioxide capture device. This device uses liquid nitrogen to rapidly cool the area affected by the leak. An automated control system precisely sprays liquid nitrogen to ensure coverage and continuous cooling of the leaked area. The drone automatically adjusts the amount of liquid nitrogen sprayed based on the size of the leak and the area sprayed, converting the leaked carbon dioxide into either liquid or solid form. After receiving the cooling stop control signal from the signal center, the drone stops spraying liquid nitrogen and immediately starts the vacuum pump to recover non-gaseous carbon dioxide and complete the subsequent work of leak disposal.

[0037] In one embodiment, the maintenance and processing center 3 is specifically responsible for arranging repairs on pipelines experiencing carbon dioxide leaks upon receiving maintenance processing signals from the signal center. Equipped with specialized repair tools and equipment, as well as an experienced maintenance team, the maintenance and processing center 3 is capable of implementing effective repair measures for various types of pipeline damage (such as cracks and holes), ensuring the restoration of pipeline integrity and normal operation. The maintenance and processing center 3 is also responsible for collecting, storing, and processing the cooled carbon dioxide recovered by drones for subsequent industrial reuse. The maintenance and processing center 3 includes specialized storage containers, purification equipment, and compression devices, capable of purifying and compressing the recovered carbon dioxide to meet industrial standards, achieving resource recycling and reducing production costs and environmental impact. Furthermore, the maintenance and processing center 3 is responsible for replacing liquid nitrogen in the carbon dioxide capture device and employs an inventory management system to track propellant (liquid nitrogen) usage in real time. This system includes liquid nitrogen storage tanks, delivery pipelines, and refilling equipment, enabling safe and efficient replenishment of liquid nitrogen to the capture device. Furthermore, the inventory management system accurately records the purchase, usage, and remaining quantity of each batch of liquid nitrogen, providing accurate data support for inventory management and procurement decisions.

[0038] In one embodiment, if Figure 2 , the signal center includes: The data reception and preprocessing module establishes a stable communication connection with each environmental monitoring module and receives real-time environmental data such as pressure, temperature, and carbon dioxide concentration via efficient communication protocols such as MQTT or HTTP. MQTT, with its lightweight, low-bandwidth consumption, and publish-subscribe model, is suitable for data transmission in resource-constrained environments. HTTP, on the other hand, offers wide compatibility and ease of debugging. Next, algorithms can be applied to perform preliminary analysis of the received environmental data. For example, filtering algorithms (such as mean and median filters) can be used to remove noise and smooth the data. Anomaly detection algorithms (such as statistical methods and machine learning algorithms) can be used to identify and remove outliers, such as data that significantly deviates from the normal range due to sensor failure or external interference. This allows for the acquisition of normal data at key points and the transmission of this preprocessed normal environmental data to the data center. Alternatively, data transmitted by different environmental monitoring modules can be converted to a format compatible with the data center before analysis to ensure data consistency and compatibility.

[0039] The data receiving and pre-processing module also establishes communication with each drone to receive the thermal imaging image data collected by the drone in real time. These image data are usually transmitted in a specific image format (such as JPEG or PNG) and send the thermal imaging images to the data center.

[0040] The drone dispatch module continuously monitors the data center's leak detection results for key locations. When the data center detects a leak at a key location, it triggers a drone dispatch event through an event-driven architecture (EDA). Using an intelligent dispatch algorithm, the module dispatches one or more drones to the relevant key location to collect thermal images in real time. This intelligent dispatch algorithm comprehensively considers the drone's various status information and mission requirements, optimizing the drone dispatch plan and improving dispatch efficiency and mission execution success rate.

[0041] The emergency response control module receives information from the data center regarding the leak point, including its location and severity. Based on this information, it immediately sends an emergency response signal to the pipeline control system, instructing it to close the valves near the leak point. It also sends an emergency response signal to the corresponding drone, controlling the activation of the carbon dioxide capture device.

[0042] The maintenance control module receives confirmation from the data center that the leak has ceased. It then sends a cooling stop control signal to the drone currently performing the cooling task, causing it to shut down its CO2 capture device and terminate the cooling operation. Based on the location of the leak and the repair requirements, it sends a detailed maintenance signal to the maintenance center 3, including the leak's specific location, leak status, and measures taken. The module then arranges for on-site repairs by maintenance personnel and arranges for the recovery of the cooled CO2.

[0043] In one embodiment, after receiving information on multiple leakage points, the signal center will prioritize each leakage point according to the severity of the leakage. The assessment of the severity of the leakage may take into account multiple factors, such as the rate of gas leakage, the degree of concentration exceeding the standard, the impact of the location of the leakage point on the surrounding environment and facilities, etc. For example, if the gas concentration at a leakage point far exceeds the safety threshold and the leakage rate is fast, then the leakage point will be given a higher priority. According to the set priority, the signal center begins to dispatch drones. It will consider the urgency of the task and the availability of resources, and give priority to assigning drones to the tasks with the highest priority. During the scheduling process, the signal center needs to grasp the status of the drone in real time, including the location of the drone, the remaining power, the task execution status, etc., to ensure that resources can be allocated reasonably and efficiently.

[0044] In one embodiment, if Figure 2 , the data center includes: The data storage module establishes a stable communication connection with the signal center and receives real-time environmental data for key points and drone thermal images from the signal center. An efficient time-series database, such as InfluxDB, is used to store the environmental data for each key point. Time-series databases are specifically optimized for time series data, enabling efficient storage and query of timestamped data to accommodate the time-varying nature of environmental data. During storage, data is organized according to fields such as key point identifiers, data types, and timestamps for rapid retrieval and analysis. A distributed storage system, such as HDFS, is used to manage thermal images from drones. Distributed storage systems offer high scalability, reliability, and throughput, meeting the storage requirements of large-scale image data. Thermal images are sharded and stored according to dimensions such as date and key point area to improve data access efficiency.

[0045] The leak detection module is used to determine whether a leak has occurred at a key point based on pre-set rules and the normal environmental data of each key point. If a leak is detected at a key point, the module notifies the signal center to dispatch a drone to the relevant key point to collect thermal images in real time. Specifically, a series of leak detection rules are set based on historical pipeline operation data and expert experience. For example, if the pressure at a key point suddenly drops above a certain threshold, or if the temperature rises abnormally beyond a set range, the key point is considered to have a leak. The module continuously receives normal environmental data from each key point from the data storage module and analyzes it in real time according to the pre-set rules. Real-time stream processing technologies (such as Apache Flink) are used to rapidly process the data and promptly identify data patterns that meet the leak rules. If a leak is detected at a key point, a leak alert is immediately sent to the signal center, including the key point's identification and location, so that the signal center can dispatch a drone to the relevant key point to collect thermal images.

[0046] The leak point identification module uses an object detection algorithm to analyze thermal images to identify leaks and notify the signal center, which then controls the pipeline control system to close valves near the leak point and control the corresponding drone to cool the leaked CO2. Specifically, it processes the thermal images received from the drone, using image enhancement techniques (such as histogram equalization and contrast enhancement) to improve image quality. Histogram equalization adjusts the image's grayscale distribution and enhances contrast, while contrast enhancement further highlights image details and features, making the leak more visible. Object detection algorithms (such as convolutional neural networks) are used to analyze the preprocessed thermal images to identify leaks. Convolutional neural networks have powerful feature extraction and classification capabilities, automatically learning characteristic patterns in images and accurately detecting the location and size of leaks. If a leak is confirmed, relevant information (such as location and size) is transmitted to the signal center, allowing the pipeline control system to close valves near the leak point and control the corresponding drone to cool the leaked CO2.

[0047] The leak control effectiveness judgment module continuously receives real-time environmental data and thermal imaging images and performs comprehensive data analysis. It determines whether the leak is effectively controlled by monitoring the changing trends in the environmental data and the changes in the characteristics of the leak point in the thermal imaging images. If the leak is effectively controlled, a stop cooling command is immediately sent to the signal center, controlling the drone to stop cooling operations. Simultaneously, the maintenance processing center 3 is notified to arrange for personnel to repair the leak point and recycle the cooled carbon dioxide.

[0048] In one embodiment, the data center is also configured to determine whether the currently scheduled drone is capable of controlling the leak based on real-time environmental data and thermal imaging collected by the drone. This involves a comprehensive consideration of resources such as the drone's remaining battery life, payload capacity, and flight speed, as well as the compatibility of the equipment it carries with the leak type. If the existing drone is unable to complete the task, the data center uses a task mobilization algorithm, taking into account factors such as the leak's size and complexity, the drone's location, and available resources, to assess whether additional drones should be deployed for coordinated operations.

[0049] When collaborative operations are determined to be necessary, multi-UAV collaborative algorithms, such as the ant colony algorithm or particle swarm optimization algorithm, are used to dispatch more UAVs to work together to ensure efficient mission completion. The ant colony algorithm simulates ants foraging, allowing UAVs to automatically select optimal routes and assign tasks using pheromones. The particle swarm optimization algorithm simulates birds foraging, allowing UAVs to optimize task allocation and flight paths through information sharing.

[0050] In one embodiment, if Figure 2The system also includes a visualization center 5, connected to the data center 4, which acquires environmental data such as temperature, pressure, and gas concentration from sensors at key points within the pipeline. Real-time charts (such as line graphs and bar charts) clearly display the changing trends of this data over time, allowing operators to visually determine whether the data fluctuates within a normal range. A dashboard displays the current values ​​of key parameters in intuitive numerical form, allowing operators to quickly understand the real-time environmental conditions within the pipeline. Using infrared thermal images transmitted by drones, the visualization center generates a heat map on a large screen. The heat map uses different colors to represent temperature levels, visually demonstrating the temperature distribution and heat source location of leaks. The heat map allows operators to quickly locate the leak and determine its severity, providing a valuable reference for subsequent repairs.

[0051] The visualization center 5 also displays the status of drone missions. By integrating with the drone's positioning system, the visualization center 5 can display each drone's current flight position on a real-time map. Operators can clearly see the drone's specific location within the pipeline system, understanding its coverage area and flight trajectory. The visualization center 5 displays the type of mission the drone is currently performing (such as inspection, leak detection, etc.) and the mission's progress. When a drone completes a mission, the visualization center 5 promptly updates the mission completion status, indicating whether the mission was successfully completed and providing a relevant mission report. Operators can use the mission completion status to make subsequent work arrangements and decisions.

[0052] In order to better describe the pipeline transportation carbon dioxide leakage detection and capture system, it is now specifically described in conjunction with the following embodiments.

[0053] Example: A pipeline transport carbon dioxide leakage detection and capture system.

[0054] The system includes: an environmental detection center, a signal center, a drone work center, a data center, a maintenance processing center, and a visualization center.

[0055] like Figure 3 The specific implementation process is as follows: Step S01: Install sensors and monitor data in real time. The system first installs various sensors at key pipeline nodes and leak-prone areas, including pressure, temperature, and CO2 concentration sensors. These sensors monitor environmental changes inside and outside the pipeline in real time. Pressure sensors monitor pressure fluctuations within the pipeline, temperature sensors detect ambient temperature changes, and CO2 concentration sensors help detect leaks by measuring CO2 concentration within the pipeline. These sensors transmit the collected data to a signal processing center, generating real-time monitoring data that serves as the basis for subsequent processing.

[0056] Step S02: Data Preprocessing and Anomaly Detection. The signal center is responsible for receiving and analyzing data from sensors. Using efficient data communication protocols, the signal center receives real-time data uploaded by sensors and applies algorithms to denoise, filter, and detect outliers, eliminating abnormal data.

[0057] Step S03: Drone Deployment and Leak Detection. Once the data center identifies a leak risk, the signal center will deploy the drone closest to the leak point. The drone uses differential GPS technology to precisely locate the leak area, ensuring rapid on-site arrival. Upon arrival, it uses infrared thermal imaging to capture the heat source at the leak point in real time, generating a thermal image. This technology effectively identifies the location and scale of gas leaks under varying lighting conditions, enabling the drone to pinpoint the leak point.

[0058] Step S04: Emergency Control and Leak Control. Once the data center confirms the leak point based on the infrared imagery transmitted by the drone, the drone immediately activates the CO2 capture device, converting gaseous CO2 into a liquid or solid form through precise spraying to prevent its spread. The drone automatically adjusts the amount of adsorbent sprayed based on the size of the leak to ensure maximum effectiveness. Simultaneously, the data center instructs the signaling center to urgently close nearby valves to prevent further leakage.

[0059] Step S05: Drone Collaboration and Task Optimization. The data center uses the real-time imagery transmitted by the drones to determine whether a single drone can independently complete the task. If the current drone is unable to resolve the issue independently, the signal center automatically dispatches other nearby drones for coordinated action. A collaborative algorithm coordinates resources between drones to ensure efficient task completion. The coordinated operation of multiple drones can quickly cover a large leak area, improving response efficiency.

[0060] Step S06: Task completion and subsequent processing. Once the data center determines the leak has been fully contained based on real-time environmental data and thermal imaging, the signal center instructs the drone to stop spraying liquid nitrogen and activate the vacuum pump to recover the non-gaseous carbon dioxide. The maintenance and processing center and the visualization center are notified to repair the pipeline, ensuring the leak is completely resolved and preventing future leaks. Simultaneously, the maintenance and processing center places the non-gaseous carbon dioxide in a low-temperature environment for subsequent recovery and reuse, ensuring the propellant maintains its performance. The inventory management system tracks the use, recovery, and replacement of the propellant in real time to ensure the rational use of materials and optimized inventory.

[0061] The pipeline transport carbon dioxide leakage detection and capture system of this embodiment can efficiently respond to leakage incidents, quickly and accurately locate the leakage point, and ensure that the leakage is handled promptly and effectively through drone collaboration and intelligent control systems.

[0062] Compared with the prior art, the present invention has the following advantages: 1. Efficient real-time monitoring and anomaly detection: The present invention uses the environmental monitoring center to monitor the environmental data of key nodes in the transportation pipeline in real time, and uses the efficient data reception and preprocessing technology of the signal processing center to screen and process this data in real time, ensuring the accuracy and effectiveness of the data, and can quickly determine whether there is a leak and issue an early warning.

[0063] 2. Rapid response and task scheduling: The signal center uses an efficient task scheduling algorithm to prioritize the nearest drones to perform tasks and promptly respond to real-time decisions. It can reasonably allocate resources when multiple tasks are running in parallel, optimizing the system's response time and efficiency.

[0064] 3. Accurate Leak Location and CO2 Capture: The drone work center, equipped with a high-precision GPS positioning system and infrared thermal imaging technology, can accurately locate leaks and quickly identify their source. Automatic control algorithms precisely spray liquid nitrogen, ensuring it efficiently covers the leak and continuously converts gaseous CO2 into liquid or solid form. Once the leak is under control, the signaling center instructs the drone to stop spraying and activate a vacuum pump to recover the solid or liquid CO2.

[0065] 4. Flexible multi-UAV collaborative operation: Through the multi-UAV collaborative operation algorithm, the data center can determine whether the existing UAVs can complete the task, and mobilize other UAVs to work together when necessary. This largely ensures the collaborative operation between UAVs, optimizes resource allocation and task execution, and ensures that the task can be completed efficiently even when the leakage point is complex or the task scope is large.

[0066] 5. Carbon dioxide recovery and adsorption reuse: The maintenance and processing center uses efficient liquid nitrogen to convert carbon dioxide into a form technology, which can recover and reuse non-gaseous carbon dioxide, minimizing resource waste.

[0067] 6. Real-time Monitoring and Data Visualization: The visualization center provides intuitive displays of sensor data, thermal images, and drone operating status through real-time charts, dashboards, and heat maps, enabling operators to track the entire system's operations in real time. The visualization center's interactive tools and historical data playback capabilities enhance operator decision-making and response speed, ensuring timely action.

[0068] In summary, the pipeline transportation carbon dioxide leak detection and capture system of the present invention deploys multiple sensors at key pipeline nodes to monitor environmental data in real time. Leaks are detected based on the monitored data. Once a leak is detected, a drone is immediately dispatched to collect infrared image data for on-site verification. The infrared image data identifies the leak point and controls the drone to capture and process the carbon dioxide at the leak point. Once the leak is confirmed to be effectively controlled, the maintenance center is notified to arrange for repairs to the leak point and to recover the cooled carbon dioxide. This system improves the response speed and accuracy of leak detection, reduces manual intervention and false alarms, and enables rapid and accurate detection and resolution of leaks, particularly in complex environments and large-scale pipeline networks. Furthermore, the system is highly flexible and scalable, capable of being modified and upgraded according to actual needs, adapting to a variety of operating environments and detection scenarios, and improving pipeline transportation safety. Therefore, this system effectively overcomes the shortcomings of the existing technology and has high industrial value.

[0069] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, any equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical principles disclosed herein are intended to be covered by the claims of the present invention.

Claims

1. A pipeline transport carbon dioxide leakage detection and capture system, characterized in that: The system comprises: The environmental detection center includes: environmental detection modules arranged at multiple key points in the pipeline, which are used to collect environmental data of each key point in the pipeline in real time; A drone work center, including: multiple drones equipped with infrared cameras and carbon dioxide capture devices, used to collect thermal imaging images through infrared cameras and cool leaked carbon dioxide through carbon dioxide capture devices; A maintenance and processing center to arrange for leak repairs and recycle cooled CO2; The data processing and control center is connected to the environmental detection center, the drone work center and the maintenance processing center. It is used to dispatch one or more drones to the vicinity of the key point where the leak is determined to have occurred based on the environmental data of each key point in the pipeline to collect thermal imaging images in real time. After the leak point is determined based on the thermal imaging image, the data processing and control center controls the closure of the valve near the leak point and controls the corresponding drone to open the capture device to cool the carbon dioxide leaked from the leak point. After confirming that the leakage at the leak point is effectively controlled, the data processing and control center controls the drone to stop cooling and notifies the maintenance processing center to arrange for repair of the leak point and recovery of the cooled carbon dioxide.

2. The pipeline transportation carbon dioxide leakage detection and capture system according to claim 1, characterized in that: Each environmental detection module includes: Pressure sensor, used to monitor the pressure changes near the current key point in the pipeline in real time; Temperature sensor, used to monitor the temperature changes near the current key points in the pipeline in real time; The carbon dioxide concentration sensor is used to monitor the carbon dioxide concentration near the current key point in the pipeline in real time.

3. The pipeline transportation carbon dioxide leakage detection and capture system according to claim 2, characterized in that: The data processing and control center includes: a signal center and a data center connected to the signal center; Among them, the data center determines whether there is a leak near the key point based on the environmental data of each key point in the pipeline, and when it is determined that there is a leak near the key point, the signal center dispatches the drone to arrive near the relevant key point to collect thermal imaging images in real time; the data center determines the leakage point based on the thermal imaging image collected by the drone, and the signal center controls the pipeline control system to close the valve near the leakage point and controls the drone to cool the carbon dioxide leaked from the leakage point; after the data center confirms that the leakage at the leakage point is effectively controlled, the signal center controls the drone to stop cooling and notifies the maintenance processing center to repair the leakage point and recycle the cooled carbon dioxide.

4. The pipeline transportation carbon dioxide leakage detection and capture system according to claim 3, characterized in that: The signal center includes: The data receiving and preprocessing module is used to receive the environmental data collected in real time by each environmental detection module, detect and filter abnormal data, and send the preprocessed normal environmental data to the data center; it is also used to receive thermal imaging images collected in real time by drones and send the thermal imaging images to the data center; A drone dispatching module, configured to dispatch one or more drones to relevant key points to collect thermal imaging images in real time when the data center determines that there is a leak at a key point; An emergency disposal control module, configured to send an emergency disposal signal after the data center determines the leakage point, so as to control the pipeline control system to close the valve near the leakage point and control the drone to open the carbon dioxide capture device; The maintenance processing control module is used to send a cooling stop control signal to the drone to control the drone to stop cooling after the data center confirms that the leakage at the leakage point has stopped, and to send a maintenance processing signal to the maintenance processing center to control the maintenance processing center to arrange for the maintenance of the leakage point and the recovery of the cooled carbon dioxide.

5. The pipeline transportation carbon dioxide leakage detection and capture system according to claim 4, characterized in that: The data center includes: A data storage module, used to store normal environmental data and thermal imaging images of each key point sent by the signal center; a leakage determination module, connected to the data storage module, for determining whether a leakage occurs at any key point based on the normal environmental data of each key point based on preset rules, and notifying the signal center when a leakage occurs at a key point so as to dispatch a drone to the relevant key point to collect thermal imaging images in real time; A leakage point identification module, connected to the data storage module, is used to analyze the thermal imaging image using a target detection algorithm to identify the leakage point and inform the signal center to control the pipeline control system to close the valve near the leakage point and control the corresponding drone to cool the carbon dioxide leaked from the leakage point; The leakage effective control judgment module is used to judge whether the leakage at the leakage point is effectively controlled based on the real-time collected environmental data and thermal imaging images, and after judging that the leakage is effectively controlled, inform the signal center to control the drone to stop cooling and notify the maintenance processing center to repair the leakage point and recycle the cooled carbon dioxide.

6. The pipeline transportation carbon dioxide leakage detection and capture system according to claim 5, characterized in that: Each drone is used to locate the relevant key points through the GPS module after being dispatched by the signal center, and after arriving at the key point, it uses the infrared camera to capture the heat source of the leakage point in real time, generates a thermal imaging image and sends it to the data center; after receiving the emergency disposal signal from the signal center, it starts the carbon dioxide capture device to spray liquid nitrogen at the leakage point, turning the leaked carbon dioxide into liquid or solid carbon dioxide; when receiving the cooling stop control signal sent by the signal center, it stops spraying and starts the vacuum pump to recover non-gaseous carbon dioxide; wherein, the liquid nitrogen spraying amount is automatically adjusted based on the leakage scale and spraying area.

7. The pipeline transportation carbon dioxide leakage detection and capture system according to claim 5, characterized in that: The maintenance processing center is used to repair the pipeline and recover the cooled carbon dioxide after receiving the maintenance processing signal from the signal center; it is also used to replace the liquid nitrogen of the carbon dioxide capture device and use an inventory management system to track the use of the carbon dioxide capture device propellant in real time.

8. The pipeline transportation carbon dioxide leakage detection and capture system according to claim 5, characterized in that: The data center is also used to determine whether the currently scheduled drone has the ability to control the leakage point based on the environmental data and thermal imaging images collected by the drone in real time, and to notify the signal center to call other drones for collaborative work when it is determined that it does not have the control capability.

9. The pipeline transportation carbon dioxide leakage detection and capture system according to claim 1, characterized in that: The system also includes a visualization center connected to the data center, which is used to display environmental data of key points in the pipeline, drone mission execution status and mission progress through real-time charts, dashboards and heat maps.

10. The pipeline transportation carbon dioxide leakage detection and capture system according to claim 5, characterized in that: When the signal center determines that leakage occurs at multiple key points at the same time in the data center, it sets priorities according to the severity of the leakage and dispatches drones according to the priority.

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