Carbon dioxide pipeline leak detection and capture system

Abstract

The present application provides a kind of pipeline transportation carbon dioxide leak detection and capture system, by deploying multiple sensors in the key node of pipeline to monitor environmental data in real time, and when the leakage is detected by monitoring data, immediately dispatch unmanned aerial vehicle to carry out on-site verification, and based on unmanned aerial vehicle infrared image data, identify the leakage point and control unmanned aerial vehicle to carry out carbon dioxide capture processing to the leakage point;After confirming that the leakage point is effectively controlled, inform the maintenance processing center to arrange repair to the leakage point and recover the cooled carbon dioxide.The present application can improve the response speed and accuracy of leak detection, reduce manual intervention and false alarm, especially in complex environment and large-scale pipeline network, can quickly and accurately find the leakage point and process.In addition, the system also has high flexibility and scalability, can be modified and upgraded according to actual needs, adapt to various operating environments and detection scenarios, improve pipeline transportation safety.

Description

TECHNICAL FIELD

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

[0002] Carbon dioxide, as an important greenhouse gas, is widely used in many industrial processes, especially in the oil, gas and chemical industries. At the same time, carbon dioxide is also widely used in carbon capture and storage (CCS) technology to reduce greenhouse gas emissions. Because carbon dioxide has a strong greenhouse effect, its leakage poses a potential threat to the environment and human health, so 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 ways, but due to factors such as pipeline aging, improper operation, external interference, carbon dioxide leakage has become a serious problem. This not only may lead to waste of gas resources, but also may cause serious pollution to the surrounding environment. Because carbon dioxide has the characteristics of colorless and odorless when it leaks, traditional leakage detection methods usually have the problems of delayed response and inaccurate positioning, so it is an urgent need to develop more efficient and accurate carbon dioxide leakage detection technology.

[0003] At present, carbon dioxide leakage detection technology mainly focuses on sensor monitoring, infrared detection, acoustic sensing technology, etc. Sensor technology usually relies on pressure, temperature or gas concentration sensors for real-time monitoring, although these methods can detect signs of leakage to some extent, but due to the limitations of sensor layout range and response speed, it is often difficult to accurately locate the leakage point, and in harsh environments it may cause false positives or false negatives. Infrared technology can detect carbon dioxide leakage through thermal imaging, which has good positioning ability, but it is limited by coverage and environmental interference, often requiring manual intervention and subsequent processing, and has low accuracy and response speed. Acoustic technology detects the vibration and sound wave changes of the pipeline to infer the leakage point, but its accuracy is also easily affected in noisy environments. The existing detection technology has many defects, especially in real-time, accuracy and comprehensiveness, there is still a lot of room for improvement, which makes the current technology unable to meet the growing demand for efficient leakage detection. SUMMARY

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

[0005] To achieve the above object and other related objects, the present application provides a pipeline transportation carbon dioxide leakage detection and capture system, which comprises an environment detection center, an unmanned aerial vehicle working center, a maintenance processing center and a data processing and control center.

[0006] In an embodiment of the present application, each environment detection module comprises a pressure sensor for monitoring the pressure change near the current key point in the pipeline in real time, a temperature sensor for monitoring the temperature change near the current key point in the pipeline in real time, and a carbon dioxide concentration sensor for monitoring the carbon dioxide concentration near the current key point in the pipeline in real time.

[0007] In an embodiment of the present application, the data processing and control center comprises a signal center and a data center connected with the signal center; wherein the data center determines whether there is leakage near a key point based on the environment data of each key point in the pipeline, and when it is determined that there is leakage near a key point, the signal center dispatches an unmanned aerial vehicle to arrive near the relevant key point to collect thermal imaging images in real time; the data center determines the leakage point according to the thermal imaging images collected by the unmanned aerial vehicle, and the signal center controls the pipeline control system to close the valve near the leakage point and controls the unmanned aerial vehicle to cool the carbon dioxide leaked from the leakage point; when the data center confirms that the leakage of the leakage point is effectively controlled, the signal center controls the unmanned aerial vehicle to stop cooling and notifies the maintenance processing center to repair the leakage point and recycle the cooled carbon dioxide.

[0008] In an embodiment of the present application, the signal center comprises: a data receiving and preprocessing module, configured to receive environment data collected by each environment detection module in real time, detect and screen abnormal data, and send normal environment data after preprocessing to the data center; also configured to receive thermal imaging images collected by the unmanned aerial vehicle in real time, and send the thermal imaging images to the data center; an unmanned aerial vehicle scheduling module, configured to schedule one or more unmanned aerial vehicles to arrive at the relevant key point to collect thermal imaging images in real time when the data center determines that there is a leak at the key point; an emergency treatment control module, configured to send an emergency treatment signal to control the pipeline control system to close the valve near the leak point and control the unmanned aerial vehicle to start the carbon dioxide capture device after the data center determines the leak point; a repair processing control module, configured to send a cooling stop control signal to the unmanned aerial vehicle to control the unmanned aerial vehicle to stop cooling and send a maintenance processing signal to the maintenance processing center to control the maintenance processing center to arrange repair of the leak point and recovery of the cooled carbon dioxide after the data center confirms that the leak at the leak point has stopped.

[0009] In an embodiment of the present application, the data center comprises: a data storage module, configured to store normal environment data and thermal imaging images of each key point sent by the signal center; a leak judgment module connected to the data storage module, configured to determine whether there is a leak at the key point based on preset rules according to the normal environment data of each key point, and inform the signal center when a leak at the key point is determined to schedule the unmanned aerial vehicle to arrive at the relevant key point to collect thermal imaging images in real time; a leak point identification module connected to the data storage module, configured to identify the leak point by analyzing the thermal imaging images using a target detection algorithm, and inform the signal center to control the pipeline control system to close the valve near the leak point and control the corresponding unmanned aerial vehicle to cool the carbon dioxide leaked from the leak point; a leak effective control judgment module, configured to determine whether the leak at the leak point is effectively controlled based on the real-time collected environment data and thermal imaging images, and inform the signal center to control the unmanned aerial vehicle to stop cooling and notify the maintenance processing center to repair the leak point and recover the cooled carbon dioxide after determining that the leak is effectively controlled.

[0010] In an embodiment of the present application, each unmanned aerial vehicle is configured to locate the relevant key point by the GPS module after being scheduled by the signal center, capture the heat source of the leak point in real time by the infrared camera after arriving at the key point, generate thermal imaging images and send them to the data center; start the carbon dioxide capture device to spray liquid nitrogen on the leak point after receiving the emergency treatment signal from the signal center, so as to change the leaked carbon dioxide into liquid or solid carbon dioxide; stop spraying and start the vacuum pump to recover the non-gaseous carbon dioxide when receiving the cooling stop control signal sent by the signal center; wherein the amount of liquid nitrogen sprayed is automatically adjusted based on the leakage scale and the spraying area.

[0011] In an embodiment of the present application, 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; and is also used to replace the liquid nitrogen of the carbon dioxide capture device, and uses an inventory management system to track the use of the carbon dioxide capture device in real time.

[0012] In an embodiment of the present application, the data center is also used to determine whether the currently dispatched unmanned aerial vehicle has the ability to control the leakage of the leakage point based on the environmental data and the thermal imaging image collected by the unmanned aerial vehicle in real time, and notify the signal center to call other unmanned aerial vehicles to work cooperatively when it is determined that the unmanned aerial vehicle does not have the ability to control.

[0013] In an embodiment of the present application, the system further comprises a visualization center connected to the data center, used to display the environmental data of each key point in the pipeline, the task execution state of the unmanned aerial vehicle and the task progress through real-time charts, dashboards and heat maps.

[0014] In an embodiment of the present application, the signal center sets priorities according to the severity of the leakage when the data center determines that multiple key points leak at the same time, and dispatches unmanned aerial vehicles according to the priorities.

[0015] As described above, the present application is a pipeline carbon dioxide leakage detection and capture system, which has the following beneficial effects: the present application can monitor environmental data in real time by deploying multiple sensors at key nodes of the pipeline, and detect whether leakage occurs based on the monitoring data; once leakage is detected, an unmanned aerial vehicle is dispatched to collect infrared image data for on-site verification, and the leakage point is identified based on the infrared image data and the unmanned aerial vehicle is controlled to capture and process the carbon dioxide at the leakage point; after confirming that the leakage at the leakage point is effectively controlled, the maintenance processing center is notified to arrange repair of the leakage point and recovery of the cooled carbon dioxide. The present application can improve the response speed and accuracy of leakage detection, reduce manual intervention and false positives, and can quickly and accurately find and process leakage points, especially in complex environments and large-scale pipeline networks. In addition, the system also has high flexibility and scalability, can be modified and upgraded according to actual needs, and is suitable for various operating environments and detection scenarios, improving the safety of pipeline transportation. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 A structure schematic diagram of the pipeline carbon dioxide leakage detection and capture system in an embodiment of the present application is shown.

[0017] Figure 2 A structure schematic diagram of the pipeline carbon dioxide leakage detection and capture system in an embodiment of the present application is shown.

[0018] Figure 3A schematic diagram showing the working flow of the pipeline transportation carbon dioxide leakage detection and capture system according to an embodiment of the present application. DETAILED DESCRIPTION

[0019] Other advantages and benefits of the present application will become apparent to those skilled in the art upon reading the following description with reference to the accompanying drawings. The present application can be implemented or applied in other different embodiments and various modifications or changes can be made to the details without departing from the spirit and scope of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict, if possible.

[0020] It should be noted that in the following description, reference will be made to the accompanying drawings, in which several embodiments of the present application are illustrated. It should be understood that other embodiments can also be used and mechanical, structural, electrical and operational changes can be made without departing from the spirit and scope of the present application. The following detailed description is not to be considered as limiting and the scope of the embodiments of the present application is only limited by the claims of the published patent. The terms used herein are only for describing specific embodiments and are not intended to limit the present application. Spatially relative terms such as "upper", "lower", "left", "right", "below", "under", "bottom", "top", and the like, can be used herein for ease of description of the relationship of one element or feature to another element or feature as illustrated in the figures.

[0021] Throughout the specification, when it is said that a part is "connected" to another part, it includes not only the case of "direct connection" but also the case of "indirect connection" in which other elements are interposed therebetween. In addition, when it is said that a part "includes" a certain constituent element, other constituent elements are not excluded unless specifically stated to the contrary, and it means that other constituent elements can also be included.

[0022] The first, second, and third, etc. terms mentioned therein are used for the purpose of describing various parts, components, regions, layers and / or sections, but are not limited thereto. These terms are only used to distinguish a certain part, component, region, layer or section from other parts, components, regions, layers or sections. Therefore, the first part, component, region, layer or section described below can be referred to as the second part, component, region, layer or section within the scope of the present application.

[0023] Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises", "comprising", "includes" and / or "including", as used herein, specify the presence of stated features, operations, elements, components, items, and / or objects, but do not preclude the presence or addition of one or more other features, operations, elements, components, items, and / or objects. As used herein, the terms "or" and "and / or" are to be interpreted as inclusive, i.e., as meaning one or any combination of the items. 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". An exception to this definition will occur only when a combination of elements, functions, or operations are in some way inherently mutually exclusive.

[0024] The present application provides a pipeline transportation carbon dioxide leakage detection and capture system, which monitors environmental data in real time by deploying multiple sensors at key nodes of the pipeline, and detects whether a leakage occurs based on the monitoring data; once a leakage is detected, a drone is dispatched to collect infrared image data for on-site verification, and the leakage point is identified based on the infrared image data and the drone is controlled to capture and process the carbon dioxide at the leakage point; after confirming that the leakage at the leakage point is effectively controlled, the maintenance processing center is notified to arrange repair of the leakage point and recovery of the cooled carbon dioxide. The present application can improve the response speed and accuracy of leakage detection, reduce manual intervention and false positives, and especially in complex environments and large-scale pipeline networks, can quickly and accurately find and process the leakage point. In addition, the system also has high flexibility and scalability, can be modified and upgraded according to actual needs, and is suitable for various operating environments and detection scenarios, improving pipeline transportation safety.

[0025] The embodiments of the present application will be described in detail below with reference to the accompanying drawings, so that those skilled in the art in the technical field to which the present application pertains can easily implement the present application. The present application can be embodied in various different forms, and is not limited to the embodiments described herein.

[0026] As Figure 1 A structure diagram of a pipeline transportation carbon dioxide leakage detection and capture system in an embodiment of the present application is shown.

[0027] The system comprises:

[0028] The environmental detection center 1 includes environmental detection modules installed at key positions inside the carbon dioxide transportation pipeline, such as near bends, tees, valves, and equidistant points along the length of the pipeline. The selection of these key points is based on the structural characteristics of the pipeline and the risk assessment of leakage, ensuring comprehensive coverage of areas where pipeline leakage may occur. The environmental detection modules have the ability to collect a variety of environmental data in real time, including but not limited to carbon dioxide concentration, temperature, pressure, etc. Through high-precision sensors, subtle changes in the environment at each key point in the pipeline can be accurately captured, providing reliable basis for subsequent leakage judgment.

[0029] The unmanned aerial vehicle working center 2 includes multiple unmanned aerial vehicles equipped with infrared cameras and carbon dioxide capture devices. The infrared cameras on the unmanned aerial vehicles are designed with high resolution and high sensitivity, capable of clearly capturing thermal imaging images under different lighting conditions. The carbon dioxide capture devices on the unmanned aerial vehicles have high cooling and capture capabilities, allowing for rapid cooling and treatment of leaked carbon dioxide.

[0030] The maintenance and treatment center 3 is used to arrange for repair of the leakage point and recovery of the cooled carbon dioxide.

[0031] The data processing and control center 4 connects the environmental detection center 1, the unmanned aerial vehicle working center 2, and the maintenance and treatment center 3, and is used to receive environmental data from each environmental detection module in real time. The data analysis algorithm and model are used to analyze the collected environmental data to determine whether there is a risk of leakage near the key points in the pipeline. When it is determined that there may be a leak near a key point, one or more unmanned aerial vehicles are intelligently dispatched to quickly arrive near the key point to collect thermal imaging images in real time. Based on the thermal imaging images, the leakage point is accurately determined, and instructions are sent to the pipeline control system to close the valve near the leakage point to prevent further gas leakage. At the same time, instructions are sent to the corresponding unmanned aerial vehicle to open the capture device and start the carbon dioxide cooling program. The data processing and control center 4 sends the environmental data and thermal imaging images collected by the unmanned aerial vehicle during the cooling process to the data center, which analyzes the real-time environmental data feedback and thermal imaging images to confirm whether the leakage at the leakage point is effectively controlled. Once it is confirmed that the leakage is effectively controlled, the unmanned aerial vehicle stops the cooling operation, and a notification is sent to the maintenance and treatment center 3 to recover the cooled carbon dioxide and arrange for repair personnel to repair the leakage point.

[0032] In an embodiment, each environmental detection module includes a pressure sensor, a temperature sensor, and a carbon dioxide concentration sensor.

[0033] When the pipeline is in normal operation, the internal pressure will be maintained in a relatively stable range. Once the pipeline has an abnormal situation such as leakage or damage, the pressure balance in the pipeline will be broken, and abnormal fluctuations will occur. Therefore, a pressure sensor needs to be set to monitor the pressure change near the current key point in the pipeline in real time; the pressure sensor can use a piezoresistive sensor technology, and the resistance of the core component sensor film will change with the change of the pressure. By accurately detecting the small change of the resistance of the sensor film and converting it into a measurable electrical signal, the real-time sensing of the pressure change is realized.

[0034] During the normal operation of the pipeline, the temperature of the internal and surrounding environment will remain relatively stable. When an abnormal event such as leakage occurs, it may cause abnormal temperature rise or drop around the pipeline. Therefore, a temperature sensor needs to be set to monitor the temperature change near the current key point in the pipeline in real time; the temperature sensor can use a thermocouple or RTD (Resistance Temperature Detector) sensor. The thermocouple works on the principle of thermoelectric effect, that is, when the temperature of the two junctions is different, a thermoelectric potential will be generated in the closed loop composed of two different metals, and the temperature value can be determined by measuring the thermoelectric potential; the RTD sensor uses the characteristic that the resistance of the metal changes with temperature, and accurately calculates the temperature by measuring the change of the resistance value.

[0035] When the pipeline has a leakage event, the carbon dioxide concentration near the leakage point will usually rise sharply. Therefore, a carbon dioxide concentration sensor needs to be set to monitor the carbon dioxide concentration near the current key point in the pipeline in real time; the carbon dioxide concentration sensor can use a non-dispersive infrared (NDIR) sensor technology. The NDIR sensor detects gas concentration based on the absorption characteristics of carbon dioxide molecules to specific wavelength infrared light. When infrared light passes through a gas sample containing carbon dioxide, carbon dioxide molecules will absorb infrared light of a specific wavelength, and by measuring the change of the intensity of the unabsorbed infrared light, the concentration of carbon dioxide can be accurately calculated.

[0036] Through the cooperative work of the pressure sensor, the temperature sensor and the carbon dioxide concentration sensor, each environmental detection module can monitor the environmental data in the pipeline in real time and comprehensively. The system can analyze the abnormal changes of these data at the early stage of leakage, find problems in time and issue a warning, which can gain valuable time for subsequent emergency treatment, effectively reduce possible losses and ensure the safe and stable operation of the pipeline system.

[0037] In an embodiment, the data processing and control center 4 comprises a signal center and a data center connected with the signal center;

[0038] The signal center receives the environmental data from the environmental detection modules arranged at the key points in the pipeline in real time, ensures that the pipeline operating environment state is known in the first time, and forwards the environmental data to the data center for analysis and processing. The signal center receives the judgment result and decision suggestion fed back by the data center, such as whether a leakage occurs, the position of the leakage point, and the like. According to the judgment result of whether a leakage occurs at the key point judged by the data center, the signal center sends a scheduling instruction to the unmanned aerial vehicle control center, schedules the unmanned aerial vehicle to go to the key point related to the leakage to perform a task, and receives the flight state, thermal imaging image, and the like data returned by the unmanned aerial vehicle and forwards the data to the data center. The data center determines the leakage point according to the thermal imaging image collected by the unmanned aerial vehicle, and the signal center controls the pipeline control system to close the valve near the leakage point and controls the unmanned aerial vehicle to cool the leaked carbon dioxide at the leakage point. After the data center confirms that the leakage at the leakage point is effectively controlled according to the real-time environmental data and the thermal imaging image collected by the unmanned aerial vehicle in real time, the signal center controls the unmanned aerial vehicle to stop cooling and sends a maintenance notification to the maintenance processing center 3, informs the position of the leakage point, the leakage condition, and the measures taken, and receives the feedback of the maintenance processing center 3 to coordinate the subsequent maintenance and recovery work.

[0039] In an embodiment, the signal center screens the closest unmanned aerial vehicle according to the leakage key point information judged by the data center through a GPS positioning system. In order to improve the positioning accuracy, the differential GPS technology is used to position and schedule the unmanned aerial vehicle, so as to ensure that the unmanned aerial vehicle can quickly and accurately arrive at the leakage key point. The scheduled unmanned aerial vehicle continuously receives satellite signals through the equipped GPS module, accurately determines the position of the unmanned aerial vehicle and the target abnormal position according to the geographic coordinates, plans a flight route, and goes to the target abnormal position. After arriving at the leakage point, the unmanned aerial vehicle uses the infrared camera carried thereon to accurately position the leakage source by using the infrared thermal imaging technology. The infrared camera captures the heat source of the leakage point in real time and generates a thermal imaging image. Regardless of the lighting conditions, the thermal imaging image can clearly show the leakage area with large temperature difference. The data center further judges the specific position and size of the leakage point by analyzing the image. When receiving the emergency disposal signal sent by the signal center, the unmanned aerial vehicle starts the carbon dioxide capturing device. The device uses liquid nitrogen to quickly cool the leaked carbon dioxide area, accurately sprays liquid nitrogen through an automatic control system, ensures that the leakage point is covered and the leaked area is continuously cooled. The unmanned aerial vehicle can automatically adjust the liquid nitrogen spraying amount according to the leakage scale and spraying area, and convert the leaked carbon dioxide into liquid or solid carbon dioxide. After receiving the cooling stop control signal from the signal center, the unmanned aerial vehicle stops spraying liquid nitrogen and immediately starts the vacuum pump to recover the non-gaseous carbon dioxide, and completes the subsequent work of leakage disposal.

[0040] In an embodiment, the maintenance processing center 3 is responsible for arranging repair work for pipelines that have leaked carbon dioxide after receiving the maintenance processing signal from the signal center. The maintenance processing center 3 is equipped with professional repair tools and equipment, as well as experienced maintenance teams, which can take effective repair measures for different types of pipeline damage (such as cracks, holes, etc.), to ensure the integrity and normal operation of the pipeline. The maintenance processing center 3 is also responsible for collecting, storing and processing the cooled carbon dioxide recovered by the drones for subsequent industrial reuse. The maintenance processing center 3 includes specialized storage containers, purification equipment and compression devices, which can purify and compress the recovered carbon dioxide to meet industrial use standards, achieve resource recycling, reduce production costs and environmental impact. In addition, the maintenance processing center 3 is also responsible for replacing the liquid nitrogen in the carbon dioxide capture device, and uses an inventory management system to track the use of the propellant (liquid nitrogen) in real time. It contains liquid nitrogen storage tanks, delivery pipelines and filling equipment, which can safely and efficiently replenish new liquid nitrogen for the capture device. At the same time, the inventory management system can accurately record the purchase, use and remaining quantity of each batch of liquid nitrogen, providing accurate data support for inventory management and procurement decisions.

[0041] In an embodiment, as Figure 2 , the signal center includes:

[0042] The data receiving and preprocessing module establishes stable communication connection with each environmental detection module, and receives pressure, temperature, carbon dioxide concentration and other environmental data in real time through efficient communication protocols (such as MQTT or HTTP protocol). The MQTT protocol has the characteristics of lightweight, low bandwidth consumption and publish / subscribe mode, which is suitable for data transmission in resource-constrained environments; the HTTP protocol has the advantages of wide compatibility and easy debugging. Next, algorithms can be used to preliminarily analyze the received environmental data. For example, filtering algorithms (such as mean filtering, median filtering) are used to remove noise interference in the data, making the data smoother; anomaly detection algorithms (such as statistical-based methods, machine learning algorithms) are used to identify and eliminate outliers in the data, such as data that deviates significantly from the normal range due to sensor failure or external interference, to obtain normal data at each key point, and send the preprocessed normal environmental data to the data center. It can also be analyzed that the data format transmitted by different environmental detection modules is uniformly converted to a format that the data center can process, to ensure the consistency and compatibility of the data.

[0043] The data receiving and preprocessing module also communicates 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 the thermal imaging images are sent to the data center.

[0044] The UAV scheduling module continuously monitors the judgment results about key point leakage sent by the data center. When the data center judges that there is leakage at a key point, it can trigger a UAV scheduling event through the event-driven architecture (EDA), and use an intelligent scheduling algorithm to schedule one or more UAVs to arrive at the relevant key point to collect thermal imaging images in real time. Using the intelligent scheduling algorithm, various state information of the UAV and task requirements are considered comprehensively to optimize the scheduling scheme of the UAV and improve the scheduling efficiency and task execution success rate.

[0045] The emergency treatment control module receives information about the determination of the leakage point sent by the data center, including the location of the leakage point, the leakage degree, etc. According to the leakage point information, an emergency treatment signal is immediately sent to the pipeline control system to control the pipeline control system to close the valve near the leakage point, and an emergency treatment signal is sent to the corresponding UAV to control the opening of the carbon dioxide capture device.

[0046] The repair processing control module receives confirmation information about the leakage stop of the leakage point sent by the data center. A cooling stop control signal is sent to the UAV that is executing the cooling task, and the UAV closes the carbon dioxide capture device to end the cooling operation. According to the location of the leakage point and the repair requirements, a detailed repair processing signal is sent to the maintenance processing center 3, including information such as the specific location of the leakage point, the leakage situation, and the measures taken, to arrange repair personnel to go to the scene for repair, and to arrange for the recovery of the cooled carbon dioxide.

[0047] In an embodiment, after receiving the information of multiple leakage points, the signal center prioritizes each leakage point according to the severity of the leakage. The assessment of the severity of the leakage may consider 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 of a certain leakage point far exceeds the safety threshold and the leakage rate is fast, the leakage point will be given a higher priority. According to the set priority, the signal center starts to schedule the UAV. It will consider the urgency of the task and the availability of resources, and prioritize the allocation of UAVs for the highest priority task. During the scheduling process, the signal center needs to real-time master the state of the UAV, including the location of the UAV, the remaining power, the task execution situation, etc., to ensure that resources can be reasonably and efficiently allocated.

[0048] In an embodiment, as Figure 2 , the data center includes:

[0049] The data storage module establishes a stable communication connection with the signal center and receives normal environment data of each key point and thermal imaging images of the unmanned aerial vehicle sent by the signal center in real time. An efficient time series database (such as InfluxDB) is used to store the normal environment data of each key point. The time series database is optimized for time series data and can efficiently store and query data with timestamps, meeting the characteristics of environment data changing over time. When storing, the data is organized according to fields such as key point identification, data type and timestamp, so as to quickly retrieve and analyze. A distributed storage system (such as HDFS) is used to manage thermal imaging images from the unmanned aerial vehicle. The distributed storage system has the characteristics of high scalability, high reliability and high throughput, and can meet the storage needs of large-scale image data. The thermal imaging images are stored in slices according to date, key point area and other dimensions to improve data access efficiency.

[0050] The leakage judgment module is used to judge whether there is leakage at each key point based on the preset rules according to the normal environment data of each key point, and to inform the signal center to dispatch the unmanned aerial vehicle to arrive at the relevant key point to collect the thermal imaging image in real time when it is judged that there is leakage at the key point. Specifically, a series of rules for judging leakage are set according to the historical data of pipeline operation and expert experience. For example, when the pressure of a certain key point suddenly drops more than a certain threshold or the temperature abnormally rises more than a certain range, it is determined that the key point may have a leak. The normal environment data of each key point in the data storage module is continuously received and analyzed in real time according to the set rules. Real-time stream processing technology (such as Apache Flink) is used to quickly process the data and timely discover data patterns that meet the leakage rules. When it is judged that there is leakage at the key point, leakage alarm information including the identification, location and other information of the leakage key point is immediately sent to the signal center, so that the signal center can dispatch the unmanned aerial vehicle to the relevant key point to collect the thermal imaging image.

[0051] A leak point identification module is configured to analyze the thermal imaging images using a target detection algorithm to identify the leak point and inform the signal center to control the pipeline control system to close the valves near the leak point and control the corresponding UAV to cool the leaked carbon dioxide at the leak point. Specifically, the received thermal imaging images of the UAV are processed, and a graph enhancement technique (such as histogram equalization and contrast enhancement) is used to improve the image quality. Histogram equalization can adjust the gray scale distribution of the image and enhance the contrast of the image; contrast enhancement can further highlight the details and features in the image, making the leak point more obvious. A target detection algorithm (such as a convolutional neural network) is used to analyze the preprocessed thermal imaging images to identify the leak point in the image. The convolutional neural network has strong feature extraction and classification capabilities, can automatically learn the feature patterns in the image, and accurately detects the location and size of the leak point. If a leak is determined, the signal center is informed of the relevant information (such as location, size, etc.) of the leak point so that the signal center can control the pipeline control system to close the valves near the leak point and control the corresponding UAV to cool the leaked carbon dioxide at the leak point.

[0052] A leak effective control judgment module is configured to continuously receive the real-time collected environmental data and thermal imaging images, and comprehensively analyze the data. By monitoring the trend of the environmental data and the characteristic changes of the leak point in the thermal imaging images, it is determined whether the leak is effectively controlled. If it is determined that the leak at the leak point is effectively controlled, a stop cooling instruction is immediately sent to the signal center to control the UAV to stop the cooling operation. At the same time, the maintenance processing center 3 is notified to arrange personnel to repair the leak point, and the cooled carbon dioxide is recovered.

[0053] In an embodiment, the data center is also configured to determine whether the currently dispatched UAV has the ability to control the leak at the leak point based on the environmental data and thermal imaging images collected by the UAV in real time; this involves a comprehensive consideration of the resource status of the UAV, such as the remaining power, load capacity, and flight speed, as well as the matching degree of the equipment carried by the UAV and the leak type. If the existing UAV cannot complete the task, the data center will use a task mobilization algorithm to evaluate whether other UAVs need to be called to work together, taking into account factors such as the size and complexity of the leak point, the location and state of the UAV, and available resources.

[0054] When it is determined that collaborative work is needed, a multi-UAV collaborative work algorithm, such as an ant colony algorithm or a particle swarm optimization algorithm, is used to dispatch more UAVs to work together to ensure efficient completion of the task. The ant colony algorithm simulates ants foraging, allowing UAVs to automatically select the optimal path and task allocation guided by pheromones; the particle swarm optimization algorithm simulates bird foraging, allowing UAVs to optimize task allocation and flight paths through information sharing.

[0055] In an embodiment, as Figure 2The system also includes a visualization center 5 connected to the data center 4, which obtains environmental data such as temperature, pressure, and gas concentration from sensors at key points in the pipeline. Real-time charts (such as line graphs, bar charts, etc.) are used to clearly show the trend of these data over time, and operators can visually see whether the data is within the normal range. The dashboard displays the current value of the key parameters in a visual form, allowing operators to quickly understand the real-time environmental conditions in the pipeline. With the help of infrared thermal imaging maps returned by the UAV, the visualization center generates a heat map on the large screen. The heat map uses different colors to represent the temperature, which can visually show the temperature distribution and heat source location of the leakage point. Operators can quickly locate the leakage area and judge the severity of the leakage based on the heat map, providing important reference for subsequent maintenance work.

[0056] The visualization center 5 also displays the UAV task status. By integrating with the positioning system of the UAV, the visualization center 5 can display the current flight position of each UAV on the map in real time. Operators can clearly see the specific location of the UAV in the pipeline system and understand its coverage and flight trajectory. The visualization center 5 displays the type of task being performed by the UAV (such as inspection, leakage detection, etc.) and the progress of the task. When the UAV completes the task, the visualization center 5 updates the task completion status in time, showing whether the task is successfully completed and the related task report. Operators can make subsequent work arrangements and decisions based on the task completion.

[0057] In order to better describe the carbon dioxide leakage detection and capture system for pipeline transportation, the following embodiments are combined for specific description.

[0058] Embodiment: A carbon dioxide leakage detection and capture system for pipeline transportation.

[0059] The system includes an environmental detection center, a signal center, a UAV operation center, a data center, a maintenance and processing center, and a visualization center.

[0060] As Figure 3 The specific implementation process is as follows:

[0061] Step S01: Install sensors and monitor data in real time. The system first installs various sensors at key nodes and places prone to leakage in the pipeline, including pressure, temperature, and carbon dioxide concentration sensors. These sensors monitor the environmental changes inside and outside the pipeline in real time. The pressure sensor monitors the pressure fluctuations inside the pipeline, the temperature sensor detects the temperature changes in the environment, and the carbon dioxide concentration sensor helps detect leakage by measuring the carbon dioxide concentration in the pipeline. These sensors transmit the collected data to the signal center to form real-time monitoring data as the basis for subsequent processing.

[0062] Step S02: Data preprocessing and anomaly detection. The signal center is responsible for receiving data from sensors and conducting analysis. The signal center receives real-time data uploaded by sensors using efficient data communication protocols, and uses algorithms to denoise, filter and detect outliers in the data, filtering out abnormal data.

[0063] Step S03: UAV deployment and leak detection. Once the data center determines that there is a risk of leakage, the signal center will mobilize the nearest UAV to handle the situation. The UAV uses differential GPS technology to accurately locate the leak area, ensuring that it can quickly reach the scene. Upon arrival, it uses infrared thermal imaging technology to capture the heat source of the leak point in real time, generating thermal images. This technology can effectively identify the location and scale of gas leaks under different lighting conditions, helping the UAV accurately determine the leak point.

[0064] Step S04: Emergency control and leak control. After the data center confirms the leak point based on the infrared images transmitted by the UAV, the UAV will immediately activate the carbon dioxide capture device to convert gaseous carbon dioxide into liquid or solid form to prevent gas diffusion. The UAV automatically adjusts the amount of adsorbent sprayed based on the scale of the leak to ensure maximum efficiency. At the same time, the data center will instruct the signal center to urgently close the valves near the leak to prevent further leakage.

[0065] Step S05: UAV coordination and task optimization. The data center will determine whether a single UAV can complete the task independently based on the images transmitted by the UAV in real time. If the current UAV cannot solve the problem alone, it will automatically dispatch other nearby UAVs to work together. UAVs coordinate with each other through collaborative algorithms to ensure efficient task completion. The coordinated work of multiple UAVs can quickly cover a large area of the leak area, improving response efficiency.

[0066] Step S06: Task completion and subsequent processing. When the data center determines that the leak has been completely controlled based on real-time environmental data and thermal images, the signal center will instruct the UAV to stop spraying liquid nitrogen and start the vacuum pump to recover non-gaseous carbon dioxide. The maintenance and processing center and the visualization center will repair the pipeline to ensure that the leakage problem is completely solved and future leakage events are prevented. At the same time, the maintenance and processing center will place non-gaseous carbon dioxide in a low-temperature environment for subsequent recovery and reuse, and ensure that the performance of the spray agent remains good. The use, recovery and replacement of spray agents will be tracked in real time by the inventory management system to ensure rational use of materials and optimization of inventory.

[0067] The pipeline transportation carbon dioxide leakage detection and capture system of the embodiment can efficiently respond to leakage events, quickly and accurately locate the leakage point, and ensure that the leakage is timely and effectively handled through the cooperation of unmanned aerial vehicles and the intelligent control system.

[0068] Compared with the prior art, the present application has the following advantages:

[0069] 1. Efficient real-time monitoring and anomaly detection: The present application monitors the environmental data of key nodes in the transportation pipeline through the environmental detection center, and uses efficient data reception and preprocessing technology in the signal processing center to real-time filter and process these data, ensuring the accuracy and effectiveness of the data, and quickly determining whether there is a leak and issuing a warning.

[0070] 2. Fast response and task scheduling: The signal center uses an efficient task scheduling algorithm to prioritize the nearest unmanned aerial vehicle to execute the task, and timely reflects real-time decisions, reasonably allocates resources, and optimizes the response time and efficiency of the system when multiple tasks are parallel.

[0071] 3. Precise leak location and carbon dioxide capture: The unmanned aerial vehicle working center can accurately locate the leakage point and quickly identify the source of the leak by using high-precision GPS positioning systems and infrared thermal imaging technology. Using automatic control algorithms to accurately spray liquid nitrogen ensures that liquid nitrogen can efficiently cover the leakage point and continuously convert gaseous carbon dioxide into liquid or solid. After the leakage is controlled, the signal center will instruct the unmanned aerial vehicle to stop spraying and start the vacuum pump to recover the solid or liquid carbon dioxide.

[0072] 4. Flexible multi-unmanned aerial vehicle cooperative operation: Through the multi-unmanned aerial vehicle cooperative operation algorithm, the data center can determine whether the existing unmanned aerial vehicle can complete the task, and if necessary, mobilize other unmanned aerial vehicles to work together, greatly ensuring the cooperative operation between unmanned aerial vehicles, optimizing the allocation of resources and the execution of tasks, and ensuring that the task can be efficiently completed in the case of complex leakage points or large task ranges.

[0073] 5. Carbon dioxide recovery and adsorption reuse: The maintenance and treatment center can recover and reuse non-gaseous carbon dioxide through efficient liquid nitrogen conversion carbon dioxide form technology, minimizing resource waste.

[0074] 6. Real-time monitoring and data visualization: The visualization center visually displays sensor data, thermal imaging maps, and unmanned aerial vehicle working status through real-time charts, dashboards, and heat maps, allowing operators to track the entire system's operation in real time. The interactive tools and historical data playback function of the visualization center enhance the decision-making ability and response speed of the operators, ensuring that necessary actions are taken in a timely manner.

[0075] In summary, the pipeline transportation carbon dioxide leakage detection and capture system of the present application, by deploying multiple sensors in key nodes of the pipeline to monitor environmental data in real time, and detecting whether leakage occurs from the monitoring data; once the leakage is detected, the unmanned aerial vehicle is immediately dispatched to collect infrared image data for on-site verification, and based on the infrared image data, the leakage point is identified and the unmanned aerial vehicle is controlled to capture and process the carbon dioxide at the leakage point; after confirming that the leakage at the leakage point is effectively controlled, the maintenance processing center is notified to arrange for repair of the leakage point and recovery of the cooled carbon dioxide. The present application can improve the response speed and accuracy of leakage detection, reduce manual intervention and false positives, especially in complex environments and large-scale pipeline networks, it can quickly and accurately find the leakage point and process it. In addition, the system also has high flexibility and scalability, can be modified and upgraded according to actual needs, suitable for various operating environments and detection scenarios, and improve the safety of pipeline transportation. Therefore, the present application effectively overcomes the shortcomings of the prior art and has high industrial utilization value.

[0076] The above embodiments only exemplarily illustrate the principles and effects of the present application, and are not intended to limit the present application. Any person skilled in the art can modify or change the above embodiments without departing from the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by those skilled in the art without departing from the spirit and technical idea disclosed by the present application shall be covered by the claims of the present application.

Claims

1. A pipeline transport carbon dioxide leak detection and capture system, characterized by, The system comprises: an environment detection center comprising environment detection modules arranged at multiple key points in the pipeline respectively, for collecting environment data of the key points in the pipeline in real time; a UAV working center comprising multiple UAVs carrying infrared cameras and carbon dioxide capturing devices, for collecting thermal imaging images through the infrared cameras and cooling the leaked carbon dioxide through the carbon dioxide capturing devices; a maintenance processing center for arranging repair of the leakage point and recovery of the cooled carbon dioxide; a data processing and control center connected to the environment detection center, the UAV working center and the maintenance processing center, for dispatching one or more UAVs to the vicinity of the key point where leakage is determined to occur based on the environment data of the key points in the pipeline to collect thermal imaging images in real time, and for controlling the valve near the leakage point to be closed and the carbon dioxide capturing device of the corresponding UAV to be turned on to cool the leaked carbon dioxide at the leakage point based on the thermal imaging images, and for controlling the UAV to stop cooling and notifying the maintenance processing center to arrange repair of the leakage point and recovery of the cooled carbon dioxide after confirming that the leakage at the leakage point is effectively controlled.

2. The pipeline transport carbon dioxide leak detection and capture system of claim 1, wherein, Each environment detection module comprises: a pressure sensor for monitoring pressure change near the current key point in the pipeline in real time; a temperature sensor for monitoring temperature change near the current key point in the pipeline in real time; a carbon dioxide concentration sensor for monitoring carbon dioxide concentration near the current key point in the pipeline in real time.

3. The pipeline transport carbon dioxide leak detection and capture system of claim 2, wherein, The data processing and control center comprises a signal center and a data center connected to the signal center; wherein the data center determines whether leakage occurs near a key point based on the environment data of the key points in the pipeline, and dispatches a UAV to the vicinity of the relevant key point to collect thermal imaging images in real time when leakage near a key point is determined; the data center determines the leakage point based on the thermal imaging images collected by the UAV, and the signal center controls the pipeline control system to close the valve near the leakage point and controls the UAV to cool the leaked carbon dioxide at the leakage point; the signal center controls the UAV to stop cooling and notifies the maintenance processing center to repair the leakage point and recover the cooled carbon dioxide after the data center confirms that the leakage at the leakage point is effectively controlled.

4. The pipeline transport carbon dioxide leak detection and capture system of claim 3, wherein, The signal center comprises: a data receiving and preprocessing module for receiving the environment data collected by each environment detection module in real time, detecting and screening abnormal data, and sending the preprocessed normal environment data to the data center; and for receiving the thermal imaging images collected by the UAV in real time and sending the thermal imaging images to the data center; a UAV dispatching module for dispatching one or more UAVs to the relevant key point to collect thermal imaging images in real time when the data center determines that a key point leaks; an emergency disposal control module for sending an emergency disposal signal to control the pipeline control system to close the valve near the leakage point and control the UAV to turn on the carbon dioxide capturing device after the data center determines the leakage point. The maintenance treatment control module is configured to send a cooling stop control signal to the unmanned aerial vehicle to control the unmanned aerial vehicle to stop cooling and send a maintenance treatment signal to the maintenance treatment center to control the maintenance treatment center to arrange maintenance of the leakage point and recovery of the cooled carbon dioxide after the data center confirms that the leakage of the leakage point stops.

5. The pipeline transport carbon dioxide leak detection and capture system of claim 4, wherein, The data center comprises: A data storage module configured to store normal environment data of each key point and thermal imaging images sent by the signal center; A leakage judgment module connected to the data storage module and configured to judge whether a key point leaks based on preset rules according to the normal environment data of each key point and inform the signal center when it is judged that a key point leaks to dispatch an unmanned aerial vehicle to arrive at the relevant key point to collect a thermal imaging image in real time; A leakage point identification module connected to the data storage module and configured to identify a leakage point by analyzing the thermal imaging image using a target detection algorithm and inform the signal center to control the pipeline control system to close a valve near the leakage point and control the corresponding unmanned aerial vehicle to cool the leaked carbon dioxide of the leakage point; A leakage effective control judgment module configured to judge whether the leakage of the leakage point is effectively controlled based on the real-time collected environment data and thermal imaging images and inform the signal center to control the unmanned aerial vehicle to stop cooling and notify the maintenance treatment center to maintain the leakage point and recover the cooled carbon dioxide after it is judged that the leakage is effectively controlled.

6. The pipeline transport carbon dioxide leak detection and capture system of claim 5, wherein, Each unmanned aerial vehicle is configured to locate a relevant key point by a GPS module after being dispatched by the signal center, capture a heat source of a leakage point in real time by an infrared camera after arriving at the key point, generate a thermal imaging image and send it to the data center, start a carbon dioxide capturing device to spray liquid nitrogen on the leakage point to change the leaked carbon dioxide into liquid or solid carbon dioxide after receiving an emergency treatment signal from the signal center, stop spraying and start a vacuum pump to recover the non-gaseous carbon dioxide when receiving a cooling stop control signal sent by the signal center, and automatically adjust the amount of liquid nitrogen spraying based on the leakage scale and spraying area.

7. The pipeline transport carbon dioxide leak detection and capture system of claim 5, wherein, The maintenance treatment center is configured to repair the pipeline and recover the cooled carbon dioxide after receiving a maintenance treatment signal from the signal center, and also configured to replace liquid nitrogen of the carbon dioxide capturing device and use an inventory management system to track the use of the spraying agent of the carbon dioxide capturing device in real time.

8. The pipeline transport carbon dioxide leak detection and capture system of claim 5, wherein, The data center is also configured to judge whether the currently dispatched unmanned aerial vehicle has the ability to control the leakage of the leakage point based on the real-time collected environment data and thermal imaging images of the unmanned aerial vehicle and notify the signal center to call other unmanned aerial vehicles to work cooperatively when it is judged that the unmanned aerial vehicle does not have the ability to control the leakage.

9. The pipeline transport carbon dioxide leak detection and capture system of claim 1, wherein, The system further comprises a visualization center connected to the data center and configured to display environment data of each key point in the pipeline, task execution status and task progress of the unmanned aerial vehicle through real-time charts, dashboards and heat maps.

10. The pipeline transport carbon dioxide leak detection and capture system of claim 5, wherein, The signal center sets priorities according to the severity of the leakage and dispatches unmanned aerial vehicles according to the priorities when the data center judges that multiple key points leak at the same time.

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