Carbon dioxide transmission pipeline early warning method and device based on optical cable temperature difference monitoring

Abstract

This application provides a method and device for early warning of carbon dioxide transmission pipelines based on optical fiber cable temperature difference monitoring, relating to the safety monitoring of carbon dioxide transportation. The method includes: acquiring raw temperature data from various monitoring points along the entire section of the carbon dioxide transmission pipeline collected by a distributed optical fiber sensing cable; processing the raw temperature data using an adaptive filtering algorithm to determine a temperature difference dataset; determining the difference between the measured temperature difference value at each monitoring point and a reference temperature difference value based on the measured temperature difference value in the temperature difference dataset, and defining this difference as the real-time temperature difference deviation value for the corresponding monitoring point; comparing the real-time temperature difference deviation value of each monitoring point with the segmented alarm threshold configured for the corresponding section; and based on the comparison results, determining the leakage event and leakage level through a secondary verification mechanism, generating and issuing early warning information. This application can accurately capture the initial temperature difference changes in pipeline leaks, improving the accuracy and timeliness of early warnings, and effectively ensuring the safety of carbon dioxide pipeline transportation.

Description

Technical Field

[0001] This application relates to the field of carbon dioxide transportation safety monitoring, and more specifically, to a method and device for early warning of carbon dioxide transmission pipelines based on optical cable temperature difference monitoring. Background Technology

[0002] Carbon dioxide transmission pipelines are core facilities in carbon capture, utilization, and storage (CCLS) and industrial gas transportation systems, and their operational safety directly impacts environmental and production safety. Existing methods for detecting leaks in carbon dioxide transmission pipelines have significant technical shortcomings. In the early stages of a leak, the small diffusion range of the medium and the slight temperature change make it difficult to detect quickly. Traditional detection methods are slow to respond and cannot accurately capture early leaks by observing temperature differences between the pipeline and the surrounding environment, easily leading to an escalation of the leak risk. Some temperature difference monitoring schemes use fixed thresholds and single data processing modes, resulting in weak anti-interference capabilities and susceptibility to environmental temperature changes, pipeline vibration, and other factors, leading to poor detection accuracy and failing to meet the need for leak early warning across the entire pipeline route, around the clock. Summary of the Invention

[0003] The purpose of this application is to provide a method and device for early warning of carbon dioxide transmission pipelines based on optical fiber temperature difference monitoring, which solves the above-mentioned problems in the prior art, improves the accuracy and response speed of initial identification of carbon dioxide pipeline leaks, has strong anti-interference ability, effectively avoids the expansion of leakage risk, and provides reliable protection for the safe operation of pipelines.

[0004] Firstly, a method for early warning of carbon dioxide transmission pipelines based on optical fiber temperature difference monitoring is provided, which may include: Acquire raw temperature data from all monitoring points along the entire route of the carbon dioxide transmission pipeline collected by the distributed fiber optic sensing cable. An adaptive filtering algorithm is used to process the raw temperature data to determine the temperature difference dataset; Based on the temperature difference measurement value of each monitoring point in the temperature difference dataset, the difference between the temperature difference measurement value of the same monitoring point and the reference temperature difference value is determined, and the difference is determined as the real-time temperature difference deviation value of the corresponding monitoring point; wherein, the reference temperature difference value is determined based on the target temperature data of the carbon dioxide transmission pipeline under normal transportation conditions; The real-time temperature difference deviation value of each monitoring point is compared with the segmented alarm threshold configured for the corresponding road section. Based on the comparison results, a secondary verification mechanism is used to determine the leakage event and leakage level, and early warning information is generated and issued.

[0005] In one possible implementation, the raw temperature data includes the pipe outer wall temperature data corresponding to each monitoring point and the ambient temperature data around the pipe.

[0006] In one possible implementation, the configuration process for the segmented alarm thresholds includes: Based on the physical properties of carbon dioxide, pipeline operating parameters, and environmental factors, the segmental alarm thresholds for the relevant road sections are determined.

[0007] In one possible implementation, the segmented alarm threshold is further configured with an adaptive correction coefficient; Based on the adaptive correction coefficient and the ambient temperature around the pipeline, the reference temperature difference value of the corresponding road segment is corrected to obtain the corrected segmented alarm threshold.

[0008] In one possible implementation, the secondary verification mechanism includes: when the real-time temperature difference deviation value of any monitoring point reaches or exceeds the corresponding segmented alarm threshold, the effective temperature difference measurement values ​​of the monitoring point and multiple adjacent monitoring points are continuously collected within a preset time period, and the corresponding real-time temperature difference deviation value is calculated. If all threshold conditions are met or the real-time temperature difference deviation value of the monitoring point continues to rise, a leakage event is determined to exist.

[0009] In one possible implementation, the leakage level is divided based on the magnitude and diffusion rate of the real-time temperature difference deviation value exceeding the segmented alarm threshold, with different leakage levels corresponding to different ranges of temperature difference deviation magnitude and diffusion rate.

[0010] In one possible implementation, the early warning information includes the leak location, real-time temperature difference deviation value, leak level, and handling suggestions, and is released through local audible and visual alarms and remote platform push notifications.

[0011] Secondly, a carbon dioxide transmission pipeline early warning device based on optical cable temperature difference monitoring is provided, the device may include: The acquisition unit is used to acquire the raw temperature data of each monitoring point along the entire route of the carbon dioxide transmission pipeline collected by the distributed optical fiber sensing cable. The processing unit is used to process the raw temperature data using an adaptive filtering algorithm to determine the temperature difference dataset; The determining unit is used to determine the difference between the temperature difference measurement value of the same monitoring point and the reference temperature difference value based on the temperature difference measurement value of each monitoring point in the temperature difference dataset, and to determine the difference as the real-time temperature difference deviation value of the corresponding monitoring point; wherein, the reference temperature difference value is determined based on the target temperature data of the carbon dioxide transmission pipeline under normal transportation conditions; The comparison unit is used to compare the real-time temperature difference deviation value of each monitoring point with the segmented alarm threshold configured for the corresponding road section. Based on the comparison results, the leakage event and leakage level are determined through a secondary verification mechanism, and early warning information is generated and issued.

[0012] Thirdly, an electronic device is provided, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in memory, it implements any of the steps described in the first aspect above.

[0013] Fourthly, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the steps of any of the methods described in the first aspect above.

[0014] This application provides a method and device for early warning of carbon dioxide transmission pipelines based on optical fiber cable temperature difference monitoring. The method includes: acquiring raw temperature data from each monitoring point along the entire section of the carbon dioxide transmission pipeline collected by a distributed optical fiber sensing cable; processing the raw temperature data using an adaptive filtering algorithm to determine a temperature difference dataset; determining the difference between the measured temperature difference value of each monitoring point and a reference temperature difference value based on the temperature difference measurement value of each monitoring point in the temperature difference dataset, and defining the difference as the real-time temperature difference deviation value of the corresponding monitoring point; comparing the real-time temperature difference deviation value of each monitoring point with the segmented alarm threshold configured for the corresponding section, and based on the comparison result, determining the leakage event and leakage level through a secondary verification mechanism, generating and issuing early warning information. This application can accurately capture the initial temperature difference changes in pipeline leakage, improve the accuracy and timeliness of early warning, and effectively ensure the safety of carbon dioxide pipeline transportation. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating an early warning method for carbon dioxide transmission pipelines based on optical cable temperature difference monitoring, provided in an embodiment of this application; Figure 2 A schematic diagram of a carbon dioxide transmission pipeline early warning device based on optical cable temperature difference monitoring provided in this application embodiment; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0018] Carbon dioxide transmission pipelines are core facilities in carbon capture, utilization, and storage (CCLS) and industrial gas transportation systems, and their operational safety directly impacts environmental and production safety. Existing methods for detecting leaks in carbon dioxide transmission pipelines have significant technical shortcomings. In the early stages of a leak, the small diffusion range of the medium and the slight temperature change make it difficult to detect quickly. Traditional detection methods are slow to respond and cannot accurately capture early leaks by observing temperature differences between the pipeline and the surrounding environment, easily leading to an escalation of the leak risk. Some temperature difference monitoring schemes use fixed thresholds and single data processing modes, resulting in weak anti-interference capabilities and susceptibility to environmental temperature changes, pipeline vibration, and other factors, leading to poor detection accuracy and failing to meet the need for leak early warning across the entire pipeline route, around the clock.

[0019] Therefore, this application provides an early warning method for carbon dioxide transmission pipelines based on optical fiber temperature difference monitoring, which solves the above-mentioned problems in the prior art. It can improve the accuracy and response speed of initial identification of carbon dioxide pipeline leaks, has strong anti-interference ability, effectively avoids the expansion of leakage risk, and provides reliable protection for the safe operation of pipelines.

[0020] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application. Furthermore, the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0021] Figure 1 This is a flowchart illustrating an early warning method for carbon dioxide transmission pipelines based on optical cable temperature difference monitoring, provided as an embodiment of this application. Figure 1 As shown, the method may include: Step S110: Obtain the raw temperature data of each monitoring point along the entire route of the carbon dioxide transmission pipeline collected by the distributed optical fiber sensing cable.

[0022] The raw temperature data includes the pipe outer wall temperature data corresponding to each monitoring point and the ambient temperature data around the pipe.

[0023] Specifically, the raw temperature data is collected from each monitoring point along the entire carbon dioxide transmission pipeline by the distributed optical fiber sensing cable. The raw temperature data includes the pipeline outer wall temperature data corresponding to each monitoring point and the ambient temperature data around the pipeline. The two work together to provide basic data support for subsequent temperature difference calculation and leakage judgment.

[0024] The distributed fiber optic sensing cable has been pre-processed and custom-deployed. The cable is fixed along the entire length of the carbon dioxide transmission pipeline, with reinforced wrapping at high-leakage locations such as bends and joints to ensure no monitoring blind spots along the entire route. The sensing section of the cable undergoes anti-corrosion and anti-interference treatment, making it suitable for complex laying environments such as outdoor, underground, and humid conditions, ensuring the stability and reliability of the raw temperature data acquisition. Through the distributed sensing characteristics of the cable, synchronous acquisition of temperature data from all monitoring points along the entire pipeline is achieved, ensuring that the raw temperature data accurately reflects the temperature status of the pipeline and its surrounding environment, providing a precise data foundation for subsequent data processing and leak early warning.

[0025] Step S120: Use an adaptive filtering algorithm to process each raw temperature data to determine the temperature difference dataset.

[0026] Specifically, the adaptive filtering algorithm employs an adaptive filtering model based on the minimum mean square error criterion. Its core lies in its ability to dynamically adjust filtering parameters according to the characteristics of the input raw temperature data, eliminating the need for a pre-set fixed filtering template and adapting to the temperature data fluctuation characteristics under different pipeline laying environments and operating conditions. The algorithm incorporates an interference feature identification module, which can selectively distinguish between valid temperature signals and interference signals by extracting the frequency, amplitude, and duration characteristics of the temperature signal. For instantaneous, high-frequency temperature interference signals caused by natural environmental factors such as wind, sunlight, and precipitation, as well as sudden temperature disturbances caused by operating conditions such as pipeline load fluctuations and vibrations, the algorithm suppresses and filters out these interference signals by dynamically adjusting the filtering window width and attenuation coefficient. Simultaneously, it retains continuous and stable temperature signal components while eliminating abnormal discrete data points, ensuring that the retained temperature data accurately reflects the temperature correlation between the pipeline and its surrounding environment, thus preventing interference data from affecting the accuracy of subsequent temperature difference calculations and leak detection.

[0027] The algorithm first performs separate preprocessing on the pipe outer wall temperature data and ambient temperature data collected synchronously at each monitoring point. It adaptively adjusts the convergence factor to control the parameter update rate, adapting to the temperature data characteristics differences in different laying environments such as outdoor and underground locations, as well as temperature baseline fluctuations caused by diurnal temperature variations and seasonal changes. Next, it performs correlation calculations on the calibrated temperature data, subtracting the ambient temperature data from the pipe outer wall temperature data at the corresponding monitoring point to calculate the real-time temperature difference data for each monitoring point. Finally, it aggregates the real-time temperature difference data from all monitoring points along the entire route according to monitoring location and collection time sequence, forming a standardized temperature difference dataset. This provides accurate and stable data support for subsequent benchmark temperature difference value comparison and real-time temperature difference deviation value calculation, ensuring the accuracy of subsequent leak identification. The adaptive characteristics of this algorithm effectively solve the problems of weak anti-interference ability and susceptibility to environmental and operating conditions in traditional fixed filtering algorithms, ensuring the reliability of temperature difference data processing.

[0028] In some embodiments, the filter order L is set to 32, and the initial step size is... The filter weight coefficient vector Initialize to a zero vector. Use the reference temperature difference value calculated from the same monitoring point within the reference calibration period. The low-frequency trend component is extracted as an ideal reference signal d(n) by using a first-order low-pass filter with a cutoff frequency of 0.1Hz. Then, the filtered output ,in It is an input vector composed of current and historical original temperature difference signals.

[0029] The error calculation process is as follows: ; Calculate the instantaneous energy of the input signal Normalized step size is adopted Line update, where ε=10 -6 This is a small constant designed to prevent division by zero errors. This design increases the convergence speed when the signal is stable and decreases the step size to maintain stability when the signal fluctuates wildly.

[0030] The weight coefficient update process is as follows:

[0031] Step S130: Based on the temperature difference measurement value of each monitoring point in the temperature difference dataset, determine the difference between the temperature difference measurement value of the same monitoring point and the reference temperature difference value, and determine the difference as the real-time temperature difference deviation value of the corresponding monitoring point.

[0032] The reference temperature difference value is determined based on the target temperature data of the carbon dioxide transmission pipeline under normal transportation conditions. Specifically, this may include: before officially initiating leak monitoring, a preheating calibration process is performed. Using distributed fiber optic sensing cables, target temperature data (including pipeline outer wall temperature and surrounding ambient temperature) is continuously collected at different times and along different sections of the pipeline under leak-free, normal transportation conditions. The collection period covers different environmental conditions such as day and night, and sunny or cloudy weather, ensuring the comprehensiveness of the data sample. Subsequently, an adaptive filtering algorithm is used to remove interference from the collected target temperature data, eliminating abnormal data caused by sudden environmental changes, instantaneous pipeline vibrations, etc. Then, the average temperature difference within the calibration period is calculated for each monitoring point, and this average temperature difference is used as the reference temperature difference value for the corresponding monitoring point, forming a reference temperature difference value database for all monitoring points along the entire pipeline section. This database supports periodic calibration and updates to adapt to changes in operating conditions after long-term pipeline operation.

[0033] In some embodiments, the target temperature data is dynamically generated using a digital twin model that considers the real gas properties of carbon dioxide and transient heat transfer in the pipe. The core of this model lies in solving the following one-dimensional unsteady-state heat transfer equation:

[0034] Where T is the CO2 temperature inside the pipe, t is time, and x is the axial distance of the pipe. , , Here, represents the density, specific heat capacity at constant pressure, and thermal conductivity of CO2, respectively, and A is the cross-sectional area of ​​the pipe. Let r be the mass flow rate, r be the pipe radius, and U be the overall heat transfer coefficient. For soil temperature This represents the temperature change rate caused by the Joule-Thomson effect.

[0035] Step S130 specifically includes: according to the location of the monitoring points and the collection time sequence, performing a one-to-one correspondence calculation between the real-time temperature difference measurement value of each monitoring point in the temperature difference dataset and the benchmark temperature difference value of the corresponding monitoring point in the benchmark temperature difference value database. The calculation formula is: Real-time temperature difference deviation value = Real-time temperature difference measurement value of monitoring point - Benchmark temperature difference value of monitoring point. This calculation can accurately capture the degree of deviation of the temperature difference of each monitoring point from the normal operating conditions. When a pipeline leaks, the diffusion of carbon dioxide in the leak area will cause abnormal changes in the temperature of the outer wall of the pipeline, thereby causing the temperature difference measurement value of the corresponding monitoring point to deviate from the benchmark temperature difference value, forming a significant real-time temperature difference deviation value, providing a clear discrimination signal for subsequent leak identification. At the same time, the calculated real-time temperature difference deviation values ​​of each monitoring point are standardized and recorded, and associated with the location information and time sequence information of the corresponding monitoring points to form a real-time temperature difference deviation value dataset, ensuring the accuracy and traceability when comparing with the segmented alarm thresholds later.

[0036] Step S140: Compare the real-time temperature difference deviation value of each monitoring point with the segmented alarm threshold configured for the corresponding road section. Based on the comparison results, determine the leakage event and leakage level through a secondary verification mechanism, and generate and issue early warning information.

[0037] The configuration process for segmented alarm thresholds includes: Based on the physical properties of carbon dioxide, pipeline operating parameters, and environmental factors, the segmented alarm thresholds for each road segment are determined. Specifically, using the baseline temperature difference value of the monitoring points for the corresponding road segment as a foundation, and considering the physical characteristics of rapid diffusion and heat absorption after carbon dioxide leakage, a preset temperature difference influence weighting coefficient is established. This weighting is adjusted in conjunction with pipeline operating parameters such as pipeline delivery pressure and medium temperature. The higher the delivery pressure and the greater the temperature difference between the medium and the ambient temperature, the higher the weighting coefficient, and the smaller the deviation range of the corresponding segmented alarm threshold from the baseline temperature difference value. Simultaneously, the thresholds are optimized by considering environmental factors such as the temperature and humidity of the pipeline laying environment and geographical conditions. The threshold deviation range is appropriately reduced in humid environments and areas with large temperature fluctuations, while it can be moderately relaxed in dry and stable environments, forming the basic segmented alarm thresholds. For high-risk leakage locations such as pipeline bends and joints, the deviation range is further reduced by 10%-30% based on the basic segmented alarm thresholds, setting more stringent segmented alarm thresholds. Ultimately, a gradient threshold system matching the risk level of the road segment (low risk for straight pipe sections, high risk for bends and joints) is formed to ensure early detection of leakage hazards in high-risk areas.

[0038] In some embodiments, the segmented alarm threshold is further configured with an adaptive correction coefficient; Based on the adaptive correction coefficient and the ambient temperature around the pipeline, the baseline temperature difference value of the corresponding road segment is corrected to obtain the corrected segmented alarm threshold. Specifically, this process includes: the segmented alarm threshold is also configured with an adaptive correction coefficient, the setting and correction method of which is as follows: the adaptive correction coefficient is preset based on the correlation analysis between historical ambient temperature fluctuation data and early warning accuracy, using a normalization method to convert the correlation between the ambient temperature change amplitude and the corresponding number of false alarms and missed alarms into a coefficient value within the range of 0.8-1.2. The greater the ambient temperature fluctuation, the closer the coefficient value is to 0.8, used to narrow the threshold deviation range and improve sensitivity; the more stable the ambient temperature, the closer the coefficient value is to 1.2, used to appropriately relax the threshold to reduce false alarms. In subsequent correction processes, the ambient temperature around the pipeline is collected in real time, the deviation value between the current ambient temperature and the average ambient temperature within the baseline calibration period is calculated, and combined with the preset adaptive correction coefficient, the basic segmented alarm threshold of the corresponding road segment is dynamically corrected through the calculation logic of corrected segmented alarm threshold = basic segmented alarm threshold × adaptive correction coefficient, rather than directly correcting the baseline temperature difference value, ensuring the stability of the baseline temperature difference value. For example, when the ambient temperature rises significantly above the reference temperature, the adaptive correction coefficient is lowered, and the corrected segmented alarm threshold is reduced, which can accurately capture the small temperature difference deviation caused by leakage; when the ambient temperature is stable, the coefficient is kept high, and the threshold is appropriately relaxed to avoid false alarms caused by ambient temperature drift and ensure the applicability of the threshold under different environmental conditions.

[0039] The secondary verification mechanism includes: when the real-time temperature difference deviation value of any monitoring point reaches or exceeds the corresponding segmented alarm threshold, the effective temperature difference measurement values ​​of the monitoring point and multiple adjacent monitoring points are continuously collected within a preset time period, and the corresponding real-time temperature difference deviation value is calculated. If all the threshold conditions are met or the real-time temperature difference deviation value of the monitoring point continues to rise, a leakage event is determined to exist. Furthermore, the secondary verification mechanism is used to improve the accuracy of leak detection and avoid misjudgments caused by momentary interference. Specifically, it includes: when the real-time temperature difference deviation value of any monitoring point reaches or exceeds the segmented alarm threshold (including the corrected threshold) of the corresponding road segment, the secondary verification process is immediately initiated. Within a preset time period, the effective temperature difference measurement values ​​of the monitoring point and multiple adjacent monitoring points are continuously collected, and the real-time temperature difference deviation value of each point is obtained synchronously according to the calculation method in step S130; the secondary verification data is analyzed. If the real-time temperature difference deviation values ​​of the monitoring point and multiple adjacent monitoring points all meet the threshold conditions, or the real-time temperature difference deviation value of the monitoring point shows a continuous upward trend without any signs of decline, then momentary interference factors are excluded, and a leak event is formally determined to exist; if only the monitoring point triggers the threshold once and the subsequent data returns to the normal range, it is determined to be an interference signal, and a leak warning is not triggered, ensuring the reliability of leak detection.

[0040] Furthermore, the leakage level is determined based on the magnitude and spread rate of the real-time temperature difference deviation exceeding the segmented alarm threshold. Different leakage levels correspond to different ranges of temperature difference deviation magnitude and spread rate. In other words, the leakage level is divided into multiple levels based on the magnitude and spread rate of the real-time temperature difference deviation exceeding the segmented alarm threshold. Different leakage levels correspond to different temperature difference deviation ranges and spread rate ranges, achieving precise differentiation of leakage severity: by tracking the number of monitoring points that trigger the threshold and the spread range in real time, the spread rate of the leak area is calculated. Combined with the specific magnitude of the real-time temperature difference deviation exceeding the threshold, different levels of leakage events are classified. The larger the deviation magnitude and the faster the spread rate, the higher the corresponding leakage level, indicating a more severe leakage risk.

[0041] In some embodiments, the early warning information must include complete leakage-related parameters and handling guidelines, specifically including the leakage location, real-time temperature difference deviation value, leakage level, and targeted handling suggestions. The leakage location is accurately located based on the location information of the monitoring point that triggered the early warning, and the handling suggestions are preset in combination with the leakage level and road section conditions. The early warning information is simultaneously released through local audible and visual alarms and remote platform push. Local audible and visual alarms can quickly remind on-site inspection personnel, and remote platform push can be promptly synchronized to the control center and relevant responsible personnel's terminals, achieving multi-dimensional early warning coverage and buying time for leakage handling.

[0042] After an early warning is issued, the system is linked to the pipeline monitoring platform, simultaneously uploading all data including leak location, real-time temperature difference deviation, leak level, temperature difference change curve (including baseline temperature difference and corrected threshold), and early warning records, generating a standardized leak early warning report. For high-level leak warnings, an emergency pipeline inspection command is automatically initiated, pushing the leak location, leak level, and handling suggestions to on-site inspection personnel to guide rapid emergency response. Simultaneously, the system retains all temperature difference data, baseline temperature difference calibration records, threshold correction logs, early warning records, and linkage operation logs, archiving them according to preset timeframes to provide data support for subsequent leak cause analysis, fault tracing, and system optimization. Furthermore, the system periodically verifies the sensing performance of the distributed fiber optic sensing cable based on the retained full data, and optimizes the adaptive filtering algorithm parameters and segmented alarm threshold setting logic by combining historical leak data and baseline temperature difference fluctuation patterns, continuously improving the stability and accuracy of the early warning system.

[0043] This application provides an early warning method for carbon dioxide transmission pipelines based on optical fiber cable temperature difference monitoring. The method includes: acquiring raw temperature data from monitoring points along the entire section of the carbon dioxide transmission pipeline collected by a distributed optical fiber sensing cable; processing the raw temperature data using an adaptive filtering algorithm to determine a temperature difference dataset; determining the difference between the measured temperature difference at each monitoring point and a reference temperature difference value based on the measured temperature difference at the same monitoring point, and defining this difference as the real-time temperature difference deviation value for the corresponding monitoring point; comparing the real-time temperature difference deviation value at each monitoring point with the segmented alarm threshold configured for the corresponding section; and based on the comparison results, determining the leakage event and leakage level through a secondary verification mechanism, generating and issuing early warning information. This application can accurately capture initial temperature difference changes in pipeline leaks, improving the accuracy and timeliness of early warnings, and effectively ensuring the safety of carbon dioxide pipeline transportation.

[0044] Corresponding to the above method, this application also provides an early warning device for carbon dioxide transmission pipelines based on optical cable temperature difference monitoring, such as... Figure 2 As shown, the device includes: Acquisition unit 210 is used to acquire raw temperature data of each monitoring point along the entire route of the carbon dioxide transmission pipeline collected by the distributed optical fiber sensing cable. The processing unit 220 is used to process each raw temperature data using an adaptive filtering algorithm to determine the temperature difference dataset; The determining unit 230 is used to determine the difference between the temperature difference measurement value of the same monitoring point and the reference temperature difference value based on the temperature difference measurement value of each monitoring point in the temperature difference dataset, and to determine the difference as the real-time temperature difference deviation value of the corresponding monitoring point; wherein, the reference temperature difference value is determined based on the target temperature data of the carbon dioxide transmission pipeline under normal transportation conditions; The comparison unit 240 is used to compare the real-time temperature difference deviation value of each monitoring point with the segmented alarm threshold configured for the corresponding road section. Based on the comparison results, the leakage event and leakage level are determined through a secondary verification mechanism, and early warning information is generated and issued.

[0045] The functions of each unit in the early warning device for carbon dioxide transmission pipelines based on optical cable temperature difference monitoring provided in the above embodiments of this application can be implemented through the above methods and steps. Therefore, the specific working process and beneficial effects of each unit in the early warning device for carbon dioxide transmission pipelines based on optical cable temperature difference monitoring provided in the embodiments of this application will not be repeated here.

[0046] This application also provides an electronic device, such as... Figure 3 As shown, it includes a processor 310, a communication interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other through the communication bus 340.

[0047] Memory 330 is used to store computer programs; When the processor 310 executes the program stored in the memory 330, it performs the following steps: Acquire raw temperature data from all monitoring points along the entire route of the carbon dioxide transmission pipeline collected by the distributed fiber optic sensing cable. An adaptive filtering algorithm is used to process the raw temperature data to determine the temperature difference dataset; Based on the temperature difference measurement value of each monitoring point in the temperature difference dataset, the difference between the temperature difference measurement value of the same monitoring point and the reference temperature difference value is determined, and the difference is determined as the real-time temperature difference deviation value of the corresponding monitoring point; wherein, the reference temperature difference value is determined based on the target temperature data of the carbon dioxide transmission pipeline under normal transportation conditions; The real-time temperature difference deviation value of each monitoring point is compared with the segmented alarm threshold configured for the corresponding road section. Based on the comparison results, a secondary verification mechanism is used to determine the leakage event and leakage level, and early warning information is generated and issued.

[0048] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0049] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0050] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0051] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0052] The implementation methods and beneficial effects of the various components of the electronic device in the above embodiments for solving the problem can be found in [reference needed]. Figure 1 The steps in the illustrated embodiments are used to implement the electronic device. Therefore, the specific working process and beneficial effects of the electronic device provided in this application will not be repeated here.

[0053] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores instructions that, when executed on a computer, cause the computer to perform any of the above embodiments of a method for early warning of carbon dioxide transmission pipelines based on optical cable temperature difference monitoring.

[0054] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the above embodiments of a method for early warning of carbon dioxide transmission pipelines based on optical cable temperature difference monitoring.

[0055] Those skilled in the art will understand that the embodiments in this application can be provided as methods, systems, or computer program products. Therefore, the embodiments in this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments in this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0056] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0057] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0058] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0059] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected," "coupled," or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0060] Although preferred embodiments have been described in this application, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the embodiments in this application are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments in this application.

[0061] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of the embodiments of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the embodiments of this application and their equivalents, then these modifications and variations are also intended to be included in the embodiments of this application.

Claims

1. A method for early warning of carbon dioxide transmission pipelines based on optical fiber temperature difference monitoring, characterized in that, The method includes: Acquire raw temperature data from all monitoring points along the entire route of the carbon dioxide transmission pipeline collected by the distributed fiber optic sensing cable. An adaptive filtering algorithm is used to process the raw temperature data to determine the temperature difference dataset; Based on the temperature difference measurement value of each monitoring point in the temperature difference dataset, the difference between the temperature difference measurement value of the same monitoring point and the reference temperature difference value is determined, and the difference is determined as the real-time temperature difference deviation value of the corresponding monitoring point; wherein, the reference temperature difference value is determined based on the target temperature data of the carbon dioxide transmission pipeline under normal transportation conditions; The real-time temperature difference deviation value of each monitoring point is compared with the segmented alarm threshold configured for the corresponding road section. Based on the comparison results, a secondary verification mechanism is used to determine the leakage event and leakage level, and early warning information is generated and issued.

2. The method as described in claim 1, characterized in that, The raw temperature data includes the pipe outer wall temperature data corresponding to each monitoring point and the ambient temperature data around the pipe.

3. The method as described in claim 1, characterized in that, The configuration process for the segmented alarm thresholds includes: Based on the physical properties of carbon dioxide, pipeline operating parameters, and environmental factors, the segmental alarm thresholds for the relevant road sections are determined.

4. The method as described in claim 3, characterized in that, The segmented alarm threshold is also configured with an adaptive correction coefficient; Based on the adaptive correction coefficient and the ambient temperature around the pipeline, the reference temperature difference value of the corresponding road segment is corrected to obtain the corrected segmented alarm threshold.

5. The method as described in claim 1, characterized in that, The secondary verification mechanism includes: when the real-time temperature difference deviation value of any monitoring point reaches or exceeds the corresponding segmented alarm threshold, the effective temperature difference measurement values ​​of the monitoring point and multiple adjacent monitoring points are continuously collected within a preset time period, and the corresponding real-time temperature difference deviation value is calculated. If all the threshold conditions are met or the real-time temperature difference deviation value of the monitoring point continues to rise, it is determined that there is a leakage event.

6. The method as described in claim 1, characterized in that, The leakage level is based on the magnitude and diffusion rate of the real-time temperature difference deviation value exceeding the segmented alarm threshold. Different leakage levels correspond to different ranges of temperature difference deviation magnitude and diffusion rate.

7. The method as described in claim 1, characterized in that, The early warning information includes the leak location, real-time temperature difference deviation value, leak level, and handling suggestions, and is issued through local audible and visual alarms and remote platform push notifications.

8. A carbon dioxide transmission pipeline early warning device based on optical cable temperature difference monitoring, characterized in that, The device includes: The acquisition unit is used to acquire the raw temperature data of each monitoring point along the entire route of the carbon dioxide transmission pipeline collected by the distributed optical fiber sensing cable. The processing unit is used to process the raw temperature data using an adaptive filtering algorithm to determine the temperature difference dataset; The determining unit is used to determine the difference between the temperature difference measurement value of the same monitoring point and the reference temperature difference value based on the temperature difference measurement value of each monitoring point in the temperature difference dataset, and to determine the difference as the real-time temperature difference deviation value of the corresponding monitoring point; wherein, the reference temperature difference value is determined based on the target temperature data of the carbon dioxide transmission pipeline under normal transportation conditions; The comparison unit is used to compare the real-time temperature difference deviation value of each monitoring point with the segmented alarm threshold configured for the corresponding road section. Based on the comparison results, the leakage event and leakage level are determined through a secondary verification mechanism, and early warning information is generated and issued.

9. An electronic device, characterized in that, The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method described in any one of claims 1-7.

Images