Gas pipeline leakage monitoring method and isolation device based on background-oriented schlieren
By using a background-guided schlieren-based gas pipeline leak detection method and isolation device, the problem of detecting minute leaks in gas pipelines has been solved, enabling early detection and isolation and improving the safety of gas pipelines.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- DATANG INT POWER GENERATION CO LTD BEIJING GAOJING THERMAL POWER BRANCH
- Filing Date
- 2026-04-15
- Publication Date
- 2026-07-10
AI Technical Summary
Existing technologies are insufficient to detect and address minute gas leaks in gas pipelines that are unlikely to accumulate to dangerous concentrations under low leakage rates and normal ventilation conditions, posing significant safety hazards.
A gas pipeline leak detection method based on background-guided schlieren is adopted. By acquiring real-time background schlieren images, performing region matching and feature function calculation, a trace gas leak is identified, and an airbag device is used for isolation.
It enables early detection and timely isolation of minor leaks in gas pipelines, reducing the potential risks of minor gas leaks and improving the overall safety of gas pipelines.
Smart Images
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Abstract
Description
Technical Field
[0001] This application relates to the field of gas pipeline safety monitoring technology, and in particular to a gas pipeline leakage monitoring method and isolation device based on background guiding schlieren. Background Technology
[0002] Gas-fired combined cycle (COC) units are core equipment for achieving efficient energy supply in the current energy sector. With advantages such as high fuel utilization, rapid start-up and shutdown response, and low pollutant emissions, they are widely used in thermal power generation, industrial energy supply, and regional integrated energy supply. In its energy transmission system, the gas pipeline is responsible for transporting methane from the storage unit to the combustion chamber, and its reliability is directly related to the safety factor of the COC unit. Currently, temperature fluctuations and pressure fluctuations during the start-up and shutdown of COC units, material fatigue caused by long-term high-load operation, and the continuous effect of trace corrosive components in the gas can all lead to gas pipeline leaks. Furthermore, the risk of leaks is higher at critical locations such as welded joints and flange sealing surfaces of the gas pipeline. Summary of the Invention
[0003] The applicant has found that current technologies for preventing and detecting gas pipeline leaks, such as the indirect judgment method based on the pressure difference between the pipeline inlet and outlet, cannot promptly detect minute gas leaks with low leakage rates that are unlikely to accumulate to dangerous concentrations under normal ventilation conditions. Often, an alarm is only triggered when the leaked gas accumulates to the point of forming an explosive gas mixture around the pipeline, thus posing a significant safety hazard. Therefore, this application provides a gas pipeline leak monitoring method and isolation device based on background guiding schlieren, which can continuously monitor gas pipelines and promptly detect minute gas leaks with low leakage rates that are unlikely to accumulate to dangerous concentrations under normal ventilation conditions. This reduces the potential risks associated with minute gas leaks and improves the overall safety of gas pipelines.
[0004] To achieve the above objectives, this application provides the following solution.
[0005] In a first aspect, this application provides a method for monitoring gas pipeline leaks based on background-guided schlieren, including: Obtain the real-time background schlieren image of the target area at the current moment; the target area is the area where the gas pipeline is located.
[0006] The real-time background schlieren image is independently matched with each image block in the initial background schlieren image block set of the target region to obtain a real-time displacement vector set; the initial background schlieren image block set of the target region is obtained by dividing the initial background schlieren image of the target region; the initial background schlieren image is an image in the target region that does not have leakage.
[0007] Interpolation and row-by-row averaging are performed on all displacement vectors in the real-time displacement vector set to obtain the real-time characteristic function.
[0008] A comparison feature function without a discriminant marker in the leakage database of the target region is selected as the discriminant feature function, and the similarity between the real-time feature function and the discriminant feature function is calculated as the real-time similarity. The leakage database of the target region includes multiple comparison feature functions of the target region and leakage data corresponding to each comparison feature function.
[0009] Determine whether the real-time similarity is less than the similarity threshold to obtain a first determination result. If the first determination result is negative, determine that there is a leakage situation in the target area at the current time. Based on the leakage data corresponding to the discrimination feature function and the real-time feature function, obtain the real-time leakage data of the target area at the current time.
[0010] Secondly, this application provides a gas pipeline leak monitoring and isolation device based on background-guided schlieren, comprising: The control module is used to execute the above-described background-guided schlieren-based gas pipeline leak detection method.
[0011] The transmission module is used to transmit real-time leaked data output by the control module to the isolation module.
[0012] The isolation module is used to deploy an airbag when it receives the real-time leakage data, so that the airbag covers the gas pipeline with leakage in the target area.
[0013] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a gas pipeline leakage monitoring method and isolation device based on background-guided schlieren. First, a real-time background schlieren image of the target area, where the gas pipeline is located, is acquired. Second, the real-time background schlieren image is independently matched with each image block in the initial background schlieren image block set of the target area to obtain a real-time displacement vector set. The initial background schlieren image block set of the target area is obtained by dividing the initial background schlieren image of the target area, where no leakage is observed. All displacement vectors in the real-time displacement vector set are interpolated and averaged row-by-row to obtain a real-time feature function. The real-time displacement vectors obtained in this step completely preserve the gradient information of the flow field in space, highlighting the shape of the gas around the gas pipeline along the jet direction. The system extracts information about the target region and reduces the dimensionality of the real-time background schlieren image, simplifying the identification elements and making the displacement information of pixels on the real-time background schlieren image of the target region easier to identify. Next, it filters out a comparison feature function without a discrimination marker in the leakage database of the target region as the discrimination feature function, and calculates the similarity between the real-time feature function and the discrimination feature function as the real-time similarity. The leakage database of the target region includes multiple comparison feature functions of the target region and leakage data corresponding to each comparison feature function. It determines whether the real-time similarity is less than a similarity threshold to obtain a first judgment result. If the first judgment result is negative, it is determined that there is a leakage situation in the target region at the current time, and the real-time leakage data of the target region at the current time is obtained based on the leakage data corresponding to the discrimination feature function and the real-time feature function. This application can monitor gas pipelines and capture background pattern changes caused by extremely small gas leaks in the target area. It can also promptly detect trace gas leaks with low leakage rates that are unlikely to accumulate to dangerous concentrations under normal ventilation conditions. It can make accurate monitoring and judgments in the very early stages of gas leaks, thereby reducing the potential risks of gas pipelines due to trace gas leaks and improving the overall safety of gas pipelines. Attached Figure Description
[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0015] Figure 1 This is an application environment diagram of a gas pipeline leakage monitoring method based on background guiding schlieren in one embodiment of this application; Figure 2A schematic flowchart illustrating a gas pipeline leakage monitoring method based on background-guided schlieren, provided as an embodiment of this application; Figure 3 This is the real-time displacement field image corresponding to the real-time displacement field matrix in step 401 of this application. Figure 4 This is the real-time feature function graph obtained in step 203 of this application. Figure 5 A structural block diagram of a gas pipeline leak monitoring and isolation device based on background guiding schlieren provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an isolation module provided in one embodiment of this application; Figure 7 This application provides a schematic diagram of the operation of a gas pipeline leak monitoring and isolation device based on background guiding schlieren, according to one embodiment. Figure 8 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application.
[0016] Reference numerals: Terminal 102, Server 104, Retractable support rod 1, Ejection device 2, Airbag 3, First semicircular ring 4, Second semicircular ring 5, Moving device 6, Control module 7, Gas pipeline 8, Isolation module 9, Background plate 10. 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 some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0019] The gas pipeline leakage monitoring method based on background-guided schlieren provided in this application can be applied to, for example... Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on another server. Terminal 102 can send the real-time background schlieren image of the target area to server 104. Server 104 receives the real-time background schlieren image of the target area and performs independent region matching between the real-time background schlieren image and each image block in the initial background schlieren image block set of the target area to obtain a real-time displacement vector set. The initial background schlieren image block set of the target area is obtained by dividing the initial background schlieren image of the target area. The initial background schlieren image is an image of the target area without leakage. Interpolation and row-by-row averaging are performed on all displacement vectors in the real-time displacement vector set. The system processes data to obtain real-time feature functions. It then filters out a comparison feature function without a discriminant marker in the target region's leakage database, using this as the discriminant feature function. The similarity between the real-time feature function and the discriminant feature function is calculated as the real-time similarity. The target region's leakage database includes multiple comparison feature functions for the target region and leakage data corresponding to each comparison feature function. The system determines whether the real-time similarity is less than a similarity threshold, obtaining a first determination result. If the first determination result is negative, it is determined that a leakage exists in the target region at the current moment. Based on the leakage data corresponding to the discriminant feature function and the real-time feature function, the server 104 obtains the real-time leakage data of the target region at the current moment. The server 104 can then feed back the obtained real-time leakage data of the target region at the current moment to the terminal 102. Furthermore, in some embodiments, the gas pipeline leak detection method based on background-guided schlieren can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly process the real-time background schlieren image of the target area at the current moment to obtain a real-time feature function, and calculate the similarity with the comparison feature function in the leak database to determine whether there is a leak in the target area at the current moment. Alternatively, the server 104 can obtain the real-time background schlieren image of the target area at the current moment from the data storage system, process the real-time background schlieren image of the target area at the current moment to obtain a real-time feature function, and calculate the similarity with the comparison feature function in the leak database to determine whether there is a leak in the target area at the current moment.
[0020] The terminal 102 can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle devices. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster composed of multiple servers, or it can be a cloud server.
[0021] In one exemplary embodiment, such as Figure 2 As shown, a method for monitoring gas pipeline leaks based on background-guided schlieren is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps 201 to 205. Wherein: Step 201: Obtain the real-time background schlieren image of the target area at the current moment; the target area is the area where the gas pipeline is located.
[0022] Step 202: Perform independent region matching between the real-time background schlieren image and each image block in the initial background schlieren image block set of the target region to obtain a real-time displacement vector set; the initial background schlieren image block set of the target region is obtained by dividing the initial background schlieren image of the target region; the initial background schlieren image is an image in the target region where there is no leakage.
[0023] Step 203: Interpolate and average all displacement vectors in the real-time displacement vector set to obtain the real-time characteristic function.
[0024] Step 204: Select a comparison feature function without a discrimination marker in the leakage database of the target area as the discrimination feature function, and calculate the similarity between the real-time feature function and the discrimination feature function as the real-time similarity; the leakage database of the target area includes multiple comparison feature functions of the target area, and leakage data corresponding to each comparison feature function.
[0025] Step 205: Determine whether the real-time similarity is less than the similarity threshold to obtain a first determination result. If the first determination result is negative, determine that there is a leakage in the target area at the current time. Based on the leakage data corresponding to the discrimination feature function and the real-time feature function, obtain the real-time leakage data of the target area at the current time.
[0026] In step 201, “acquiring the real-time background schlieren image of the target area at the current moment”, an optical system consisting of a high-resolution camera can be constructed, with the length of the gas pipeline as the horizontal axis of the monitoring and the vertical height of the gas pipeline (250mm) as the vertical axis of the monitoring. The camera captures the image of the observed target.
[0027] The real-time feature function graph obtained in step 203 above is shown below. Figure 4 As shown.
[0028] The leakage database of the target area mentioned in step 204 above is composed of different characteristic functions measured under different leakage data of the gas pipeline.
[0029] The similarity threshold in step 205 above is related to the image patch size in the initial background schlieren image patch set, the real-time background schlieren image resolution, and all comparison feature functions in the leaked database.
[0030] In step 205 above, if the first judgment result is negative, that is, if the real-time similarity is greater than or equal to the similarity threshold, then based on the leakage data corresponding to the discriminative feature function and the real-time feature function, it is determined that the target area at the current time has experienced leakage corresponding to the leakage data corresponding to the discriminative feature function.
[0031] By implementing steps 201 to 205, the real-time background schlieren image of the target area at the current moment can be processed to obtain a real-time feature function. The similarity is calculated with the feature function in the leakage database to determine whether there is a leakage in the target area at the current moment. This allows for monitoring of the gas pipeline and captures changes in the background pattern caused by extremely weak gas leaks in the target area. Even for trace gas leaks with low leakage rates that are not likely to accumulate to dangerous concentrations under normal ventilation conditions, timely detection is possible. Accurate monitoring and judgment can be made in the very early stages of gas leaks, thereby reducing the potential risks of trace gas leaks in gas pipelines and improving the overall safety of gas pipelines.
[0032] In another exemplary embodiment of this application, in order to eliminate problems such as uneven background and noise interference in the real-time background schlieren image of the target area and improve image accuracy, the above step 202 is replaced by the following steps 301 to 304: Step 301: Perform basal correction on the real-time background schlieren image to obtain the first image.
[0033] Step 302: Perform adaptive spatial domain filtering and frequency domain low-pass filtering on the first image to obtain the second image.
[0034] Step 303: Pixel optimization is performed on the second image to obtain the processed real-time background schlieren image.
[0035] Step 304: Perform independent region matching between the processed real-time background schlieren image and each image block in the initial background schlieren image block set of the target region to obtain a real-time displacement vector set.
[0036] In the above steps, the substrate correction of the real-time background schlieren image of the target area is first completed by the background grayscale adaptive fitting method to eliminate false noise and substrate deviation, and to regularize the background texture substrate, laying the foundation for image quality improvement. Then, adaptive spatial filtering is performed with the gradient direction of the schlieren stripes as a constraint, combined with frequency domain low-pass filtering, to accurately preserve the edge details of the flow field structure while suppressing high-frequency random noise, ensuring the image detail resolution capability. Finally, pixel optimization and reconstruction are used to enhance the grayscale difference between the schlieren and the background, which greatly improves the image detail recognition and overall quality, effectively enhancing the actual resolution capability of the image, thereby eliminating the problems of background unevenness and noise interference in the real-time background schlieren image of the target area, so that the processed real-time background schlieren image can be used for subsequent region matching to obtain the real-time displacement vector set.
[0037] In another exemplary embodiment of this application, in order to fully preserve the gradient information of the flow field in space and highlight the shape information of the gas around the gas pipeline along the jet direction, the above step 203 is replaced by the following steps 401 to 403: Step 401: Interpolate all displacement vectors in the real-time displacement vector set to obtain a real-time displacement field matrix; the real-time displacement field matrix includes the displacement vector of each pixel in the real-time background schlieren image of the target region.
[0038] Step 402: Calculate the magnitude of all displacement vectors in the real-time displacement field matrix to obtain the real-time displacement magnitude matrix; the real-time displacement magnitude matrix includes the displacement vector magnitude of each pixel in the real-time background schlieren image of the target region.
[0039] Step 403: Based on the coordinate values corresponding to each pixel in the real-time displacement field matrix, the displacement magnitude of each pixel in the real-time displacement field matrix is averaged row by row to obtain the real-time feature function.
[0040] In the above steps, by averaging the displacement magnitude of each pixel within the real-time displacement field matrix row by row, the original size is... The two-dimensional data is compressed into a length of The real-time feature function not only reduces dimensionality but also preserves shape information along the jet development direction.
[0041] The real-time displacement field diagram corresponding to the real-time displacement field matrix obtained in step 401 is as follows: Figure 3 As shown.
[0042] In another exemplary embodiment of this application, the real-time feature functions in step 203 and step 402 above are calculated by the following method: (1); in, The real-time feature function of the target region; The first in the real-time displacement modulus matrix The number of displacement moduli corresponding to each row. The first in the real-time displacement modulus matrix Line number The displacement vector magnitude corresponding to the column.
[0043] In another exemplary embodiment of this application, the real-time similarity in step 204 above is calculated by the following method: (2); in, For the real-time feature function of the target region, To determine the characteristic function, The length of the gas pipeline within the target area.
[0044] In another exemplary embodiment of this application, after performing step 205, the method further includes: Step 206: If the first judgment result is yes, then determine whether the leakage database of the target area at the current time still contains comparison feature functions that have not been discriminated and marked, and obtain the second judgment result.
[0045] Step 207: If the second judgment result is yes, then the discrimination feature function is marked, and a comparison feature function that does not have a discrimination mark in the leakage database of the target area is returned as the discrimination feature function.
[0046] Step 208: If the second judgment result is negative, then it is determined that there is no leakage in the target area at the current time.
[0047] In another exemplary embodiment of this application, the leakage data mentioned in step 205 above specifically includes: leakage location, leakage pressure, and leakage orifice diameter.
[0048] This application also provides an application scenario in which the above-described background-guided schlieren-based gas pipeline leak detection method is applied. Specifically, the background-guided schlieren-based gas pipeline leak detection method provided in this embodiment can be applied in a gas pipeline safety assurance scenario. The gas pipeline safety assurance scenario includes a real-time gas pipeline monitoring stage, a real-time gas pipeline information processing link, and a gas pipeline repair stage. The real-time background schlieren image of the target area at the current moment enters the real-time gas pipeline information processing link from the real-time gas pipeline monitoring stage. After image processing, a real-time feature function is obtained, and the similarity is calculated by comparing the feature function with the feature function in the leak database to obtain the corresponding leak data, which then enters the downstream gas pipeline repair stage. The background-guided schlieren-based gas pipeline leak detection method provided in this embodiment belongs to a stage in the real-time gas pipeline information processing link. Specifically, in the real-time gas pipeline information processing process for the real-time background schlieren image of the target area at the current moment, the gas pipeline leak can be monitored in real time by calculating the similarity between the real-time feature function of the target area and the feature function in the leak database, thus achieving accurate gas pipeline monitoring.
[0049] Based on the same inventive concept, this application also provides a background-guided schlieren-based gas pipeline leak detection and isolation device for implementing the steps described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more background-guided schlieren-based gas pipeline leak detection and isolation device embodiments provided below can be found in the limitations of the background-guided schlieren-based gas pipeline leak detection method described above, and will not be repeated here.
[0050] In one exemplary embodiment, such as Figure 5 As shown, a gas pipeline leak detection and isolation device based on background-guided schlieren is provided, specifically including: The control module is used to execute the above-described background-guided schlieren-based gas pipeline leak detection method.
[0051] The transmission module is used to transmit real-time leaked data output by the control module to the isolation module.
[0052] The isolation module is used to deploy an airbag when it receives the real-time leakage data, so that the airbag covers the gas pipeline with leakage in the target area.
[0053] The control module is capable of capturing a real-time background texture image of the target area at the current moment, thereby obtaining a real-time background texture image of the target area at the current moment.
[0054] The isolation module can be implemented using the following movable airbag device: the movable airbag device, such as... Figure 6As shown, it includes: a retractable support rod 1, an ejection device 2, two first semicircular rings 4 and 5 with airbags 3 on their inner sides that can wrap around the sidewalls of the pipe, and a moving device 6.
[0055] The movable airbag device works as follows: Initially, the first semicircular ring 4 and the second semicircular ring 5 hang naturally. After obtaining the leakage information of the gas pipeline, the moving device 6 controls the movable airbag device to move as a whole to below the leakage point. The retractable support rod 1 adjusts the first semicircular ring 4 and the second semicircular ring 5 to the vicinity of the leakage point on the side wall of the gas pipeline. The ejection device 2 is used to launch the first semicircular ring 4 and the second semicircular ring 5, so that the airbag 3 inside them covers the location of the gas pipeline leakage. There are magnets at the connection points of the two ends of the first semicircular ring 4 and the second semicircular ring 5, which firmly attract the two semicircular rings. Thus, the two semicircular rings are combined into a complete ring and inflated into the airbag 3.
[0056] In another exemplary embodiment of this application, a gas pipeline leak monitoring and isolation device based on background-guided schlieren provided in this application further includes: an alarm module.
[0057] The transmission module is used to transmit the real-time leakage data output by the control module to the alarm module.
[0058] The alarm module is used to issue an alarm when the real-time leak data is received.
[0059] In another exemplary embodiment of this application, a gas pipeline leak monitoring and isolation device based on background-guided schlieren provided by this application further includes: a background plate, and when the background plate is used, when the background plate is placed on one side of the target area, the control module is placed on the other side of the target area.
[0060] The gas pipeline leak monitoring and isolation device based on background-guided schlieren provided in this application operates as follows: Figure 7 As shown. The control module 7 monitors the gas pipeline 8. When a leak is detected in the gas pipeline 8, the leak data is sent to the isolation module 9 through the transmission module. The isolation module 9 can then deploy the gasbag in a timely manner based on the leak data.
[0061] When a gas leak occurs and emergency response is needed for gas pipelines and reverse flow, the aforementioned gas pipeline leak monitoring and isolation device based on background guiding holograms can achieve a rapid isolation mechanism with real-time linkage of leak detection signals. It can promptly deploy airbags to prevent further gas leakage, reduce the duration of the gas leak, further reduce the risk of the accident's impact spreading, and minimize the negative impact of continuous gas leakage, thus providing reliable safety protection for gas pipelines.
[0062] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 8 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores gas pipeline leak data. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a background-guided schlieren-based gas pipeline leak monitoring method.
[0063] Those skilled in the art will understand that Figure 8 The structures shown are merely block diagrams of some structures related to the present application and do not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.
[0064] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.
[0065] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.
[0066] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use and processing of the relevant data are carried out in compliance with the relevant data protection laws and policies of the country where the location is located, and with the authorization granted by the owner of the corresponding device.
[0067] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).
[0068] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.
[0069] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0070] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for monitoring gas pipeline leaks based on background-guided schlieren, characterized in that, The gas pipeline leakage detection method based on background guided schlieren includes: Acquire the real-time background schlieren image of the target area at the current moment; the target area is the area where the gas pipeline is located. The real-time background schlieren image is independently matched with each image block in the initial background schlieren image block set of the target region to obtain a real-time displacement vector set; the initial background schlieren image block set of the target region is obtained by dividing the initial background schlieren image of the target region; the initial background schlieren image is a background schlieren image of the target region where there is no leakage. Interpolation and row-by-row averaging are performed on all displacement vectors in the real-time displacement vector set to obtain the real-time characteristic function; A comparison feature function without a discrimination marker in the leakage database of the target area is selected as the discrimination feature function, and the similarity between the real-time feature function and the discrimination feature function is calculated as the real-time similarity; the leakage database of the target area includes multiple comparison feature functions of the target area, and leakage data corresponding to each comparison feature function; Determine whether the real-time similarity is less than the similarity threshold to obtain a first determination result. If the first determination result is negative, determine that there is a leakage situation in the target area at the current time. Based on the leakage data corresponding to the discrimination feature function and the real-time feature function, obtain the real-time leakage data of the target area at the current time.
2. The gas pipeline leakage monitoring method based on background guiding schlieren according to claim 1, characterized in that, The real-time background schlieren image is independently matched with each image block in the initial background schlieren image block set of the target region to obtain a real-time displacement vector set, specifically including: Basis correction is performed on the real-time background schlieren image to obtain the first image; The first image is subjected to adaptive spatial domain filtering and frequency domain low-pass filtering to obtain the second image; The second image is pixel-optimized to obtain a processed real-time background schlieren image; The processed real-time background schlieren image is independently matched with each image block in the initial background schlieren image block set of the target region to obtain a real-time displacement vector set.
3. The gas pipeline leakage monitoring method based on background guiding schlieren according to claim 1, characterized in that, Interpolation and row-by-row averaging are performed on all displacement vectors within the real-time displacement vector set to obtain the real-time characteristic function, specifically including: Interpolation processing is performed on all displacement vectors in the real-time displacement vector set to obtain a real-time displacement field matrix; the real-time displacement field matrix includes the displacement vector of each pixel in the real-time background schlieren image of the target region. The magnitude of all displacement vectors within the real-time displacement field matrix is calculated to obtain the real-time displacement magnitude matrix; the real-time displacement magnitude matrix includes the displacement vector magnitude of each pixel in the real-time background schlieren image of the target region. Based on the coordinate value corresponding to each pixel in the real-time displacement field matrix, the displacement magnitude of each pixel in the real-time displacement field matrix is averaged row by row to obtain the real-time feature function.
4. The gas pipeline leakage monitoring method based on background-guided schlieren according to claim 1 or 3, characterized in that, The real-time feature function is: ； in, The real-time feature function of the target region; The first in the real-time displacement modulus matrix y The number of displacement moduli corresponding to each row. The first in the real-time displacement modulus matrix y Line number x The displacement vector magnitude corresponding to the column.
5. The gas pipeline leakage monitoring method based on background guiding schlieren according to claim 1, characterized in that, The formula for calculating the similarity is: ； in, For the real-time feature function of the target region, To determine the characteristic function, The length of the gas pipeline within the target area.
6. The gas pipeline leakage monitoring method based on background guiding schlieren according to any one of claims 1-5, characterized in that, The gas pipeline leakage monitoring method based on background guiding schlieren also includes: If the first judgment result is yes, then determine whether the leakage database of the target area at the current time still contains comparison feature functions that have not been discriminated and marked, and obtain the second judgment result; If the second judgment result is yes, then the discrimination feature function is marked, and a comparison feature function that does not have a discrimination mark in the leakage database of the target area is returned as the step of the discrimination feature function; If the second judgment result is negative, then it is determined that there is no leakage in the target area at the current time.
7. The gas pipeline leakage monitoring method based on background guiding schlieren according to claim 1, characterized in that, The leakage data includes: leakage location, leakage pressure, and leakage orifice diameter.
8. A gas pipeline leak monitoring and isolation device based on background guiding schlieren, characterized in that, The gas pipeline leak monitoring and isolation device based on background guiding schlieren includes: The control module is used to execute the gas pipeline leakage monitoring method based on background guiding schlieren as described in any one of claims 1-7; The transmission module is used to transmit real-time leaked data output by the control module to the isolation module; The isolation module is used to deploy an airbag when it receives the real-time leakage data, so that the airbag covers the gas pipeline with leakage in the target area.
9. The gas pipeline leak monitoring and isolation device based on background guiding schlieren according to claim 8, characterized in that, Also includes Alarm module; The transmission module is used to transmit the real-time leakage data output by the control module to the alarm module; The alarm module is used to issue an alarm when the real-time leak data is received.
10. The gas pipeline leak monitoring and isolation device based on background guiding schlieren according to claim 8, characterized in that, Also includes: The background board, and when the background board is in use, when the background board is placed on one side of the target area, the control module is placed on the other side of the target area.