Leakage detection positioning method and system of oil refining equipment, electronic equipment and storage medium

Abstract

The present application provides a kind of oil refining equipment leak detection positioning method, system, electronic equipment and storage medium, it is related to oil refining equipment detection technical field, based on the leakage record of equipment pipeline and the maintenance record of sealing element, constructs the test sample including test volume group and leakage rate group, test sample is input fluid simulation model, obtains multiple equipment leak states, when visual equipment detects leakage phenomenon, match the multiple equipment leak states obtained by test, obtain test sample, test sample is used as repair reference, provides assistance for repair personnel. On the one hand, the detection speed is greatly improved, on the other hand, the quality requirement to detection personnel is also very low, even a junior staff, can also complete most of routine maintenance tasks under the guidance of repair reference.

Description

Technical Field

[0001] This invention relates to the field of oil refining equipment testing technology, and in particular to a method, system, electronic device and storage medium for leak detection and location of oil refining equipment. Background Technology

[0002] Equipment that converts crude oil into gasoline, diesel, aviation kerosene, naphtha, and liquefied petroleum gas that meet national standards is called oil refining equipment.

[0003] Leakage problems occasionally occur in oil refining equipment. Once a leak occurs, personnel need to be organized to troubleshoot the problem. Troubleshooting can affect the project schedule. The faster the troubleshooting is, the less impact it has on the project schedule. Therefore, how to improve the speed of leak detection is the technical problem that this invention aims to solve. Summary of the Invention

[0004] This invention provides a method, system, electronic device, and storage medium for detecting and locating leaks in oil refining equipment, in order to overcome the deficiencies existing in related technologies.

[0005] This invention provides a method for detecting and locating leaks in oil refining equipment, comprising: Obtain the equipment model of the oil refining equipment, and locate each equipment pipeline and each seal in the equipment model; The following process is executed repeatedly to obtain a reference graphics library containing multiple reference visual images: Obtain leakage records for each equipment pipeline, determine the test quantity for each equipment pipeline based on the leakage records, and combine the test quantities for each equipment pipeline to obtain a test quantity group; Query the maintenance records of each seal, determine the leakage rate range of each seal based on the maintenance records, select a leakage rate within the leakage rate range, and combine the leakage rates of each different seal to obtain a leakage rate group; Based on the test quantity group and the leakage rate group, fluid simulation is performed on the equipment model to obtain a leakage model, and a reference visual image of the leakage model is determined. Acquire actual visual images of the oil refining equipment, and based on the actual visual images, traverse the reference image library to determine matching target reference visual images; Based on the test quantity group and leakage rate group corresponding to the target reference visual image, the oil refining equipment is leaked and located.

[0006] According to a leak detection and location method for oil refining equipment provided by the present invention, the steps include acquiring leak records of each equipment pipeline, determining test quantities for each equipment pipeline based on the leak records, and combining the test quantities of each equipment pipeline to obtain a test quantity group, comprising: For any equipment pipeline, query the leakage time and leakage amount of any equipment pipeline in the leakage record of that equipment pipeline; Obtain the maximum and minimum leakage of any of the equipment pipelines, create a leakage range, determine the test step size based on the leakage time, mark the test quantity within the leakage range according to the test step size, and select the target test quantity from the test quantities corresponding to any of the equipment pipelines; The test quantity group is obtained by combining the target test quantities corresponding to each equipment pipeline according to the preset equipment pipeline sequence.

[0007] According to the present invention, a method for detecting and locating leaks in an oil refining facility, wherein determining the test step size based on the leak time includes: Where S represents the measurement step size, Δt represents the time difference between adjacent leakage moments, σ(Δt) represents the standard deviation of all time differences, E(Δt) represents the mean of all time differences, and α is a correction coefficient.

[0008] According to a leak detection and location method for oil refining equipment provided by the present invention, the method involves querying the maintenance records of each seal, determining the leakage rate range of each seal based on the maintenance records, selecting a leakage rate within the leakage rate range, and combining the leakage rates of different seals to obtain a leakage rate group, including: For any seal, check the maintenance record of that seal for the number of times it has been replaced and the time of the last replacement. Based on the time difference between the previous replacement time and the current time, the leakage rate range of any seal is determined, and the leakage rate range of any seal is segmented to obtain multiple ranges. Based on the number of times any seal is replaced, the probability of selecting the multiple ranges in the leakage rate range of any seal is determined. Based on the selection probability of the multiple ranges, the leakage rate of any seal is selected multiple times within the leakage rate range of any seal, and the leakage rates of each seal selected each time constitute a leakage rate group.

[0009] According to a leakage detection and location method for oil refining equipment provided by the present invention, determining the selection probability of multiple ranges within the leakage rate range of any given seal based on the number of times any given seal has been replaced includes: Among them, P i F represents the probability of selecting the i-th segment. i Represents the feature value of the i-th segment. f represents the number of times any of the seals can be replaced, β is a correction factor, and L iThis represents the left endpoint value of the i-th segment range, and N is the total number of segments in the multi-segment range.

[0010] According to a leak detection and location method for oil refining equipment provided by the present invention, the step of performing fluid simulation on the equipment model based on the test quantity group and the leak rate group to obtain a leak model, and determining a reference visual image of the leak model, includes: Input the device model into the fluid simulation software; Initial conditions are applied according to the test quantity group, and constraint conditions are applied according to the leak rate group; Fluid simulation is performed using the fluid simulation software to obtain the leakage model, and an observation image of the leakage model from a preset viewpoint is obtained as the reference visual image.

[0011] According to the present invention, a method for leak detection and location in an oil refining facility includes, wherein acquiring an actual visual image of the oil refining facility and, based on the actual visual image, traversing a reference image library to determine a matching target reference visual image, comprises: The actual visual image is acquired at a preset viewing angle using a visual device; Traverse the reference image library, select reference visual images in sequence, compare the actual visual image with the selected reference visual image, and calculate the similarity. The reference visual image with the highest similarity is selected as the target reference visual image; In the comparison process, the main body of the device is located in the actual visual image, an adjustment layer is determined based on the color value of the main body of the device and the theoretical color value, the actual visual image is adjusted based on the adjustment layer, and the similarity is calculated by using a pixel comparison algorithm.

[0012] The present invention also provides a leak detection and location device for oil refining equipment, comprising: The component positioning module is used to obtain the equipment model of the oil refining equipment and locate each equipment pipeline and each seal in the equipment model; The sample building module is used to iteratively execute the following process to obtain a reference graphics library including multiple reference visual images: Obtain leakage records for each equipment pipeline, determine the test quantity for each equipment pipeline based on the leakage records, and combine the test quantities for each equipment pipeline to obtain a test quantity group; Query the maintenance records of each seal, determine the leakage rate range of each seal based on the maintenance records, select a leakage rate within the leakage rate range, and combine the leakage rates of each different seal to obtain a leakage rate group; Based on the test quantity group and the leakage rate group, fluid simulation is performed on the equipment model to obtain a leakage model, and a reference visual image of the leakage model is determined. The data matching module is used to acquire the actual visual image of the oil refining equipment, and based on the actual visual image, traverse the reference image library to determine the target reference visual image to match. The detection and positioning module is used to detect and locate leaks in the oil refining equipment based on the test quantity group and leak rate group corresponding to the target reference visual image.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the leakage detection and location method for oil refining equipment as described above.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the leak detection and location method for oil refining equipment as described above.

[0015] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the leakage detection and location method for oil refining equipment as described above.

[0016] The present invention provides a method, system, electronic equipment, and storage medium for leak detection and location in oil refining equipment. Based on leak records of equipment pipelines and maintenance records of seals, it constructs test samples including test quantity groups and leak rate groups. The test samples are input into a fluid simulation model to obtain various equipment leak states. When a leak is detected by a vision device, the various equipment leak states obtained from the tests are matched to acquire test samples. These test samples are used as maintenance references to assist maintenance personnel. On the one hand, this greatly improves the detection speed; on the other hand, it greatly reduces the skill requirements for testing personnel. Even a junior employee can independently complete most routine maintenance tasks under the guidance of the maintenance references. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the leakage detection and location method for oil refining equipment provided by the present invention.

[0019] Figure 2 This is one of the sub-process diagrams in the leakage detection and location method for oil refining equipment provided by the present invention.

[0020] Figure 3 This is the second sub-process diagram in the leakage detection and location method for oil refining equipment provided by the present invention.

[0021] Figure 4 This is the third sub-process diagram in the leakage detection and location method for oil refining equipment provided by the present invention.

[0022] Figure 5 This is the fourth sub-process diagram in the leakage detection and location method for oil refining equipment provided by the present invention.

[0023] Figure 6 This is a schematic diagram of the structure of the leakage detection and location device for oil refining equipment provided by the present invention.

[0024] Figure 7 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0026] Figure 1 This is a flowchart illustrating a leak detection and location method for oil refining equipment provided in an embodiment of the present invention. Figure 1 As shown, the method includes: S11, Obtain the equipment model of the oil refining equipment, and locate each equipment pipeline and each seal in the equipment model; S12, repeat the following process to obtain a reference graphics library including multiple reference visual images: S121, Obtain the leakage records of each equipment pipeline, determine the test quantity of each equipment pipeline based on the leakage records, and combine the test quantities of each equipment pipeline to obtain a test quantity group; S122, query the maintenance records of each seal, determine the leakage rate range of each seal according to the maintenance records, select a leakage rate within the leakage rate range, and combine the leakage rates of each different seal to obtain a leakage rate group; S123, Based on the test quantity group and the leakage rate group, perform fluid simulation on the equipment model to obtain a leakage model, and determine the reference visual image of the leakage model; S13, acquire the actual visual image of the oil refining equipment, and traverse the reference image library based on the actual visual image to determine the matching target reference visual image; S14, based on the test quantity group and leakage rate group corresponding to the target reference visual image, perform leakage detection and location on the oil refining equipment.

[0027] Specifically, the leakage detection and location method for oil refining equipment provided in this embodiment of the invention is executed by a leakage detection and location device for oil refining equipment. This device can be configured in a computer, which can be a local computer or a cloud computer. The local computer can be a computer, tablet, etc., and no specific limitation is made here.

[0028] It is understandable that steps S11-S12 are the design phase, and steps S13-S14 are the testing phase.

[0029] First, step S11 is executed to obtain the equipment model of the oil refining equipment, and then the various equipment pipelines and seals are located within the equipment model. The equipment model is a 3D model of the oil refining equipment created using 3D software, and is considered known data. The equipment pipelines and seals are queried within the equipment model. Equipment pipelines refer to components that store leaking oil, such as pipes used to transport oil. Seals are components used to prevent oil leakage; in this invention, the locations of the seals are considered potential leakage points.

[0030] Then, step S12 is executed repeatedly, repeating the following process to obtain a reference image library containing multiple reference visual images. Specifically, each execution of steps S121-S123 yields a test set, a leak rate set, and a reference visual image. Repeating this process multiple times results in multiple reference visual images. Here, the number of iterations can be a preset threshold, such as the number of possible combinations. The reference image library can include the same number of reference visual images as the number of iterations, and the corresponding test set and leak rate set can both serve as labels for the reference visual images.

[0031] In step S121, leakage records for each equipment pipeline can be found in the maintenance records. These records include the amount of oil leaked at what time. Subsequently, the leakage records for each equipment pipeline are analyzed to determine the potential leakage amount, known as the test quantity. The test quantity for the same equipment pipeline is not unique. One test quantity is selected from those corresponding to each equipment pipeline, and then combined according to the order of the equipment pipelines to obtain a test quantity group. This test quantity group is an array composed of the test quantities for each equipment pipeline, with each test quantity corresponding to one equipment pipeline.

[0032] It should be noted that when selecting test quantities for each equipment pipeline, a simplified approach can be adopted to reduce the number of combinations. First, select test quantities for one or two equipment pipelines, and then set the test quantities for other equipment pipelines to zero. The practical significance of this is that, under normal circumstances, most of the time one equipment pipeline will have a problem, a small probability that two equipment pipelines will have a problem, and the probability of three or more equipment pipelines having a problem is almost zero.

[0033] Then proceed to step S122. The location of the seal is generally where leakage may occur. By checking the maintenance records of each seal, the leakage rate range can be determined.

[0034] Then, a leakage rate is selected from the leakage rate range corresponding to each seal and combined to obtain a leakage rate group. This leakage rate group is an array composed of the leakage rates of each seal, with each leakage rate corresponding to one seal. Here, the leakage rate refers to the mass or volume of fluid that leaks out from the gap of the seal per unit time.

[0035] Then, step S123 is executed. The test quantity represents how much oil is produced by the equipment pipeline, and the leakage rate represents the sealing capacity of the seal. The equipment pipeline can be regarded as the liquid source, and the leakage rate can be regarded as the constraint. The equipment model is input into the fluid simulation software, and the liquid source and constraint are determined according to the test quantity group and the leakage rate group. Then, fluid simulation is performed, and the fluid simulation result is called the leakage model.

[0036] The leakage model is a predictive model obtained using fluid simulation software; it represents a prediction result. Once the leakage model is obtained, reference visual images of the leakage model can be determined from a preset perspective, typically including a front view, rear view, left view, and right view.

[0037] Following step S13, a visual image of the refining equipment can be acquired using vision devices, including optical cameras and infrared gas cameras. Optical cameras are used to detect visible leaks, while infrared gas cameras are used to detect invisible leaks, such as colorless gases. When an infrared gas camera is used, the gas being transported in the equipment pipeline is the same as oil; the only difference is the transported substance.

[0038] The reference image library is traversed using actual visual images. The traversal process is a real-time comparison process. The comparison process requires calculating similarity and selecting the reference visual image with the highest similarity as the target reference visual image for matching.

[0039] Finally, step S14 is executed to detect and locate leaks in the oil refining equipment using the test quantity group and leak rate group corresponding to the target reference visual image. After retrieving the target reference visual image, its corresponding test quantity group and leak rate group are read from the reference image library. The test quantity group indicates which equipment pipelines may leak oil, and the leak rate group indicates which seals may have problems. Both can be used as a reference for leak detection.

[0040] The leakage detection and location method for oil refining equipment provided in this embodiment of the invention constructs a test sample including a test quantity group and a leak rate group based on leakage records of equipment pipelines and maintenance records of seals. The test sample is input into a fluid simulation model to obtain various equipment leakage states. When a leakage phenomenon is detected by a vision device, the various equipment leakage states obtained from the test are matched to obtain a test sample. This test sample is used as a maintenance reference to assist maintenance personnel. On the one hand, it greatly improves the detection speed; on the other hand, it has very low requirements for the skill level of the detection personnel. Even a junior employee can independently complete most routine maintenance tasks under the guidance of the maintenance reference.

[0041] like Figure 2 As shown, based on the above embodiments, the step of obtaining leakage records for each equipment pipeline, determining the test quantity for each equipment pipeline based on the leakage records, and combining the test quantities for each equipment pipeline to obtain a test quantity group includes: S21, For any equipment pipeline, query the leakage time and leakage amount of any equipment pipeline in the leakage record of any equipment pipeline; S22, obtain the maximum and minimum leakage of any equipment pipeline, create a leakage range, determine the test quantity step size according to the leakage time, mark the test quantity within the leakage range according to the test quantity step size, and select the target test quantity from the test quantities corresponding to any equipment pipeline; S23, combine the target test quantities corresponding to each equipment pipeline according to the preset equipment pipeline sequence to obtain the test quantity group.

[0042] Specifically, the maintenance record of each equipment pipeline is used to check the time and amount of leakage. The time and amount of leakage indicate how much oil was leaked at what time.

[0043] Obtain the maximum and minimum leakage amounts from the maintenance records to create a leakage range. Then, arrange the leakage times to calculate the leakage frequency. Based on the leakage frequency, determine a test step size, divide the leakage range, and mark multiple test quantities as the corresponding test quantities for this equipment pipeline. The leakage range is essentially an interval, and the division process is equivalent to extracting multiple points within that interval to obtain the test quantities.

[0044] Finally, select one test quantity from the test quantities corresponding to each equipment pipeline as the target test quantity, and combine the target test quantities corresponding to each equipment relationship according to the arrangement order of the equipment pipelines to obtain the test quantity group.

[0045] Based on the above embodiments, determining the test step size according to the leakage time includes: Where S represents the measurement step size, Δt represents the time difference between adjacent leakage moments, σ(Δt) represents the standard deviation of all time differences, E(Δt) represents the mean of all time differences, and α is a correction coefficient.

[0046] Specifically, the test step size is used to select test quantities within the test quantity range. The principle is that after arranging the leakage times, the time difference between adjacent leakage times is calculated. The longer the time difference between all leakage times, the longer the corresponding mean. In this case, a larger test step size is needed, resulting in fewer test quantities selected within the leakage range. Conversely, a larger standard deviation indicates a more unstable frequency of leakage times; in this case, a smaller test step size is needed, resulting in more test quantities selected within the leakage range.

[0047] like Figure 3 As shown, based on the above embodiments, the step of querying the maintenance records of each seal, determining the leakage rate range of each seal based on the maintenance records, selecting a leakage rate within the leakage rate range, and combining the leakage rates of different seals to obtain a leakage rate group, including: S31, For any seal, query the maintenance record of any seal for the number of times the seal was replaced and the time of the last replacement. S32, based on the time difference between the previous replacement time and the current time, determine the leakage rate range of any seal, and segment the leakage rate range of any seal to obtain multiple ranges. Based on the number of replacements of any seal, determine the selection probability of the multiple ranges in the leakage rate range of any seal. S33, based on the selection probability of the multiple ranges, the leakage rate of any seal is selected multiple times within the leakage rate range of any seal, and the leakage rates of each seal selected each time constitute a leakage rate group.

[0048] Specifically, in this embodiment of the invention, the process for selecting the leakage rate of the seal is limited. First, the number of times each seal has been replaced and the time of the last replacement are queried. The number of replacements indicates whether the seal needs to be replaced frequently at that location. If so, it means that the probability of a problem is high. The difference between the time of the last replacement and the current time indicates how long the newly replaced seal has been used.

[0049] A leakage rate range is determined by combining the number of times each seal is replaced and the time difference between the previous replacement time and the current time. This leakage rate range is then segmented to obtain multiple ranges. For each range, the selection probability of that range is determined, and only one leakage rate is selected from the leakage rate range corresponding to each seal using the selection probability. The selected leakage rates of each seal are combined to obtain leakage rate groups. By repeating this process multiple times, multiple leakage rate groups can be obtained.

[0050] Based on the above embodiments, determining the selection probability of the multiple ranges within the leakage rate range of any seal based on the number of times any seal is replaced includes: Among them, P i F represents the probability of selecting the i-th segment. i Represents the feature value of the i-th segment. f represents the number of times any of the seals can be replaced, β is a correction factor, and L i This represents the left endpoint value of the i-th segment range, and N is the total number of segments in the multi-segment range.

[0051] Specifically, the principle for calculating the probability is as follows: first, the leakage rate range is divided into segments, for example, 10 segments. For each segment, L... i This represents the left endpoint value of the i-th segment. The larger the left endpoint value, the higher the leakage rate. After obtaining the number of replacements, a higher number of replacements indicates more frequent replacements, making it more likely that a problem will occur at that location. The number of replacements is corrected based on a preset correction coefficient β. Then, by calculating the difference between the corrected number of replacements and the left endpoint value of each segment, it is determined which segment the corrected number of replacements is closer to. The closer the number of replacements, the larger the corresponding feature value. After normalizing the feature values ​​of each segment, the selection probability of each segment can be obtained. The effect is that the larger the number of replacements, the greater the probability of selecting a segment with a higher leakage rate.

[0052] like Figure 4 As shown, based on the above embodiments, the step of performing fluid simulation on the device model based on the test quantity group and the leakage rate group to obtain a leakage model and determining a reference visual image of the leakage model includes: S41, Input the device model into the fluid simulation software; S42, apply initial conditions according to the test quantity group, and apply constraint conditions according to the leak rate group; S43, Perform fluid simulation based on the fluid simulation software to obtain the leakage model, and obtain the observation image of the leakage model from a preset viewpoint as the reference visual image.

[0053] Specifically, most existing fluid simulation software supports multiple formats of 3D models. Inputting the equipment model into the software is not complicated. Initial conditions are applied based on the test quantity group, constraints are applied based on the leakage rate group, and other simulation parameters can use default, conventional data. The resulting simulation result is called the leakage model. Observational images of the leakage model from a preset viewpoint are then obtained as reference visual images. Here, the observational images used include the front view, rear view, left view, and right view.

[0054] like Figure 5 As shown, based on the above embodiments, the step of acquiring the actual visual image of the oil refining equipment and traversing the reference image library based on the actual visual image to determine the matching target reference visual image includes: S51, acquire the actual visual image at a preset viewing angle using a vision device; S52, Traverse the reference image library, select reference visual images in sequence, compare the actual visual image with the selected reference visual image, and calculate the similarity. S53, Select the reference visual image corresponding to the maximum similarity as the target reference visual image; In the comparison process, the main body of the device is located in the actual visual image, an adjustment layer is determined based on the color value of the main body of the device and the theoretical color value, the actual visual image is adjusted based on the adjustment layer, and the similarity is calculated by using a pixel comparison algorithm.

[0055] Specifically, when determining the target reference visual image, the actual visual image of the oil refining equipment is acquired with the help of a vision device at a preset viewing angle. The preset viewing angle includes the front view, the rear view, the left view, and the right view. The actual visual image is compared one by one with the reference visual images in the reference image library to calculate the similarity. The reference visual image with the highest similarity is selected as the target reference visual image for matching.

[0056] In this invention, the comparison process is limited. Because the actual visual image is affected by ambient lighting conditions during the acquisition stage, directly comparing it with a reference visual image is difficult. From a computer perspective, pixels are numerical values, and these values ​​change significantly due to environmental interference, easily leading to errors. Therefore, in this embodiment, contour recognition is first performed on the actual visual image to locate the device body. The color value of the device body has a preset reference value. A layer mask or filter that converts the color value of the device body into the reference value is generated and then superimposed on the actual visual image, effectively reducing environmental influences.

[0057] like Figure 6As shown, based on the above embodiments, this embodiment of the invention provides a leak detection and location device for oil refining equipment, comprising: The component positioning module 61 is used to obtain the equipment model of the oil refining equipment and to locate each equipment pipeline and each seal in the equipment model; The sample construction module 62 is used to repeatedly execute the following process to obtain a reference graphics library including multiple reference visual images: obtain the leakage records of each equipment pipeline, determine the test quantity of each equipment pipeline according to the leakage records, and combine the test quantities of each equipment pipeline to obtain a test quantity group; Query the maintenance records of each seal, determine the leakage rate range of each seal based on the maintenance records, select a leakage rate within the leakage rate range, and combine the leakage rates of each different seal to obtain a leakage rate group; Based on the test quantity group and the leakage rate group, fluid simulation is performed on the equipment model to obtain a leakage model, and a reference visual image of the leakage model is determined. Data matching module 63 is used to acquire the actual visual image of the oil refining equipment, and traverse the reference image library based on the actual visual image to determine the target reference visual image to be matched. The detection and positioning module 64 is used to detect and locate leaks in the oil refining equipment based on the test quantity group and leak rate group corresponding to the target reference visual image.

[0058] Based on the above embodiments, the sample construction module 62 is specifically used for: For any equipment pipeline, query the leakage time and leakage amount of any equipment pipeline in the leakage record of that equipment pipeline; Obtain the maximum and minimum leakage of any of the equipment pipelines, create a leakage range, determine the test step size based on the leakage time, mark the test quantity within the leakage range according to the test step size, and select the target test quantity from the test quantities corresponding to any of the equipment pipelines; The test quantity group is obtained by combining the target test quantities corresponding to each equipment pipeline according to the preset equipment pipeline sequence.

[0059] Based on the above embodiments, determining the test step size according to the leakage time includes: Where S represents the measurement step size, Δt represents the time difference between adjacent leakage moments, σ(Δt) represents the standard deviation of all time differences, E(Δt) represents the mean of all time differences, and α is a correction coefficient.

[0060] Based on the above embodiments, the sample construction module 62 is further specifically used for: For any seal, check the maintenance record of that seal for the number of times it has been replaced and the time of the last replacement. Based on the time difference between the previous replacement time and the current time, the leakage rate range of any seal is determined, and the leakage rate range of any seal is segmented to obtain multiple ranges. Based on the number of times any seal is replaced, the probability of selecting the multiple ranges in the leakage rate range of any seal is determined. Based on the selection probability of the multiple ranges, the leakage rate of any seal is selected multiple times within the leakage rate range of any seal, and the leakage rates of each seal selected each time constitute a leakage rate group.

[0061] Based on the above embodiments, the sample construction module 62 is further specifically used for: Among them, P i F represents the probability of selecting the i-th segment. i Represents the feature value of the i-th segment. f represents the number of times any of the seals can be replaced, β is a correction factor, and L i This represents the left endpoint value of the i-th segment range, and N is the total number of segments in the multi-segment range.

[0062] Based on the above embodiments, the sample construction module 62 is further specifically used for: Input the device model into the fluid simulation software; Initial conditions are applied according to the test quantity group, and constraint conditions are applied according to the leak rate group; Fluid simulation is performed using the fluid simulation software to obtain the leakage model, and an observation image of the leakage model from a preset viewpoint is obtained as the reference visual image.

[0063] Based on the above embodiments, the data matching module is specifically used for: The actual visual image is acquired at a preset viewing angle using a visual device; Traverse the reference image library, select reference visual images in sequence, compare the actual visual image with the selected reference visual image, and calculate the similarity. The reference visual image with the highest similarity is selected as the target reference visual image; In the comparison process, the main body of the device is located in the actual visual image, an adjustment layer is determined based on the color value of the main body of the device and the theoretical color value, the actual visual image is adjusted based on the adjustment layer, and the similarity is calculated by using a pixel comparison algorithm.

[0064] Specifically, the functions of each module in the leakage detection and location device for oil refining equipment provided in this embodiment of the invention correspond one-to-one with the operation flow of each step in the above-mentioned method-like embodiments, and the achieved effects are also the same. For details, please refer to the above embodiments, and this will not be repeated in this embodiment of the invention.

[0065] Figure 7 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 7 As shown, the electronic device may include a processor 710, a communications interface 720, a memory 730, and a communication bus 740. The processor 710, communications interface 720, and memory 730 communicate with each other via the communication bus 740. The processor 710 can call logical instructions stored in the memory 730 to execute the leak detection and location methods for oil refining equipment provided in the above embodiments.

[0066] Furthermore, the logical instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to related technologies, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0067] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the leakage detection and location method for oil refining equipment provided in the above embodiments.

[0068] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the leakage detection and location method for oil refining equipment provided in the above embodiments.

[0069] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0070] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of software products. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting and locating leaks in oil refining equipment, characterized in that, include: Obtain the equipment model of the oil refining equipment, and locate each equipment pipeline and each seal in the equipment model; The following process is executed repeatedly to obtain a reference graphics library containing multiple reference visual images: Obtain leakage records for each equipment pipeline, determine the test quantity for each equipment pipeline based on the leakage records, and combine the test quantities for each equipment pipeline to obtain a test quantity group; Query the maintenance records of each seal, determine the leakage rate range of each seal based on the maintenance records, select a leakage rate within the leakage rate range, and combine the leakage rates of each different seal to obtain a leakage rate group; Based on the test quantity group and the leakage rate group, fluid simulation is performed on the equipment model to obtain a leakage model, and a reference visual image of the leakage model is determined. Acquire actual visual images of the oil refining equipment, and based on the actual visual images, traverse the reference image library to determine matching target reference visual images; Based on the test quantity group and leakage rate group corresponding to the target reference visual image, the oil refining equipment is leaked and located.

2. The method for detecting and locating leaks in oil refining equipment according to claim 1, characterized in that, The process involves acquiring leakage records for each equipment pipeline, determining the test quantities for each equipment pipeline based on the leakage records, and combining the test quantities for each equipment pipeline to obtain a test quantity group, including: For any equipment pipeline, query the leakage time and leakage amount of any equipment pipeline in the leakage record of that equipment pipeline; Obtain the maximum and minimum leakage of any of the equipment pipelines, create a leakage range, determine the test step size based on the leakage time, mark the test quantity within the leakage range according to the test step size, and select the target test quantity from the test quantities corresponding to any of the equipment pipelines; The test quantity group is obtained by combining the target test quantities corresponding to each equipment pipeline according to the preset equipment pipeline sequence.

3. The method for detecting and locating leaks in oil refining equipment according to claim 2, characterized in that, Determining the test step size based on the leakage time includes: Where S represents the measurement step size, Δt represents the time difference between adjacent leakage moments, σ(Δt) represents the standard deviation of all time differences, E(Δt) represents the mean of all time differences, and α is a correction coefficient.

4. The method for detecting and locating leaks in oil refining equipment according to claim 1, characterized in that, The process involves querying the maintenance records of each seal, determining the leakage rate range for each seal based on the maintenance records, selecting a leakage rate within the leakage rate range, and combining the leakage rates of different seals to obtain a leakage rate group, including: For any seal, check the maintenance record of that seal for the number of times it has been replaced and the time of the last replacement. Based on the time difference between the previous replacement time and the current time, the leakage rate range of any seal is determined, and the leakage rate range of any seal is segmented to obtain multiple ranges. Based on the number of times any seal is replaced, the probability of selecting the multiple ranges in the leakage rate range of any seal is determined. Based on the selection probability of the multiple ranges, the leakage rate of any seal is selected multiple times within the leakage rate range of any seal, and the leakage rates of each seal selected each time constitute a leakage rate group.

5. The method for detecting and locating leaks in oil refining equipment according to claim 4, characterized in that, The step of determining the selection probability of the multiple ranges within the leakage rate range of any given seal based on the number of times any given seal has been replaced includes: Among them, P i F represents the probability of selecting the i-th segment. i Represents the feature value of the i-th segment. f represents the number of times any of the seals can be replaced, β is a correction factor, and L i This represents the left endpoint value of the i-th segment range, and N is the total number of segments in the multi-segment range.

6. The method for detecting and locating leaks in oil refining equipment according to claim 1, characterized in that, The process of performing fluid simulation on the device model based on the test quantity group and the leakage rate group to obtain a leakage model and determining a reference visual image of the leakage model includes: Input the device model into the fluid simulation software; Initial conditions are applied according to the test quantity group, and constraint conditions are applied according to the leak rate group; Fluid simulation is performed using the fluid simulation software to obtain the leakage model, and an observation image of the leakage model from a preset viewpoint is obtained as the reference visual image.

7. The method for detecting and locating leaks in oil refining equipment according to any one of claims 1-6, characterized in that, The step of acquiring the actual visual image of the oil refining equipment and, based on the actual visual image, traversing the reference image library to determine the matching target reference visual image includes: The actual visual image is acquired at a preset viewing angle using a visual device; Traverse the reference image library, select reference visual images in sequence, compare the actual visual image with the selected reference visual image, and calculate the similarity. The reference visual image with the highest similarity is selected as the target reference visual image; In the comparison process, the main body of the device is located in the actual visual image, an adjustment layer is determined based on the color value of the main body of the device and the theoretical color value, the actual visual image is adjusted based on the adjustment layer, and the similarity is calculated by using a pixel comparison algorithm.

8. A leak detection and location device for oil refining equipment, characterized in that, include: The component positioning module is used to obtain the equipment model of the oil refining equipment and locate each equipment pipeline and each seal in the equipment model; The sample building module is used to iteratively execute the following process to obtain a reference graphics library including multiple reference visual images: Obtain leakage records for each equipment pipeline, determine the test quantity for each equipment pipeline based on the leakage records, and combine the test quantities for each equipment pipeline to obtain a test quantity group; Query the maintenance records of each seal, determine the leakage rate range of each seal based on the maintenance records, select a leakage rate within the leakage rate range, and combine the leakage rates of each different seal to obtain a leakage rate group; Based on the test quantity group and the leakage rate group, fluid simulation is performed on the equipment model to obtain a leakage model, and a reference visual image of the leakage model is determined. The data matching module is used to acquire the actual visual image of the oil refining equipment, and based on the actual visual image, traverse the reference image library to determine the target reference visual image to match. The detection and positioning module is used to detect and locate leaks in the oil refining equipment based on the test quantity group and leak rate group corresponding to the target reference visual image.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for detecting and locating leaks in oil refining equipment as described in any one of claims 1-7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for detecting and locating leaks in oil refining equipment as described in any one of claims 1-7.

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