Multidimensional data visualization method for substation maintenance operation site based on digital twin

Abstract

The present invention discloses a method for visualizing multidimensional data of a substation maintenance operation site based on digital twins, which belongs to the technical field of substation maintenance, and includes the following steps: S1: collecting real-time building data, real-time equipment data and real-time environmental data of the substation maintenance operation site, and determining real-time multidimensional data based on the substation maintenance operation site; S2: preprocessing the real-time multidimensional data based on the substation maintenance operation site, and determining characteristic multidimensional data based on the substation maintenance operation site; S3: constructing a digital twin model based on the substation maintenance operation site. The present invention solves the existing problem that the multidimensional data of the substation maintenance operation site cannot be visualized, the multidimensional data situation of the substation maintenance operation site cannot be grasped in time, and the substation maintenance effect is poor. The present invention can visualize the multidimensional data of the substation maintenance operation site, can grasp the multidimensional data situation of the substation maintenance operation site in time, and can improve the substation maintenance effect.

Description

Technical Field

[0001] The present invention relates to the technical field of substation maintenance, and in particular to a multidimensional data visualization method of a substation maintenance operation site based on digital twins. Background Art

[0002] Substation maintenance is responsible for inspecting, replacing, and debugging circuit breakers and disconnectors, and repairing transformers, current transformers and other substation equipment to ensure that they meet the quality standards required for safe operation.

[0003] The Chinese patent with publication number CN112256873B discloses a multi-label classification method for substation maintenance work tasks based on deep learning. In the process of issuing substation maintenance work tickets, the multi-label intelligent classification technology based on deep learning is introduced to automatically complete the unstructured information of the maintenance task text to the structured information of multi-task labels such as "interval type", "maintenance interval", and "maintenance equipment", so as to quickly and accurately determine the key maintenance information, provide strong support for the arrangement of safety measures, and greatly improve the work efficiency and accuracy of the work ticket issuance process; however, the patent has the following defects:

[0004] The existing multi-dimensional data of the substation maintenance operation site cannot be visualized, and the multi-dimensional data situation of the substation maintenance operation site cannot be grasped in time, resulting in poor substation maintenance effect. Summary of the invention

[0005] The purpose of the present invention is to provide a multi-dimensional data visualization method for a substation maintenance operation site based on digital twins, which can visualize the multi-dimensional data of the substation maintenance operation site, timely grasp the multi-dimensional data situation of the substation maintenance operation site, improve the substation maintenance effect, and solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The multi-dimensional data visualization method of the substation maintenance operation site based on digital twin includes the following steps:

[0008] S1: Collect real-time building data, real-time equipment data and real-time environmental data at the substation maintenance operation site to determine real-time multi-dimensional data;

[0009] S2: preprocessing the real-time multi-dimensional data to determine characteristic multi-dimensional data;

[0010] S3: Based on the training set, the digital twin model architecture is trained to determine the digital twin model;

[0011] S4: Performing performance testing and optimization adjustment on the digital twin model to determine the best digital twin model;

[0012] S5: simulating the characteristic multidimensional data based on the optimal digital twin model, completing the mapping in the virtual space, and generating a 1:1 restoration panoramic view of the multidimensional data;

[0013] S6: Visually display the multidimensional data in the multidimensional data panorama with a 1:1 restoration degree.

[0014] Preferably, in S1, the real-time multi-dimensional data is determined, and the following operations are performed:

[0015] Collect the construction conditions of the substation maintenance site in real time and determine the real-time construction data;

[0016] Collect the equipment status of the substation maintenance operation site in real time and determine the real-time equipment data;

[0017] Collect the environmental conditions of the substation maintenance operation site in real time and determine the real-time environmental data;

[0018] Among them, based on the real-time building data, real-time equipment data and real-time environmental data, the real-time multi-dimensional data based on the substation maintenance operation site is determined.

[0019] Preferably, in S2, the real-time multi-dimensional data is preprocessed by performing the following operations:

[0020] Retrieve real-time multidimensional data based on sequential retrieval method;

[0021] Identify real-time multidimensional data that is valuable for multidimensional data visualization;

[0022] Sort the real-time multidimensional data that is valuable for multidimensional data visualization based on the internal sorting method;

[0023] Divide the real-time multidimensional data that is valuable for multidimensional data visualization into multiple subsets, integrate the multiple subsets, and sort each subset;

[0024] Determine real-time multi-dimensional data with sorting order;

[0025] Extract features from real-time multi-dimensional data with arrangement order;

[0026] Determine the characteristic multi-dimensional data based on the substation maintenance operation site.

[0027] Preferably, in S2, real-time multi-dimensional data based on the substation maintenance operation site is retrieved, and the following operations are performed:

[0028] Check the consistency of real-time multidimensional data;

[0029] Remove data that is beyond the normal range, logically unreasonable or contradictory in real-time multi-dimensional data;

[0030] Determine real-time multi-dimensional data with data consistency;

[0031] Process invalid and missing values ​​for real-time multidimensional data with data consistency;

[0032] Remove invalid data and missing data that are not valuable for multidimensional data visualization contained in real-time multidimensional data with data consistency;

[0033] Identify real-time multidimensional data that is valuable for multidimensional data visualization after retrieval.

[0034] Preferably, in S3, a digital twin model based on the substation maintenance operation site is determined, and the following operations are performed:

[0035] According to the multi-dimensional data visualization requirements of substation maintenance operations based on digital twins;

[0036] Pre-set historical multi-dimensional data based on the substation maintenance operation site;

[0037] Store pre-set historical multi-dimensional data based on the substation maintenance operation site;

[0038] Divide the stored pre-set historical multi-dimensional data based on the substation maintenance operation site;

[0039] Determine the training set and test set based on the substation maintenance operation site;

[0040] Choose the right digital twin model architecture;

[0041] Based on the training set, the digital twin model architecture is trained;

[0042] Determine the digital twin model based on the substation maintenance operation site.

[0043] Preferably, in S4, the best digital twin model based on the substation maintenance operation site is determined, and the following operations are performed:

[0044] Obtain a digital twin model based on the substation maintenance operation site;

[0045] Based on the test set, the performance of the digital twin model based on the substation maintenance operation site is tested;

[0046] Determine the performance test results of the digital twin model based on the substation maintenance operation site;

[0047] Mining and analyzing the performance test results of the digital twin model based on the substation maintenance operation site;

[0048] Determine the optimization and adjustment plan of the digital twin model based on the substation maintenance operation site;

[0049] According to the optimization and adjustment plan of the digital twin model based on the substation maintenance operation site, the digital twin model based on the substation maintenance operation site is optimized and adjusted;

[0050] Determine the best digital twin model based on the substation maintenance operation site.

[0051] Preferably, in S5, a 1:1 restoration multi-dimensional data panorama based on the substation maintenance operation site is generated, and the following operations are performed:

[0052] Obtain the best digital twin model based on the substation maintenance operation site;

[0053] Acquire characteristic multi-dimensional data based on the substation maintenance operation site;

[0054] Input the characteristic multi-dimensional data into the digital twin model, simulate the characteristic multi-dimensional data based on the digital twin model, and complete the mapping in the virtual space;

[0055] Generate a 1:1 restored multi-dimensional data panoramic view of the substation maintenance operation site.

[0056] Preferably, in S6, the multidimensional data in the multidimensional data panoramic map based on the substation maintenance operation site with a 1:1 restoration degree is visualized and the following operations are performed:

[0057] Conduct detection and analysis on a 1:1 restored multi-dimensional data panorama based on the substation maintenance operation site;

[0058] The multi-dimensional data in the multi-dimensional data panorama based on the substation maintenance operation site is displayed to the user in a visual form with a 1:1 restoration.

[0059] Preferably, in S6, the 1:1 restoration degree multi-dimensional data panorama based on the substation maintenance operation site is detected, and the following operations are performed:

[0060] Test the 1:1 restored multi-dimensional data panorama based on the substation maintenance operation site;

[0061] Check whether the multi-dimensional data in the multi-dimensional data panorama based on the substation maintenance operation site with a 1:1 restoration degree is abnormal;

[0062] Determine the multi-dimensional data inspection situation based on the multi-dimensional data panorama;

[0063] According to the multi-dimensional data inspection situation based on the multi-dimensional data panorama, the multi-dimensional data of the substation maintenance operation site is intelligently controlled;

[0064] Intelligent management and control of multi-dimensional data at the substation maintenance site, including:

[0065] When the multi-dimensional data check based on the multi-dimensional data panorama is abnormal, a warning will be issued in time, and warning information will be sent to management personnel to intelligently guide management personnel to conduct safety management and control of the substation maintenance operation site.

[0066] Preferably, in S5, after simulating the characteristic multidimensional data based on the digital twin model and completing the mapping in the virtual space, it also includes:

[0067] Based on the digital twin model, the characteristic multi-dimensional data is simulated and mapped in the virtual space to obtain a panoramic view of the current multi-dimensional data;

[0068] Acquire dimension information of the multidimensional data panorama, and read the current multidimensional data panorama according to the dimension information of the multidimensional data panorama to obtain a sub-data panorama corresponding to each dimension;

[0069] Read the reference sub-panoramic frame image, overlap the reference sub-panoramic frame image with the sub-data panorama image, and locate the first key point of the reference sub-panoramic frame image and the second key point of the sub-data panorama image according to the overlapping result, wherein the reference sub-panoramic frame image and the sub-data panorama image are overlapped. Figure 1 One to one, and multiple reference sub-panoramic frame images constitute a reference panorama frame image;

[0070] Obtaining coordinate values ​​of a first key point and a second key point respectively, and calculating the overlap between the reference panoramic frame diagram and the multi-dimensional data panoramic diagram according to the coordinate values ​​of the first key point and the second key point, wherein the first key point and the second key point correspond one to one;

[0071]

[0072] Wherein, H represents the overlap between the reference panoramic frame and the multidimensional data panoramic frame; i represents the serial number of the sub-data panoramic frame or the reference sub-panoramic frame, n represents the total number of the sub-data panoramic frame or the reference sub-panoramic frame; j i Indicates the serial number value of the first key point or the second key point in the i-th sub-data panorama or the reference sub-panorama frame; m i represents the total number of first key points or second key points in the i-th sub-data panorama or reference sub-panorama frame; represents the horizontal coordinate value corresponding to the jth first key point in the i-th reference sub-panoramic frame; represents the horizontal coordinate value corresponding to the jth second key point in the i-th sub-data panorama; Indicates the total coordinate value corresponding to the jth first key point in the i-th reference sub-panoramic frame; Indicates the ordinate value corresponding to the jth second key point in the i-th sub-data panorama;

[0073] Obtaining a target overlap threshold, and comparing the overlap between the reference panoramic frame image and the multidimensional data panoramic image with the target overlap threshold;

[0074] If the overlap between the reference panoramic frame diagram and the multi-dimensional data panoramic diagram is greater than the target overlap threshold, the simulation of the multi-dimensional data panoramic diagram is determined to be qualified;

[0075] Otherwise, the simulation of the multidimensional data panorama is determined to be unqualified, and at the same time, the unqualified sub-data panorama is located, and the coordinate values ​​of unqualified key points in the unqualified sub-data panorama and the coordinate values ​​of the key points of the corresponding reference sub-panorama frame are obtained;

[0076] Calculate the correction coefficient based on the coordinate values ​​of the unqualified key points in the unqualified sub-data panorama and the coordinate values ​​of the key points of the corresponding reference sub-panorama frame image;

[0077] S(x 修正 ,y 修正 )=(x r -x w ,y r -y w );

[0078] Among them, S(x 修正 ,y 修正 ) represents the correction factor; x 修正 Indicates the horizontal coordinate value that needs to be corrected for the unqualified key point; 修正 Indicates the vertical coordinate value that needs to be corrected for the unqualified key point; x w Indicates the horizontal coordinate value of the unqualified key point; x r Indicates the horizontal coordinate value of the key point of the benchmark sub-panoramic frame corresponding to the unqualified key point; w Indicates the ordinate value of the unqualified key point; y r Indicates the vertical coordinate value of the key point of the reference sub-panoramic frame corresponding to the unqualified key point;

[0079] The unqualified sub-data panorama is corrected according to the correction coefficient to generate a multi-dimensional data panorama based on the substation maintenance operation site with a 1:1 restoration degree.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] The present invention determines real-time multidimensional data based on the substation maintenance operation site by collecting real-time building data, real-time equipment data and real-time environmental data of the substation maintenance operation site, determines characteristic multidimensional data based on the substation maintenance operation site by preprocessing the real-time multidimensional data based on the substation maintenance operation site, simulates the characteristic multidimensional data based on the digital twin model, completes mapping in a virtual space, generates a 1:1 restored multidimensional data panoramic map based on the substation maintenance operation site, and visualizes the multidimensional data in the 1:1 restored multidimensional data panoramic map based on the substation maintenance operation site, so as to visualize the multidimensional data of the substation maintenance operation site, timely grasp the multidimensional data situation of the substation maintenance operation site, and improve the substation maintenance effect.

[0082] After completing the mapping in the virtual space, the current multidimensional data panorama is read according to the dimensional information to obtain multiple sub-data panoramas, and the overlap between the sub-data panorama and the benchmark sub-panorama frame is calculated, so that the qualification of the multidimensional data panorama can be effectively judged. If it is unqualified, the unqualified sub-data panorama can be accurately corrected through the correction coefficient, ensuring the 1:1 restoration of the multidimensional data panorama based on the substation maintenance operation site, thereby improving the quality and accuracy of the multidimensional data panorama. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 This is a flow chart of the multi-dimensional data visualization method of the substation maintenance operation site based on digital twin of the present invention. DETAILED DESCRIPTION

[0084] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0085] In order to solve the existing problem that the multi-dimensional data of the substation maintenance operation site cannot be visualized, the multi-dimensional data of the substation maintenance operation site cannot be grasped in time, resulting in poor substation maintenance effect, please refer to Figure 1 , this embodiment provides the following technical solutions:

[0086] The multi-dimensional data visualization method of the substation maintenance operation site based on digital twin includes the following steps:

[0087] S1: Collect real-time building data, real-time equipment data and real-time environmental data at the substation maintenance operation site, and determine real-time multi-dimensional data based on the substation maintenance operation site;

[0088] In this embodiment, as a preferred technical solution of the present invention, real-time multi-dimensional data based on the substation maintenance operation site is determined, and the following operations are performed:

[0089] Collect the construction conditions at the substation maintenance site in real time and determine the real-time construction data based on the substation maintenance site;

[0090] Collect the equipment conditions at the substation maintenance site in real time and determine the real-time equipment data based on the substation maintenance site;

[0091] Collect the environmental conditions of the substation maintenance operation site in real time and determine the real-time environmental data based on the substation maintenance operation site;

[0092] Among them, based on the collected real-time building data, real-time equipment data and real-time environmental data, real-time multi-dimensional data based on the substation maintenance operation site is determined.

[0093] S2: pre-processing the real-time multi-dimensional data based on the substation maintenance operation site to determine the characteristic multi-dimensional data based on the substation maintenance operation site;

[0094] In this embodiment, as a preferred technical solution of the present invention, the real-time multi-dimensional data based on the substation maintenance operation site is preprocessed, and the following operations are performed:

[0095] Obtain real-time multi-dimensional data based on the substation maintenance operation site;

[0096] Based on the sequential retrieval method, the real-time multi-dimensional data based on the substation maintenance operation site is retrieved;

[0097] Identify real-time multidimensional data that is valuable for multidimensional data visualization after retrieval;

[0098] Obtaining real-time multidimensional data that is valuable for multidimensional data visualization after retrieval;

[0099] Based on the internal sorting method, the retrieved real-time multidimensional data which is valuable for multidimensional data visualization is sorted;

[0100] Divide the retrieved real-time multidimensional data that is valuable for multidimensional data visualization into multiple subsets, sort each subset, and integrate multiple subsets;

[0101] Determine sorted real-time multi-dimensional data with an arrangement order;

[0102] Obtain sorted and ordered real-time multi-dimensional data;

[0103] Extract features from the sorted real-time multi-dimensional data with arrangement order;

[0104] Determine the characteristic multi-dimensional data based on the substation maintenance operation site.

[0105] In this embodiment, as a preferred technical solution of the present invention, the real-time multi-dimensional data based on the substation maintenance operation site is retrieved, and the following operations are performed:

[0106] Obtain real-time multi-dimensional data based on the substation maintenance operation site;

[0107] Check the consistency of real-time multi-dimensional data based on the substation maintenance operation site;

[0108] Remove data that is beyond the normal range, logically unreasonable or contradictory in the real-time multi-dimensional data based on the substation maintenance operation site;

[0109] Determine real-time multi-dimensional data with data consistency;

[0110] Process invalid and missing values ​​for real-time multidimensional data with data consistency;

[0111] Remove invalid data and missing data that are not valuable for multidimensional data visualization contained in real-time multidimensional data with data consistency;

[0112] Identify real-time multidimensional data that is valuable for multidimensional data visualization after retrieval.

[0113] S3: Based on the training set, the digital twin model architecture is trained to determine the digital twin model based on the substation maintenance operation site;

[0114] In this embodiment, as a preferred technical solution of the present invention, a digital twin model based on the substation maintenance operation site is determined, and the following operations are performed:

[0115] According to the multi-dimensional data visualization requirements of substation maintenance operations based on digital twins;

[0116] Pre-set historical multi-dimensional data based on the substation maintenance operation site;

[0117] Store pre-set historical multi-dimensional data based on the substation maintenance operation site;

[0118] Obtain the stored pre-set historical multi-dimensional data based on the substation maintenance operation site;

[0119] Divide the stored pre-set historical multi-dimensional data based on the substation maintenance operation site;

[0120] Determine the training set and test set based on the substation maintenance operation site;

[0121] Choose the right digital twin model architecture;

[0122] Based on the training set, the digital twin model architecture is trained;

[0123] Determine the digital twin model based on the substation maintenance operation site.

[0124] S4: Perform performance testing and optimization on the digital twin model based on the substation maintenance operation site to determine the best digital twin model based on the substation maintenance operation site;

[0125] In this embodiment, as a preferred technical solution of the present invention, the best digital twin model based on the substation maintenance operation site is determined, and the following operations are performed:

[0126] Obtain a digital twin model based on the substation maintenance operation site;

[0127] Based on the test set, the performance of the digital twin model based on the substation maintenance operation site is tested;

[0128] Determine the performance test results of the digital twin model based on the substation maintenance operation site;

[0129] Mining and analyzing the performance test results of the digital twin model based on the substation maintenance operation site;

[0130] Determine the optimization and adjustment plan of the digital twin model based on the substation maintenance operation site;

[0131] According to the optimization and adjustment plan of the digital twin model based on the substation maintenance operation site, the digital twin model based on the substation maintenance operation site is optimized and adjusted;

[0132] Determine the best digital twin model based on the substation maintenance operation site.

[0133] S5: Based on the digital twin model, simulate the characteristic multi-dimensional data, complete the mapping in the virtual space, and generate a 1:1 restoration of the multi-dimensional data panorama based on the substation maintenance operation site;

[0134] In this embodiment, as a preferred technical solution of the present invention, a 1:1 restoration multi-dimensional data panorama based on the substation maintenance operation site is generated, and the following operations are performed:

[0135] Obtain the best digital twin model based on the substation maintenance operation site;

[0136] Acquire characteristic multi-dimensional data based on the substation maintenance operation site;

[0137] Input the characteristic multi-dimensional data into the digital twin model, simulate the characteristic multi-dimensional data based on the digital twin model, and complete the mapping in the virtual space;

[0138] Generate a 1:1 restored multi-dimensional data panoramic view of the substation maintenance operation site.

[0139] S6: Visualize the multidimensional data in the multidimensional data panorama based on the substation maintenance operation site with a 1:1 restoration degree.

[0140] In this embodiment, as a preferred technical solution of the present invention, the multi-dimensional data in the multi-dimensional data panorama based on the substation maintenance operation site with a 1:1 restoration degree is visualized and displayed, and the following operations are performed:

[0141] Obtain a 1:1 restored multi-dimensional data panorama based on the substation maintenance operation site;

[0142] Conduct detection and analysis on a 1:1 restored multi-dimensional data panorama based on the substation maintenance operation site;

[0143] The multi-dimensional data in the multi-dimensional data panorama based on the substation maintenance operation site is displayed to the user in a visual form with a 1:1 restoration.

[0144] In this embodiment, as a preferred technical solution of the present invention, a 1:1 restoration degree multi-dimensional data panorama based on the substation maintenance operation site is detected, and the following operations are performed:

[0145] Obtain a 1:1 restored multi-dimensional data panorama based on the substation maintenance operation site;

[0146] Test the 1:1 restored multi-dimensional data panorama based on the substation maintenance operation site;

[0147] Check whether the multi-dimensional data in the multi-dimensional data panorama based on the substation maintenance operation site with a 1:1 restoration degree is abnormal;

[0148] Determine the multi-dimensional data inspection situation based on the multi-dimensional data panorama;

[0149] According to the multi-dimensional data inspection results based on the multi-dimensional data panorama, the multi-dimensional data at the substation maintenance operation site is intelligently managed and controlled.

[0150] In this embodiment, as a preferred technical solution of the present invention, intelligent management and control of multi-dimensional data at the substation maintenance operation site includes:

[0151] When the multi-dimensional data check based on the multi-dimensional data panorama is abnormal, a warning will be issued in time, and warning information will be sent to management personnel to intelligently guide management personnel to conduct safety management and control of the substation maintenance operation site.

[0152] Therefore, by collecting real-time building data, real-time equipment data and real-time environmental data of the substation maintenance operation site, the real-time multidimensional data based on the substation maintenance operation site is determined, and by preprocessing the real-time multidimensional data based on the substation maintenance operation site, the characteristic multidimensional data based on the substation maintenance operation site is determined, and the characteristic multidimensional data is simulated based on the digital twin model, and the mapping is completed in the virtual space to generate a 1:1 restoration of the multidimensional data panorama based on the substation maintenance operation site, and the multidimensional data in the 1:1 restoration of the multidimensional data panorama based on the substation maintenance operation site is visualized, so that the multidimensional data of the substation maintenance operation site can be visualized, the multidimensional data situation of the substation maintenance operation site can be grasped in time, and the substation maintenance effect can be improved.

[0153] In this embodiment S5, after simulating the characteristic multi-dimensional data based on the digital twin model and completing the mapping in the virtual space, it also includes:

[0154] Based on the digital twin model, the characteristic multi-dimensional data is simulated and mapped in the virtual space to obtain a panoramic view of the current multi-dimensional data;

[0155] Acquire dimension information of the multidimensional data panorama, and read the current multidimensional data panorama according to the dimension information of the multidimensional data panorama to obtain a sub-data panorama corresponding to each dimension;

[0156] Read the reference sub-panoramic frame image, overlap the reference sub-panoramic frame image with the sub-data panorama image, and locate the first key point of the reference sub-panoramic frame image and the second key point of the sub-data panorama image according to the overlapping result, wherein the reference sub-panoramic frame image and the sub-data panorama image are overlapped. Figure 1 One to one, and multiple reference sub-panoramic frame images constitute a reference panorama frame image;

[0157] Obtaining coordinate values ​​of a first key point and a second key point respectively, and calculating the overlap between the reference panoramic frame diagram and the multi-dimensional data panoramic diagram according to the coordinate values ​​of the first key point and the second key point, wherein the first key point and the second key point correspond one to one;

[0158]

[0159] Wherein, H represents the overlap between the reference panoramic frame and the multidimensional data panoramic frame; i represents the serial number of the sub-data panoramic frame or the reference sub-panoramic frame, n represents the total number of the sub-data panoramic frame or the reference sub-panoramic frame; j i Indicates the serial number value of the first key point or the second key point in the i-th sub-data panorama or the reference sub-panorama frame; m i represents the total number of first key points or second key points in the i-th sub-data panorama or reference sub-panorama frame; represents the horizontal coordinate value corresponding to the jth first key point in the i-th reference sub-panoramic frame; represents the horizontal coordinate value corresponding to the jth second key point in the i-th sub-data panorama; Indicates the total coordinate value corresponding to the jth first key point in the i-th reference sub-panoramic frame; Indicates the ordinate value corresponding to the jth second key point in the i-th sub-data panorama;

[0160] Obtaining a target overlap threshold, and comparing the overlap between the reference panoramic frame image and the multidimensional data panoramic image with the target overlap threshold;

[0161] If the overlap between the reference panoramic frame diagram and the multidimensional data panoramic diagram is greater than the target overlap threshold, the simulation of the multidimensional data panoramic diagram is determined to be qualified;

[0162] Otherwise, the simulation of the multidimensional data panorama is determined to be unqualified, and at the same time, the unqualified sub-data panorama is located, and the coordinate values ​​of unqualified key points in the unqualified sub-data panorama and the coordinate values ​​of key points of the corresponding reference sub-panorama frame are obtained;

[0163] Calculate the correction coefficient based on the coordinate values ​​of the unqualified key points in the unqualified sub-data panorama and the coordinate values ​​of the key points of the corresponding reference sub-panorama frame image;

[0164] S(x 修正 ,y 修正 )=(x r -x w ,y r -y w );

[0165] Among them, S(x 修正 ,y 修正 ) represents the correction factor; x 修正 Indicates the horizontal coordinate value that needs to be corrected for the unqualified key point; 修正 Indicates the vertical coordinate value that needs to be corrected for the unqualified key point; x w Indicates the horizontal coordinate value of the unqualified key point; x r Indicates the horizontal coordinate value of the key point of the benchmark sub-panoramic frame corresponding to the unqualified key point; w Indicates the ordinate value of the unqualified key point; y r Indicates the vertical coordinate value of the key point of the reference sub-panoramic frame corresponding to the unqualified key point;

[0166] The unqualified sub-data panorama is corrected according to the correction coefficient to generate a multi-dimensional data panorama based on the substation maintenance operation site with a 1:1 restoration degree.

[0167] In this embodiment, the reference sub-panoramic frame diagram may be a pre-set basic framework including a multi-dimensional data panorama diagram.

[0168] In this embodiment, the target overlap threshold may be set in advance and used to measure whether the multi-dimensional data panoramic image simulation is qualified.

[0169] In this embodiment, the correction of the unqualified sub-data panorama according to the correction coefficient can be based on S(x 修正 ,y 修正 ) 修正 With y 修正 The positive or negative value determines the correction direction, such as x 修正 When it is positive, it moves to the right along the coordinate system. 修正 With y 修正 The value of determines the size of the correction.

[0170] In this embodiment, the dimensional information includes real-time building data, real-time equipment data, and real-time environment data.

[0171] The working principle and beneficial effects of the above technical solution are: after completing the mapping in the virtual space, the current multidimensional data panorama is read according to the dimensional information, so as to obtain multiple sub-data panoramas, and by calculating the overlap between the sub-data panorama and the benchmark sub-panorama frame diagram, the qualification of the multidimensional data panorama is effectively judged. When it is unqualified, the unqualified sub-data panorama is accurately corrected through the correction coefficient, thereby ensuring the 1:1 restoration of the multidimensional data panorama based on the substation maintenance operation site, thereby improving the quality and accuracy of the multidimensional data panorama.

[0172] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0173] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-dimensional data visualization method for substation maintenance operation site based on digital twin, characterized in that: The steps include: S1: Collect real-time building data, real-time equipment data and real-time environmental data at the substation maintenance operation site to determine real-time multi-dimensional data; S2: preprocessing the real-time multi-dimensional data to determine characteristic multi-dimensional data; S3: Based on the training set, the digital twin model architecture is trained to determine the digital twin model; S4: Performing performance testing and optimization adjustment on the digital twin model to determine the best digital twin model; S5: simulating the characteristic multidimensional data based on the optimal digital twin model, completing the mapping in the virtual space, and generating a 1:1 restoration panoramic view of the multidimensional data; S6: Visually display the multidimensional data in the multidimensional data panorama with a 1:1 restoration degree; In S5, after the feature multi-dimensional data is simulated based on the digital twin model and mapped in the virtual space, it also includes: Based on the digital twin model, the characteristic multi-dimensional data is simulated and mapped in the virtual space to obtain a panoramic view of the current multi-dimensional data; Acquire dimension information of the multidimensional data panorama, and read the current multidimensional data panorama according to the dimension information of the multidimensional data panorama to obtain a sub-data panorama corresponding to each dimension; Reading a reference sub-panoramic frame image, overlapping the reference sub-panoramic frame image with the sub-data panorama image, and locating a first key point of the reference sub-panoramic frame image and a second key point of the sub-data panorama image according to the overlapping result, wherein the reference sub-panoramic frame image corresponds to the sub-data panorama image one-to-one, and a plurality of reference sub-panoramic frame images constitute the reference panorama frame image; Obtaining coordinate values ​​of a first key point and a second key point respectively, and calculating the overlap between the reference panoramic frame diagram and the multi-dimensional data panoramic diagram according to the coordinate values ​​of the first key point and the second key point, wherein the first key point and the second key point correspond one to one; Wherein, H represents the overlap between the reference panoramic frame and the multidimensional data panoramic frame; i represents the serial number of the sub-data panoramic frame or the reference sub-panoramic frame, n represents the total number of the sub-data panoramic frame or the reference sub-panoramic frame; j i Indicates the serial number value of the first key point or the second key point in the i-th sub-data panorama or the reference sub-panorama frame; m i represents the total number of first key points or second key points in the i-th sub-data panorama or reference sub-panorama frame; x 1ji represents the horizontal coordinate value corresponding to the jth first key point in the i-th reference sub-panoramic frame; 2ji y represents the horizontal coordinate value corresponding to the jth second key point in the i-th sub-data panorama; 1ji represents the total coordinate value corresponding to the jth first key point in the i-th reference sub-panoramic frame; 2ji Indicates the ordinate value corresponding to the jth second key point in the i-th sub-data panorama; Obtaining a target overlap threshold, and comparing the overlap between the reference panoramic frame image and the multidimensional data panoramic image with the target overlap threshold; If the overlap between the reference panoramic frame diagram and the multi-dimensional data panoramic diagram is greater than the target overlap threshold, the simulation of the multi-dimensional data panoramic diagram is determined to be qualified; Otherwise, the simulation of the multidimensional data panorama is determined to be unqualified, and at the same time, the unqualified sub-data panorama is located, and the coordinate values ​​of unqualified key points in the unqualified sub-data panorama and the coordinate values ​​of the key points of the corresponding reference sub-panorama frame are obtained; Calculate the correction coefficient based on the coordinate values ​​of the unqualified key points in the unqualified sub-data panorama and the coordinate values ​​of the key points of the corresponding reference sub-panorama frame image; S(x 修正 ,and 修正 )=(x r -x w ,and r -and w ); Among them, S(x 修正 ,y 修正 ) represents the correction factor; x 修正 Indicates the horizontal coordinate value that needs to be corrected for the unqualified key point; 修正 Indicates the vertical coordinate value that needs to be corrected for the unqualified key point; x w Indicates the horizontal coordinate value of the unqualified key point; x r Indicates the horizontal coordinate value of the key point of the benchmark sub-panoramic frame corresponding to the unqualified key point; w Indicates the ordinate value of the unqualified key point; y r Indicates the vertical coordinate value of the key point of the reference sub-panoramic frame corresponding to the unqualified key point; The unqualified sub-data panorama is corrected according to the correction coefficient to generate a multi-dimensional data panorama based on the substation maintenance operation site with a 1:1 restoration degree.

2. The multidimensional data visualization method for substation maintenance operation site based on digital twin according to claim 1 is characterized in that: In S1, real-time multi-dimensional data is determined, and the following operations are performed: Collect the construction conditions of the substation maintenance site in real time and determine the real-time construction data; Collect the equipment status of the substation maintenance operation site in real time and determine the real-time equipment data; Collect the environmental conditions of the substation maintenance site in real time and determine the real-time environmental data; Among them, real-time multi-dimensional data based on the substation maintenance operation site is determined based on real-time building data, real-time equipment data and real-time environmental data.

3. The multidimensional data visualization method for substation maintenance operation site based on digital twin according to claim 2 is characterized in that: In S2, the real-time multi-dimensional data is pre-processed to determine feature multi-dimensional data, and the following operations are performed: Retrieve real-time multidimensional data based on sequential retrieval method; Identify real-time multidimensional data that is valuable for multidimensional data visualization; Sort the real-time multidimensional data that is valuable for multidimensional data visualization based on the internal sorting method; Divide the real-time multidimensional data that is valuable for multidimensional data visualization into multiple subsets, integrate the multiple subsets, and sort each subset; Determine real-time multi-dimensional data with sorting order; Extract features from real-time multi-dimensional data with arrangement order; Determine the characteristic multi-dimensional data based on the substation maintenance operation site.

4. The multidimensional data visualization method for substation maintenance operation site based on digital twin according to claim 3 is characterized in that: In S2, the real-time multi-dimensional data based on the substation maintenance operation site is retrieved, and the following operations are performed: Check the consistency of real-time multidimensional data; Remove data that is beyond the normal range, logically unreasonable or contradictory in real-time multi-dimensional data; Determine real-time multi-dimensional data with data consistency; Process invalid and missing values ​​for real-time multidimensional data with data consistency; Remove invalid data and missing data that are not valuable for multidimensional data visualization contained in real-time multidimensional data with data consistency; Identify real-time multidimensional data that is valuable for multidimensional data visualization after retrieval.

5. The multi-dimensional data visualization method for substation maintenance operation site based on digital twin according to claim 4 is characterized in that: In S3, a digital twin model based on the substation maintenance operation site is determined, and the following operations are performed: According to the multi-dimensional data visualization requirements of substation maintenance operations based on digital twins; Pre-set historical multi-dimensional data based on the substation maintenance operation site; Store pre-set historical multi-dimensional data based on the substation maintenance operation site; Divide the stored pre-set historical multi-dimensional data based on the substation maintenance operation site; Determine the training set and test set based on the substation maintenance operation site; Choose the right digital twin model architecture; Based on the training set, the digital twin model architecture is trained; Determine the digital twin model based on the substation maintenance operation site.

6. The multi-dimensional data visualization method for substation maintenance operation site based on digital twin according to claim 5 is characterized in that: In S4, the best digital twin model based on the substation maintenance operation site is determined, and the following operations are performed: Obtain a digital twin model based on the substation maintenance operation site; Based on the test set, the performance of the digital twin model based on the substation maintenance operation site is tested; Determine the performance test results of the digital twin model based on the substation maintenance operation site; Mining and analyzing the performance test results of the digital twin model based on the substation maintenance operation site; Determine the optimization and adjustment plan of the digital twin model based on the substation maintenance operation site; According to the optimization and adjustment plan of the digital twin model based on the substation maintenance operation site, the digital twin model based on the substation maintenance operation site is optimized and adjusted; Determine the best digital twin model based on the substation maintenance operation site.

7. The multi-dimensional data visualization method for substation maintenance operation site based on digital twin according to claim 6 is characterized in that: In S5, a 1:1 restoration multi-dimensional data panorama based on the substation maintenance operation site is generated, and the following operations are performed: Obtain the best digital twin model based on the substation maintenance operation site; Acquire characteristic multi-dimensional data based on the substation maintenance operation site; Input the characteristic multi-dimensional data into the digital twin model, simulate the characteristic multi-dimensional data based on the digital twin model, and complete the mapping in the virtual space; Generate a 1:1 restored multi-dimensional data panoramic view of the substation maintenance operation site.

8. The multi-dimensional data visualization method for substation maintenance operation site based on digital twin according to claim 7 is characterized in that: In S6, the multi-dimensional data in the multi-dimensional data panorama based on the substation maintenance operation site with a 1:1 restoration degree is visualized and the following operations are performed: Conduct detection and analysis on a 1:1 restored multi-dimensional data panorama based on the substation maintenance operation site; The multi-dimensional data in the multi-dimensional data panorama based on the substation maintenance operation site is displayed to the user in a visual form with a 1:1 restoration.

9. The multi-dimensional data visualization method for substation maintenance operation site based on digital twin according to claim 8 is characterized in that: In S6, the 1:1 restoration degree multi-dimensional data panorama based on the substation maintenance operation site is detected, and the following operations are performed: Test the 1:1 restored multi-dimensional data panorama based on the substation maintenance operation site; Check whether the multi-dimensional data in the multi-dimensional data panorama based on the substation maintenance operation site with a 1:1 restoration degree is abnormal; Determine the multi-dimensional data inspection situation based on the multi-dimensional data panorama; According to the multi-dimensional data inspection situation based on the multi-dimensional data panorama, the multi-dimensional data of the substation maintenance operation site is intelligently controlled; Intelligent management and control of multi-dimensional data at the substation maintenance site, including: When the multi-dimensional data check based on the multi-dimensional data panorama is abnormal, a warning will be issued in time, and warning information will be sent to management personnel to intelligently guide management personnel to conduct safety management and control of the substation maintenance operation site.

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