Oil pressure transformer state evaluation method and system based on big data analysis
By using big data analytics and edge detection algorithms to generate information on the core and total thermal zones of a transformer, the safety hazards caused by relying on manual inspection for transformer condition monitoring are solved, enabling rapid and accurate condition assessment and fault prevention.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- WUHU POWER SUPPLY COMPANY OF STATE GRID ANHUI ELECTRIC POWER
- Filing Date
- 2025-12-17
- Publication Date
- 2026-04-14
AI Technical Summary
Current transformer condition monitoring relies on manual inspections at fixed intervals, which leads to continuous operation under fault conditions and poses a high risk of safety hazards.
By employing a big data analytics approach, real-time and historical heat map information of the transformer is obtained, and edge detection algorithms are used to generate core and total heat area information to determine the transformer's condition assessment information.
It enables rapid and accurate transformer condition assessment, avoids continuous operation under fault conditions, reduces safety hazards, and minimizes equipment damage.
Smart Images
Figure CN121860944A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of intelligent monitoring, and more specifically, to a condition assessment method and system for hydraulic transformers based on big data analysis. Background Technology
[0002] A transformer is an electrical device mainly used for the transmission and conversion of electrical energy. Its basic principle is to convert voltage from one circuit to another through electromagnetic induction, that is, to convert high voltage to low voltage or low voltage to high voltage, in order to meet different power demands.
[0003] Currently, transformer condition monitoring mainly relies on manual inspections at fixed intervals. This method not only easily leads to the transformer continuing to operate under fault conditions, but may also cause further damage to the transformer, posing a significant safety hazard and requiring further improvement. Summary of the Invention
[0004] Based on this, this application provides a method and system for assessing the condition of hydraulic transformers based on big data analysis, in order to solve the problem of high safety hazards in the prior art.
[0005] In a first aspect, embodiments of this application provide a condition assessment method for hydraulic transformers based on big data analysis, the method comprising: Obtain real-time and historical normal thermal map information of the target transformer; Based on the real-time heat map information and the preset edge detection algorithm, first core region information and first total heat region information are generated, and based on the historical normal heat map information and the edge detection algorithm, second core region information and second total heat region information are generated. Based on the information of the first core area, the information of the first total thermal area, the information of the second core area, and the information of the second total thermal area, the status assessment information of the target transformer is determined.
[0006] Compared with existing technologies, the beneficial effects are as follows: The hydraulic transformer condition assessment method based on big data analysis provided in this application allows the terminal device to first obtain real-time thermal map information and historical normal thermal map information of the target transformer. Then, based on the real-time thermal map information and a preset edge detection algorithm, it quickly generates first core area information and first total thermal area information. Simultaneously, based on the historical normal thermal map information and the edge detection algorithm, it quickly generates second core area information and second total thermal area information. Finally, based on the first core area information, first total thermal area information, second core area information, and second total thermal area information, it accurately determines the condition assessment information of the target transformer. This avoids the situation where the transformer continues to operate under fault conditions and avoids the situation where a faulty transformer is further damaged due to continued operation, effectively reducing safety hazards and solving the problem of high safety hazards to a certain extent.
[0007] Secondly, embodiments of this application provide a condition assessment system for hydraulic transformers based on big data analysis, the system comprising: Real-time heat map information acquisition module: used to acquire real-time heat map information and historical normal heat map information of the target transformer; Core area information generation module: used to generate first core area information and first total heat area information based on the real-time heat map information and the preset edge detection algorithm, and to generate second core area information and second total heat area information based on the historical normal heat map information and the edge detection algorithm; Status assessment information determination module: used to determine the status assessment information of the target transformer based on the first core area information, the first total thermal area information, the second core area information, and the second total thermal area information.
[0008] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.
[0009] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.
[0010] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description
[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.
[0012] Figure 1 This is a schematic flowchart of a state assessment method provided in an embodiment of this application; Figure 2 This is a flowchart illustrating step S200 in a state assessment method provided in an embodiment of this application; Figure 3 This is a flowchart illustrating step S300 in a state assessment method provided in an embodiment of this application; Figure 4 This is a schematic diagram of the first process after step S300 in a state assessment method provided in an embodiment of this application; Figure 5 This is a schematic diagram of the second process after step S300 in a state assessment method provided in an embodiment of this application; Figure 6 This is a block diagram of a state assessment system provided in an embodiment of this application; Figure 7 This is a schematic diagram of a terminal device provided in an embodiment of this application. Detailed Implementation
[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.
[0014] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0015] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.
[0016] To illustrate the technical solution described in this application, specific embodiments are provided below.
[0017] Please see Figure 1 , Figure 1 This is a flowchart illustrating the condition assessment method for hydraulic transformers based on big data analysis provided in this application embodiment. In this embodiment, the execution subject of the condition assessment method is a terminal device. It is understood that the types of terminal devices include, but are not limited to, mobile phones, tablets, laptops, Ultra-Mobile Personal Computers (UMPCs), netbooks, Personal Digital Assistants (PDAs), etc. This application embodiment does not impose any restrictions on the specific type of terminal device.
[0018] Please see Figure 1 The state assessment method provided in this application includes, but is not limited to, the following steps: In S100, real-time thermal map information and historical normal thermal map information of the target transformer are obtained.
[0019] Specifically, the terminal device can first use a preset thermal imaging device to obtain real-time thermal map information and historical normal thermal map information of the target transformer. The real-time thermal map information is used to describe the thermal map generated in real time for the target transformer; the historical normal thermal map information is used to describe the thermal map generated for the target transformer in normal operation in the past; the thermal map is an image that uses color depth to represent numerical intensity.
[0020] In S200, based on real-time heat map information and a preset edge detection algorithm, first core region information and first total heat region information are generated, and based on historical normal heat map information and edge detection algorithm, second core region information and second total heat region information are generated.
[0021] Specifically, after the terminal device acquires real-time heat map information and historical normal heat map information, it can quickly generate first core area information and first total heat map information based on the real-time heat map information and the preset edge detection algorithm. At the same time, it can quickly generate second core area information and second total heat map information based on the historical normal heat map information and the edge detection algorithm.
[0022] For information on possible implementations and to help mitigate potential security risks, please refer to [link / reference]. Figure 2 Step S200 includes, but is not limited to, the following steps: In S210, based on a preset edge detection algorithm, edge detection processing is performed on the real-time heat map information to generate multiple first edge line information.
[0023] Specifically, the terminal device can perform edge detection processing on the real-time heat map information based on a preset edge detection algorithm to generate multiple first edge line information. The edge detection algorithm can be an edge detection algorithm based on the Sobel operator or an edge detection algorithm based on the Laplace operator.
[0024] In S220, the information of the first closed hot zone is determined based on the information of the first edge line.
[0025] Specifically, after the terminal device generates multiple first edge line information, the terminal device can efficiently determine the first closed hot zone information based on the first edge line information. The first closed hot zone information is used to describe the area composed of the closed first edge line information, that is, the closed area enclosed by the first edge line information.
[0026] In S230, the information of the first total thermal zone is determined based on the information of the outermost first closed thermal zone, and the information of the first core zone is determined based on the information of the innermost first closed thermal zone.
[0027] Specifically, after the terminal device determines the information of the first enclosed hot zone, the terminal device can determine the information of the outermost first enclosed hot zone as the information of the first total thermal area, and at the same time determine the information of the innermost first enclosed hot zone as the information of the first core area.
[0028] In S240, based on the edge detection algorithm, edge detection processing is performed on historical normal heat map information to generate multiple second edge line information.
[0029] Specifically, after the terminal device determines the information of the first total thermal area and the information of the first core area, the terminal device can perform edge detection processing on the historical normal thermal map information based on the edge detection algorithm to generate multiple second edge line information.
[0030] In S250, the information of the second closed hot zone is determined based on the information of the second edge line.
[0031] Specifically, after the terminal device generates multiple second edge line information, the terminal device can effectively determine the second closed hot zone information based on the second edge line information. The second closed hot zone information is used to describe the area composed of closed second edge line information, that is, the closed area enclosed by the second edge line information.
[0032] In S260, the information of the second total thermal zone is determined based on the information of the outermost second closed thermal zone, and the information of the second core zone is determined based on the information of the innermost second closed thermal zone.
[0033] Specifically, after the terminal device determines the information of the second enclosed hot zone, the terminal device can determine the information of the outermost second enclosed hot zone as the information of the second total thermal zone, and at the same time determine the information of the innermost second enclosed hot zone, and determine the information of the second core area.
[0034] In S300, the state assessment information of the target transformer is determined based on the information of the first core area, the information of the first total thermal area, the information of the second core area, and the information of the second total thermal area.
[0035] Specifically, after the terminal device generates the first core area information, the first total thermal area information, the second core area information, and the second total thermal area information, the terminal device can accurately determine the status assessment information of the target transformer based on the first core area information, the first total thermal area information, the second core area information, and the second total thermal area information. The status assessment information is normal status information, ordinary abnormal status information, or severe abnormal status information.
[0036] In some possible implementations, for accurate determination of the target transformer's condition assessment information, please refer to [link / reference needed]. Figure 3 Step S300 includes, but is not limited to, the following steps: In S310, based on a preset grayscale conversion algorithm, the average grayscale value of the first region is determined according to the information of the first core region, and based on the grayscale conversion algorithm, the average grayscale value of the second region is determined according to the information of the second core region.
[0037] Specifically, the terminal device can perform grayscale processing on the information of the first core area based on a preset grayscale conversion algorithm to determine the average grayscale value of the first area. At the same time, it can perform grayscale processing on the information of the second core area based on the same grayscale conversion algorithm to determine the average grayscale value of the second area. The average grayscale value of the first area is used to describe the average grayscale value of the information of the first core area, and the average grayscale value of the second area is used to describe the average grayscale value of the information of the second core area.
[0038] In S320, based on a preset grid division method, the area information of the first region is determined according to the information of the first total thermal region, and based on the grid division method, the area information of the second region is determined according to the information of the second total thermal region.
[0039] Specifically, after the terminal device determines the average grayscale value information of the first region and the average grayscale value information of the second region, the terminal device can divide the first total thermal region information based on a preset grid division method, then calculate the area of each divided grid and the sum of the areas to quickly determine the area information of the first region. At the same time, based on the grid division method, the terminal device can divide the second total thermal region information, then calculate the area of each divided grid and the sum of the areas to quickly determine the area information of the second region.
[0040] In S330, it is determined whether the average gray value of the first region is less than the average gray value of the second region, and whether the area of the first region is greater than the area of the second region.
[0041] Specifically, after the terminal device determines the area information of the first region and the area information of the second region, the terminal device can determine whether the average gray value of the first region is less than the average gray value of the second region, and whether the area information of the first region is greater than the area information of the second region.
[0042] In S340, if the average gray value of the first region is less than the average gray value of the second region, and the area of the first region is greater than the area of the second region, then a severe abnormal state information is generated.
[0043] Specifically, if the average gray value of the first region is less than the average gray value of the second region, and the area of the first region is greater than the area of the second region, the terminal device can generate a severe abnormal status information.
[0044] In S350, if the average gray value of the first region is greater than the average gray value of the second region, and the area of the first region is less than the area of the second region, then ordinary abnormal status information is generated; otherwise, normal status information is generated.
[0045] Specifically, if the average gray value of the first region is greater than the average gray value of the second region, and the area of the first region is less than the area of the second region, the terminal device can generate normal abnormal status information; otherwise, the terminal device can generate normal status information.
[0046] In some possible implementations, to facilitate maintenance personnel in analyzing the causes and conditions of target transformer failures, please refer to [link / reference needed]. Figure 4 After step S300, the method further includes, but is not limited to, the following steps: In the S400, real-time image information of the target transformer is acquired based on a preset camera.
[0047] Specifically, after the terminal device determines the status assessment information of the target transformer, the terminal device can acquire real-time captured image information of the target transformer based on a preset camera. The real-time captured image information is used to describe the graphic obtained by capturing the target transformer; the capture time of the real-time captured image information is the same as the capture time of the real-time heat map information.
[0048] In S410, if the status assessment information is severe abnormal status information or ordinary abnormal status information, the target associated area information is determined based on the first core area information and the real-time captured image information.
[0049] Specifically, if the status assessment information is severe abnormal status information or ordinary abnormal status information, the terminal device can determine the target associated region information based on the first core region information and the real-time captured image information. The target associated region information is used to describe the corresponding position of the first core region information in the real-time captured image information.
[0050] In S420, based on real-time captured image information, the target-related region information is processed to generate cropped image block information.
[0051] Specifically, after the terminal device determines the target associated region information, the terminal device can perform cropping processing on the target associated region information based on the real-time captured image information, and extract the target associated region information from the real-time captured image information to generate cropped image block information.
[0052] In S430, core image data packet information is generated based on the captured image patch information and real-time heat map information.
[0053] Specifically, after the terminal device generates the captured image block information, it can effectively generate core image data packet information based on the captured image block information and the real-time heat map information. The core image data packet information is used to describe the data packet that combines the captured image block information and the real-time heat map information.
[0054] In some possible implementations, to further facilitate maintenance personnel in analyzing the causes and conditions of target transformer failures, please refer to [link / reference needed]. Figure 5 If the status assessment information is ordinary abnormal status information or severe abnormal status information, then after step S300, the method further includes, but is not limited to, the following steps: In S500, the average gray value information and area information of the third region corresponding to multiple historical abnormal heat map information are obtained.
[0055] Specifically, the terminal device can obtain the average gray value information and area information of the third region corresponding to multiple historical abnormal heat map information.
[0056] In S510, the first similar heat map information is determined based on the average gray value information of the first region and the average gray value information of the third region corresponding to multiple historical abnormal heat map information.
[0057] Specifically, after the terminal device obtains the average gray value information and the area information of the third region, the terminal device can effectively determine the first similar heat map information based on the average gray value information of the first region and the average gray value information of the third region corresponding to multiple historical abnormal heat map information. The first similar heat map information is used to describe the historical abnormal heat map information corresponding to the average gray value information of the third region that is closest to the average gray value information of the first region.
[0058] In S520, it is determined whether there are multiple first similar heatmap information.
[0059] Specifically, after the terminal device determines the first similar heat map information, the terminal device can determine whether there are multiple first similar heat map information. If there is only one first similar heat map information, the terminal device can determine that the historical fault cause information of the first similar heat map information is maintenance reference information.
[0060] In S530, if there are multiple first similar heat map information, then the second similar heat map information is determined based on the first region area information and the third region area information corresponding to the multiple first similar heat map information.
[0061] Specifically, if there are multiple first similar heatmap information, the terminal device can determine the second similar heatmap information based on the first region area information and the third region area information corresponding to the multiple first similar heatmap information. The second similar heatmap information is used to describe the first similar heatmap information corresponding to the third region area information that is closest to the first region area information.
[0062] In S540, historical fault cause information corresponding to the second similar heat map information is obtained.
[0063] Specifically, after the terminal device determines the second similar heat map information, the terminal device can obtain the historical fault cause information corresponding to the second similar heat map information. The historical fault cause information is used to describe the specific fault of the target transformer when the second similar heat map information was taken. The historical fault cause information can be pre-input by the operation and maintenance personnel.
[0064] In the S550, maintenance reference information is generated based on historical fault cause information.
[0065] Specifically, after the terminal device obtains historical fault cause information, it can generate maintenance reference information based on the historical fault cause information. The maintenance reference information is used to describe data for maintenance personnel to refer to during maintenance.
[0066] The implementation principle of the hydraulic transformer condition assessment method based on big data analysis in this application embodiment is as follows: The terminal device can first obtain the real-time heat map information and historical normal heat map information of the target transformer. Then, based on the real-time heat map information and the preset edge detection algorithm, it quickly generates the first core area information and the first total heat area information. At the same time, based on the historical normal heat map information and the edge detection algorithm, it quickly generates the second core area information and the second total heat area information. Finally, based on the first core area information, the first total heat area information, the second core area information, and the second total heat area information, the condition assessment information of the target transformer is accurately determined, thereby avoiding the situation where the transformer continues to operate in a faulty state, and avoiding the situation where the faulty transformer is further damaged due to continued operation, effectively reducing safety hazards.
[0067] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0068] Embodiments of this application also provide a condition assessment system for hydraulic transformers based on big data analysis. For ease of explanation, only the parts relevant to this application are shown, such as... Figure 6 As shown, the system 60 includes: Real-time heat map information acquisition module 61: used to acquire real-time heat map information and historical normal heat map information of the target transformer; Core area information generation module 62: used to generate first core area information and first total heat area information based on real-time heat map information and preset edge detection algorithm, and to generate second core area information and second total heat area information based on historical normal heat map information and edge detection algorithm; Condition assessment information determination module 63: used to determine the condition assessment information of the target transformer based on the information of the first core area, the information of the first total thermal area, the information of the second core area, and the information of the second total thermal area.
[0069] Optionally, the aforementioned core area information generation module 62 includes: First edge line information generation submodule: Used to perform edge detection processing on real-time heat map information based on a preset edge detection algorithm, and generate multiple first edge line information; First Closed Hot Zone Information Determination Submodule: Used to determine the first closed hot zone information based on the first edge line information, wherein the first closed hot zone information is used to describe the area composed of the closed first edge line information; First core area information determination submodule: used to determine the first total thermal area information based on the information of the outermost first closed thermal zone, and to determine the first core area information based on the information of the innermost first closed thermal zone; Second edge line information generation submodule: Used to perform edge detection processing on historical normal heat map information based on edge detection algorithm to generate multiple second edge line information; The second closed hot zone information determination submodule is used to determine the second closed hot zone information based on the second edge line information, wherein the second closed hot zone information is used to describe the area composed of the closed second edge line information; The second core area information determination submodule is used to determine the second total thermal area information based on the outermost second closed thermal zone information, and to determine the second core area information based on the innermost second closed thermal zone information.
[0070] Optionally, the status assessment information can be normal status information, ordinary abnormal status information, or severe abnormal status information; the aforementioned status assessment information determination module 63 includes: The submodule for determining the average grayscale value of a region is used to determine the average grayscale value of a first region based on a preset grayscale conversion algorithm and the information of a first core region, and to determine the average grayscale value of a second region based on a second core region based on the same grayscale conversion algorithm. The submodule for determining area information is used to determine the area information of the first region based on the first total thermal region information using a preset grid division method, and to determine the area information of the second region based on the second total thermal region information using the same grid division method. The regional average gray value information judgment submodule is used to determine whether the average gray value information of the first region is less than the average gray value information of the second region, and whether the area information of the first region is greater than the area information of the second region. Severe Abnormal State Information Generation Submodule: Used to generate severe abnormal state information if the average gray value of the first region is less than the average gray value of the second region, and the area of the first region is greater than the area of the second region. Normal abnormal status information generation submodule: If the average gray value of the first region is greater than the average gray value of the second region, and the area of the first region is less than the area of the second region, then normal abnormal status information is generated; otherwise, normal status information is generated.
[0071] Optionally, the system 60 also includes: Real-time image acquisition module: used to acquire real-time image information of the target transformer based on a preset camera, wherein the shooting time of the real-time image information is the same as the shooting time of the real-time heat map information; Target-associated region information determination module: If the state assessment information is severe abnormal state information or ordinary abnormal state information, then the target-associated region information is determined based on the first core region information and the real-time captured image information. The target-associated region information is used to describe the corresponding position of the first core region information in the real-time captured image information. Image Patch Information Generation Module: Based on real-time captured image information, this module processes the information of the target-related region to generate image patch information. Core image data packet information generation module: used to generate core image data packet information based on the captured image patch information and real-time heat map information.
[0072] Optionally, if the status assessment information is ordinary abnormal status information or severe abnormal status information, the system 60 further includes: The module for obtaining average gray value information of the third region is used to obtain the average gray value information and area information of the third region corresponding to multiple historical abnormal heat map information. The first similar heatmap information determination module is used to determine the first similar heatmap information based on the average gray value information of the first region and the average gray value information of the third region corresponding to multiple historical abnormal heatmap information. The first similar heatmap information is used to describe the historical abnormal heatmap information corresponding to the average gray value information of the third region that is closest to the average gray value information of the first region. First Similar Heatmap Information Judgment Module: Used to determine whether there are multiple first similar heatmap information items; The second similar heatmap information determination module is used to determine the second similar heatmap information based on the first region area information and the third region area information corresponding to the multiple first similar heatmap information if there are multiple first similar heatmap information. The second similar heatmap information is used to describe the first similar heatmap information corresponding to the third region area information that is closest to the first region area information. Historical fault cause information acquisition module: used to acquire historical fault cause information corresponding to the second similar heat map information; Maintenance reference information generation module: Used to generate maintenance reference information based on historical fault cause information.
[0073] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.
[0074] This application also provides a terminal device, such as... Figure 7 As shown, the terminal device 70 of this embodiment includes: a processor 71, a memory 72, and a computer program 73 stored in the memory 72 and executable on the processor 71. When the processor 71 executes the computer program 73, it implements the steps in the above-described state evaluation method embodiment, for example... Figure 1 Steps S100 to S300 are shown; or, when processor 71 executes computer program 73, it implements the functions of each module in the above-described device, for example... Figure 6 The functions of modules 71 to 73 are shown.
[0075] The terminal device 70 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device, and includes, but is not limited to, a processor 71 and a memory 72. Those skilled in the art will understand that... Figure 7 This is merely an example of terminal device 70 and does not constitute a limitation on terminal device 70. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal device 70 may also include input / output devices, network access devices, buses, etc.
[0076] The processor 71 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or any conventional processor, etc.
[0077] The memory 72 can be an internal storage unit of the terminal device 70, such as the hard disk or memory of the terminal device 70. The memory 72 can also be an external storage device of the terminal device 70, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 70. Furthermore, the memory 72 can include both internal storage units and external storage devices of the terminal device 70. The memory 72 can also store computer program 73 and other programs and data required by the terminal device 70. The memory 72 can also be used to temporarily store data that has been output or will be output.
[0078] One embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.
[0079] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the methods, principles and structures of this application should be covered within the scope of protection of this application.
Claims
1. A condition assessment method for hydraulic transformers based on big data analysis, characterized in that, The method includes: Obtain real-time and historical normal thermal map information of the target transformer; Based on the real-time heat map information and the preset edge detection algorithm, first core region information and first total heat region information are generated, and based on the historical normal heat map information and the edge detection algorithm, second core region information and second total heat region information are generated. Based on the information of the first core area, the information of the first total thermal area, the information of the second core area, and the information of the second total thermal area, the status assessment information of the target transformer is determined.
2. The method according to claim 1, characterized in that, The step of generating first core region information and first total heat region information based on the real-time heat map information and a preset edge detection algorithm, and generating second core region information and second total heat region information based on the historical normal heat map information and the edge detection algorithm, includes: Based on a preset edge detection algorithm, edge detection processing is performed on the real-time heat map information to generate multiple first edge line information; Based on the first edge line information, the first closed hot zone information is determined, wherein the first closed hot zone information is used to describe the region composed of the closed first edge line information; Based on the information of the outermost first closed thermal zone, the information of the first total thermal zone is determined, and based on the information of the innermost first closed thermal zone, the information of the first core zone is determined. Based on the edge detection algorithm, edge detection processing is performed on the historical normal heat map information to generate multiple second edge line information; Based on the second edge line information, second closed hot zone information is determined, wherein the second closed hot zone information is used to describe the region composed of the closed second edge line information; Based on the information of the outermost second enclosed thermal zone, the information of the second total thermal zone is determined, and based on the information of the innermost second enclosed thermal zone, the information of the second core zone is determined.
3. The method according to claim 1, characterized in that, The status assessment information is normal status information, ordinary abnormal status information, or severe abnormal status information; determining the status assessment information of the target transformer based on the first core area information, the first total thermal area information, the second core area information, and the second total thermal area information includes: Based on the preset grayscale conversion algorithm, the average grayscale value of the first region is determined according to the information of the first core region, and based on the grayscale conversion algorithm, the average grayscale value of the second region is determined according to the information of the second core region. Based on a preset grid division method, the area information of the first region is determined according to the first total thermal region information, and the area information of the second region is determined according to the second total thermal region information based on the grid division method. Determine whether the average gray value of the first region is less than the average gray value of the second region, and whether the area of the first region is greater than the area of the second region. If the average gray value of the first region is less than the average gray value of the second region, and the area of the first region is greater than the area of the second region, then the severe abnormal state information is generated. If the average gray value of the first region is greater than the average gray value of the second region, and the area of the first region is less than the area of the second region, then the normal abnormal state information is generated; otherwise, normal state information is generated.
4. The method according to claim 1, characterized in that, After determining the state assessment information of the target transformer based on the first core region information, the first total thermal region information, the second core region information, and the second total thermal region information, the method further includes: Based on a preset camera, real-time captured image information of the target transformer is obtained, wherein the capture time of the real-time captured image information is the same as the capture time of the real-time heat map information; If the status assessment information is severe abnormal status information or ordinary abnormal status information, then the target associated region information is determined based on the first core region information and the real-time captured image information, wherein the target associated region information is used to describe the corresponding position of the first core region information in the real-time captured image information; Based on the real-time captured image information, the target associated region information is processed to generate cropped image block information; Based on the captured image block information and real-time heatmap information, core image data packet information is generated.
5. The method according to claim 3, characterized in that, If the status assessment information is ordinary abnormal status information or severe abnormal status information, then after determining the status assessment information of the target transformer based on the first core area information, the first total thermal area information, the second core area information, and the second total thermal area information, the method further includes: Obtain the average grayscale value and area information of the third region corresponding to multiple historical abnormal heatmaps; Based on the average gray value information of the first region and the average gray value information of the third region corresponding to multiple historical abnormal heat map information, the first similar heat map information is determined, wherein the first similar heat map information is used to describe the historical abnormal heat map information corresponding to the average gray value information of the third region that is closest to the average gray value information of the first region. Determine whether the number of the first similar heatmap information is multiple; If there are multiple similar heatmap information entries, then Based on the area information of the first region and the area information of the third region corresponding to multiple first similar heat map information, the second similar heat map information is determined, wherein the second similar heat map information is used to describe the first similar heat map information corresponding to the area information of the third region that is closest to the area information of the first region; Obtain historical fault cause information corresponding to the second similar heatmap information; Based on the historical fault cause information, maintenance reference information is generated.
6. A condition assessment system for hydraulic transformers based on big data analysis, characterized in that, The system includes: Real-time heat map information acquisition module: used to acquire real-time heat map information and historical normal heat map information of the target transformer; Core area information generation module: used to generate first core area information and first total heat area information based on the real-time heat map information and the preset edge detection algorithm, and to generate second core area information and second total heat area information based on the historical normal heat map information and the edge detection algorithm; Status assessment information determination module: used to determine the status assessment information of the target transformer based on the first core area information, the first total thermal area information, the second core area information, and the second total thermal area information.
7. The system according to claim 6, characterized in that, The system also includes: Real-time image acquisition module: used to acquire real-time image information of the target transformer based on a preset camera, wherein the shooting time of the real-time image information is the same as the shooting time of the real-time heat map information; Target-associated region information determination module: If the state assessment information is severe abnormal state information or ordinary abnormal state information, then based on the first core region information and the real-time captured image information, the target-associated region information is used to describe the corresponding position of the first core region information in the real-time captured image information; Image patch information generation module: used to perform cropping processing on the target associated region information based on the real-time captured image information to generate cropped image patch information; Core image data packet information generation module: used to generate core image data packet information based on the captured image block information and real-time heat map information.
8. A terminal 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 computer program, it implements the steps of the method as described in any one of claims 1 to 5.
9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.