Power transformation equipment thermal fault diagnosis method and system based on infrared image
By comparing infrared images with basic images and performing feature analysis, the preprocessing problem in infrared image processing of power equipment was solved, achieving efficient thermal fault diagnosis and improving identification accuracy and efficiency.
Patent Information
- Application Number
- CN202512006112.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-29
- Publication Date
- 2026-03-10
AI Technical Summary
Existing technologies for infrared image processing of power equipment suffer from problems such as the contradiction between preprocessing effect and efficiency (difficulty in balancing noise reduction and edge preservation), difficulty in ROI extraction, and poor model generalization ability. In particular, there is insufficient research on the heating mechanism of voltage-induced heating defects, resulting in low detection rate and complex heat conduction paths of internal faults. A quantitative correlation model between surface temperature distribution and the degree of internal faults is lacking.
By comparing the infrared image with a base image, the contour features are extracted and corrected, noise is separated, and edge operators and texture feature analysis are used to determine the center position and texture features of the analysis area. This classifies the thermal fault types of power equipment and avoids complex pre-processing.
It achieves accurate diagnosis of thermal faults in power equipment, improves the model's generalization ability and diagnostic efficiency, can identify point faults and area faults, and simplifies the processing flow.
Smart Images
Figure CN121640190A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of power grid safety management technology, and in particular to a method and system for diagnosing thermal faults in substation equipment based on infrared images. Background Technology
[0002] The core of the infrared image-based thermal fault diagnosis method for power equipment is to use infrared thermal imaging technology to capture the surface temperature distribution of the equipment, and combine image processing, feature extraction and fault identification algorithms to determine whether the equipment has thermal anomalies and the type of fault.
[0003] In practical applications, several key issues remain, including a trade-off between preprocessing effectiveness and efficiency (difficulty balancing noise reduction and edge preservation: Gaussian / median filtering easily blurs temperature abrupt changes, bilateral filtering has high computational costs and is unsuitable for online real-time processing; difficulty in ROI extraction: complex equipment structures and crisscrossing cables make traditional threshold / edge detection prone to missegmentation, and deep learning segmentation requires a large number of labeled samples) and poor model generalization ability (insufficient research on the heating mechanism of voltage-induced defects, low detection rate of infrared radiation; complex heat conduction paths for internal faults, and a lack of quantitative correlation models between surface temperature distribution and the degree of internal faults). Further research is needed to address these issues. Summary of the Invention
[0004] This application provides a method and system for diagnosing thermal faults in power equipment based on infrared images. By comparing the image with a base image and combining it with feature classification, thermal faults in power equipment can be diagnosed. This method can avoid complex preprocessing and obtain relatively accurate fault diagnosis results.
[0005] The above-mentioned objective of this application is achieved through the following technical solution: In a first aspect, this application provides a method for diagnosing thermal faults in power equipment based on infrared images, including: Acquire infrared images of the covered area and extract the contour features included in the infrared images; Obtain the base image corresponding to the covered area and extract the contour features included in the base image; The contour features included in the base image are used to correct the contour features included in the infrared image to obtain the infrared image corrected contour. Infrared images are separated by using infrared image contour correction to obtain infrared separated images; Basic processing is performed on the infrared separated images, including noise removal and image correction. Extracting temperature features from infrared separation images; The temperature characteristics of the infrared separation image are used to identify the type of thermal fault in the power equipment.
[0006] In one possible implementation of the first aspect, extracting the temperature features of the infrared separation image includes: Edge operators are used to process the infrared separation image to obtain edge contour features; Determine the number of center positions corresponding to the edge contour features; An analysis region is created based on each central location; Calculate and analyze the texture features of the region and use the texture features to classify the center location; The number of center locations, the texture features of the analyzed region, and the classification of center locations are used as temperature features of the infrared separation image.
[0007] In one possible implementation of the first aspect, when creating an analysis region based on each center position, an analysis region is created with the center position as the reference point, and the shape of the analysis region is the same as the smallest edge contour feature corresponding to the center position.
[0008] In one possible implementation of the first aspect, after creating the analysis region, the analysis region is further expanded.
[0009] In one possible implementation of the first aspect, expanding the analysis region includes: The region is expanded based on its edge, with each expansion being the same distance. Calculate the texture features of the analysis region after each expansion; Compare the texture features before and after expansion. Stop expansion when the texture features are different.
[0010] In one possible implementation of the first aspect, when using the temperature characteristics of the infrared separation image to indicate the type of thermal fault in the power equipment, the type of thermal fault in the power equipment includes point faults and area faults.
[0011] In one possible implementation of the first aspect, when there is only one center location in the center location classification, the thermal fault type of the substation is a point fault; when there are multiple center locations in the center location classification, the thermal fault type of the substation is a regional fault.
[0012] Secondly, this application provides a thermal fault diagnosis device for power equipment based on infrared images, comprising: The first acquisition unit is used to acquire an infrared image of the covered area and extract the contour features included in the infrared image; The second acquisition unit is used to acquire the base image corresponding to the coverage area and extract the contour features included in the base image; The contour correction unit is used to correct the contour features included in the infrared image using the contour features included in the base image, so as to obtain the infrared image corrected contour. The separation unit is used to separate the infrared image by correcting the contour of the infrared image to obtain the infrared separated image; The basic processing unit is used to perform basic processing on the infrared separation image, including noise removal and image correction. The feature extraction unit is used to extract temperature features from the infrared separation image; The result output unit is used to determine the type of thermal fault in the power equipment using the temperature characteristics of the infrared separation image.
[0013] Thirdly, this application provides a thermal fault diagnosis system for power equipment based on infrared images, the system comprising: One or more memories for storing instructions; and One or more processors are configured to retrieve and execute the instructions from the memory to perform the methods described in the first aspect and any possible implementation thereof.
[0014] Fourthly, this application provides a computer-readable storage medium, the computer-readable storage medium comprising: The program, when run by a processor, is executed as described in the first aspect and any possible implementation thereof.
[0015] Fifthly, this application provides a computer program product, including program instructions that, when run by a computing device, execute the method described in the first aspect and any possible implementation thereof.
[0016] Sixthly, this application provides a chip system including a processor for implementing the functions involved in the foregoing aspects, such as generating, receiving, transmitting, or processing the data and / or information involved in the foregoing methods.
[0017] This chip system can consist of chips or include chips and other discrete components.
[0018] In one possible design, the chip system also includes a memory for storing necessary program instructions and data. The processor and the memory can be decoupled and located on different devices, connected via wired or wireless means, or the processor and the memory can be coupled to the same device. Attached Figure Description
[0019] Figure 1 This is a flowchart illustrating the steps of a method for diagnosing thermal faults in power equipment based on infrared images, as provided in this application.
[0020] Figure 2This is a schematic diagram illustrating how to remove redundant parts through overlapping processing, as provided in this application.
[0021] Figure 3 This is a schematic diagram of an analysis region created based on each central location, as provided in this application.
[0022] Figure 4 This is a schematic diagram of an expansion of the analysis area provided in this application. Detailed Implementation
[0023] The technical solutions in this application will be further described in detail below with reference to the accompanying drawings.
[0024] This application discloses a method for diagnosing thermal faults in power equipment based on infrared images. Please refer to [link / reference]. Figure 1 In some examples, the infrared image-based method for diagnosing thermal faults in power equipment disclosed in this application includes the following steps: S101, acquire infrared images of the covered area and extract contour features included in the infrared images; S102, Obtain the base image corresponding to the covered area and extract the contour features included in the base image; S103, use the contour features included in the base image to correct the contour features included in the infrared image to obtain the corrected infrared image contour. S104, use infrared image correction contour to separate the infrared image to obtain the infrared separated image; S105 performs basic processing on the infrared separation image, including noise removal and image correction. S106, Extract temperature features from infrared separation image; S107 uses the temperature characteristics of the infrared separation image to indicate the type of thermal fault in the power equipment.
[0025] In steps S101 to S103, the contour features included in the base image are first used to correct the contour features included in the extracted infrared image. The correction process involves clarifying the contour features included in the infrared image through overlap processing and removing redundant parts, such as... Figure 2 As shown.
[0026] Next, in S104, infrared image correction contours are used to separate the infrared image, resulting in a separated infrared image.
[0027] Then, after basic processing of the infrared separation image, the temperature features of the infrared separation image are extracted, and finally the temperature features of the infrared separation image are used to determine the thermal fault type of the power equipment.
[0028] Basic processing includes two parts: noise removal and image correction. Specifically, the methods for noise removal are as follows: Gaussian filtering: suitable for smoothing Gaussian noise while preserving image edges; Median filtering: It is effective in removing salt-and-pepper noise and avoids blurring of temperature change points; Bilateral filtering: It balances noise reduction and edge preservation, and is suitable for processing areas with obvious temperature gradients on the surface of equipment.
[0029] The relevant methods for image correction are as follows: Radiation correction: Eliminates the influence of environmental radiation and atmospheric attenuation on temperature measurement, converting image grayscale values into true temperature values. The formula is: Geometric correction: Corrects image distortion caused by shooting angle and distance, ensuring that the device outline is consistent with the actual shape, which facilitates subsequent feature matching.
[0030] In some examples, the specific methods for extracting temperature features from infrared separation images are as follows: Edge operators are used to process the infrared separation image to obtain edge contour features; Determine the number of center positions corresponding to the edge contour features; An analysis region is created based on each central location, such as Figure 3 As shown; Calculate and analyze the texture features of the region and use the texture features to classify the center location; The number of center locations, the texture features of the analyzed region, and the classification of center locations are used as temperature features of the infrared separation image.
[0031] This will yield three results: the number of center locations, the texture features of the analyzed region, and the center location classification. These three results will be used as temperature features of the infrared separation image.
[0032] In some examples, when creating an analysis region based on each center location, an analysis region is created with the center location as the reference point, and the shape of the analysis region is the same as the smallest edge contour feature corresponding to the center location.
[0033] In addition to creating the analysis region, the process also includes expanding the analysis region, as follows: The region is expanded based on its edge, with each expansion being the same distance. Figure 4 As shown; Calculate the texture features of the analysis region after each expansion; Compare the texture features before and after expansion. Stop expansion when the texture features are different.
[0034] The purpose of expanding the analysis area is to determine the specific area of this temperature anomaly region.
[0035] In some cases, when using the temperature features of infrared separation images to determine the thermal fault type of power equipment, the thermal fault type of power equipment includes point faults and area faults. Specifically, when there is only one center location in the center location classification, the thermal fault type of power equipment is a point fault; when there are multiple center locations in the center location classification, the thermal fault type of power equipment is an area fault.
[0036] This application also provides a thermal fault diagnosis device for power equipment based on infrared images, comprising: The first acquisition unit is used to acquire an infrared image of the covered area and extract the contour features included in the infrared image; The second acquisition unit is used to acquire the base image corresponding to the coverage area and extract the contour features included in the base image; The contour correction unit is used to correct the contour features included in the infrared image using the contour features included in the base image, so as to obtain the infrared image corrected contour. The separation unit is used to separate the infrared image by correcting the contour of the infrared image to obtain the infrared separated image; The basic processing unit is used to perform basic processing on the infrared separation image, including noise removal and image correction. The feature extraction unit is used to extract temperature features from the infrared separation image; The result output unit is used to determine the type of thermal fault in the power equipment using the temperature characteristics of the infrared separation image.
[0037] In one example, the unit in any of the above devices may be one or more integrated circuits configured to implement the above methods, such as one or more application-specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.
[0038] For example, when the units in the device can be implemented through a processing element scheduler, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor capable of calling programs. Alternatively, these units can be integrated together to form a system-on-a-chip (SOC).
[0039] In this application, various objects such as messages / information / devices / network elements / systems / apparatus / actions / operations / processes / concepts may be named. It is understood that these specific names do not constitute a limitation on the relevant objects. The names may be changed depending on the scenario, context, or usage habits. The understanding of the technical meaning of the technical terms in this application should be mainly determined from their functions and technical effects embodied / performed in the technical solution.
[0040] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0041] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.
[0042] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0043] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0044] It should also be understood that in the various embodiments of this application, the terms "first," "second," etc., are merely to indicate that multiple objects are different. For example, a first time window and a second time window are only to indicate different time windows. They should not have any effect on the time windows themselves, and the aforementioned terms "first," "second," etc., should not impose any limitations on the embodiments of this application.
[0045] It should also be understood that, in the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced by each other, and the technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.
[0046] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned computer-readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0047] This application also provides a thermal fault diagnosis system for power equipment based on infrared images, the system comprising: One or more memories for storing instructions; and One or more processors are configured to retrieve and execute the instructions from the memory, performing the methods described above.
[0048] This application also provides a computer program product including instructions that, when executed, cause the terminal device and the network device to perform operations corresponding to the methods described above.
[0049] This application also provides a chip system including a processor for implementing the functions involved in the above description, such as generating, receiving, transmitting, or processing the data and / or information involved in the above methods.
[0050] This chip system can consist of chips or include chips and other discrete components.
[0051] The processor mentioned above can be a CPU, a microprocessor, an ASIC, or one or more integrated circuits that execute a program to control the method of transmitting the feedback information described above.
[0052] In one possible design, the chip system also includes a memory for storing necessary program instructions and data. The processor and the memory can be decoupled and located on different devices, connected via wired or wireless means to support the chip system in implementing the various functions described in the above embodiments. Alternatively, the processor and the memory can also be coupled to the same device.
[0053] Optionally, the computer instructions are stored in memory.
[0054] Optionally, the memory can be a storage unit within the chip, such as a register or cache. Alternatively, the memory can be a storage unit located outside the chip within the terminal, such as a ROM or other types of static storage devices that can store static information and instructions, such as RAM.
[0055] It is understood that the memory in this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.
[0056] Non-volatile memory can be ROM, programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.
[0057] Volatile memory can be RAM, which is used as an external cache. There are many different types of RAM, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus random access memory.
[0058] The embodiments described in this specific implementation are 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 structure, shape and principle of this application should be covered within the scope of protection of this application.
Claims
1. A power transformation equipment thermal fault diagnosis method based on infrared images, characterized in that, The method comprises: acquiring an infrared image of a coverage area and extracting contour features included in the infrared image; acquiring a base image corresponding to the coverage area and extracting contour features included in the base image; correcting the contour features included in the infrared image using the contour features included in the base image to obtain infrared image corrected contours; separating the infrared image using the infrared image corrected contours to obtain an infrared separated image; performing basic processing on the infrared separated image, the basic processing including noise removal and image correction; extracting temperature features of the infrared separated image; giving a thermal fault type of a power transformation device using the temperature features of the infrared separated image.
2. The infrared image-based thermal fault diagnosis method for power transformation equipment according to claim 1, characterized in that, The extracting of the temperature features of the infrared separated image comprises: processing the infrared separated image using an edge operator to obtain edge contour features; determining a number of center positions corresponding to the edge contour features; creating an analysis area based on each center position; calculating texture features of the analysis area and classifying the center positions using the texture features; taking the number of center positions, the texture features of the analysis area, and the classification of the center positions as the temperature features of the infrared separated image.
3. The infrared image-based thermal fault diagnosis method for power transformation equipment according to claim 2, characterized in that, When creating the analysis area based on each center position, a center position is taken as a reference point to create an analysis area, and the shape of the analysis area is the same as the smallest edge contour feature corresponding to the center position.
4. The infrared image-based thermal fault diagnosis method for power transformation equipment according to claim 3, characterized in that, After creating the analysis area, the analysis area is also expanded.
5. The infrared image-based thermal fault diagnosis method for power transformation equipment according to claim 4, characterized in that, The expanding of the analysis area comprises: expanding based on the edge of the analysis area, and the distance of each expansion is equal; calculating the texture features of the analysis area after each expansion; comparing the texture features before and after the expansion, and stopping the expansion when the texture features are different.
6. The infrared image-based substation thermal fault diagnostic method of claim 2, wherein, When giving the thermal fault type of the power transformation device using the temperature features of the infrared separated image, the thermal fault type of the power transformation device includes a point fault and an area fault.
7. The infrared image-based thermal fault diagnosis method of power equipment according to claim 6, characterized in that, When the number of center positions in the classification of the center positions is one, the thermal fault type of the power transformation device is the point fault; and when the number of center positions in the classification of the center positions is multiple, the thermal fault type of the power transformation device is the area fault.
8. A power transformation equipment thermal fault diagnosis device based on infrared images, characterized in that, The method comprises: a first acquisition unit configured to acquire an infrared image of a coverage area and extract contour features included in the infrared image; a second acquisition unit configured to acquire a base image corresponding to the coverage area and extract contour features included in the base image; a contour correction unit configured to correct the contour features included in the infrared image using the contour features included in the base image to obtain infrared image corrected contours; a separation unit configured to separate the infrared image using the infrared image corrected contours to obtain an infrared separated image; a basic processing unit configured to perform basic processing on the infrared separated image, the basic processing including noise removal and image correction; a feature extraction unit configured to extract temperature features of the infrared separated image; a result output unit configured to give a thermal fault type of a power transformation device using the temperature features of the infrared separated image.
9. A power transformation equipment thermal fault diagnosis system based on infrared images, characterized in that, The system comprises: one or more memories configured to store instructions; and one or more processors configured to call and run the instructions from the memories to perform the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises: a program which, when executed by a processor, causes the method of any of claims 1 to 7 to be performed.