Method and device for predicting residual life of composite insulator and storage medium

Abstract

The embodiment of the invention provides a method and device for predicting the residual life of a composite insulator, a storage medium and a computer program product. The method comprises the following steps: inspecting a running composite insulator based on a multi-sensor system, wherein the multi-sensor system at least comprises an image acquisition module, a temperature distribution acquisition module and an electroluminescent detection module; extracting target appearance characteristics of the composite insulator through the data acquired by the image acquisition module; the temperature characteristic of the composite insulator is calculated through the data acquired by the temperature distribution acquisition module; electric field distribution characteristics reflecting the electric field intensity are obtained through data collected by the electroluminescent detection module; and inputting the target appearance characteristics, the temperature characteristics and the electric field distribution characteristics into a trained life evaluation model to determine the residual life of the composite insulator.

Description

Technical Field

[0001] This application relates to the field of operation and maintenance of composite insulators in the main grid, and specifically to a method, apparatus, storage medium, and computer program product for predicting the remaining life of composite insulators. Background Technology

[0002] During the operation of composite insulators, the long-term effects of external environmental factors (such as electricity, light, and heat) can cause the molecular chains in silicone rubber to break, leading to polymer degradation. Under the influence of external aging factors, a large number of active chemical groups will produce a series of chemical reactions such as hydrolysis and oxidation. These reactions damage the structure and hydrophobicity of the silicone rubber surface, resulting in reduced flexibility of the molecular chains, material hardening, and gradual aging or even failure of the insulator's performance.

[0003] Scholars from various countries have conducted multi-faceted physicochemical analysis of composite insulators, including their appearance, physical properties, and electrical properties. They have also carried out accelerated aging tests on composite insulators in conjunction with the field operating environment, summarized many operational change patterns of composite insulators, and proposed many condition assessment models for composite insulators. These methods can provide some assistance for the field operation of composite insulators, but the accuracy and versatility of the models can be further improved.

[0004] Current composite insulator condition assessment models are typically derived from pre-installation physical and chemical property analyses, without incorporating long-term analysis during operation and often failing to consider geographical variations. This application utilizes technologies such as drone inspections to periodically measure and assess the operational status of composite insulators. Based on parameters such as the insulator's appearance, the temperature difference between the highest heating point and the ambient temperature, and the average photon count at the highest heating point, the remaining service life of the composite insulator is dynamically assessed. This provides significant guidance for the maintenance, repair, and replacement of composite insulators. Summary of the Invention

[0005] The purpose of this application is to provide a method, apparatus, storage medium, and computer program product for predicting the remaining life of composite insulators, in order to solve the problems of low accuracy and weak versatility of the composite insulator life prediction models used in the prior art.

[0006] To achieve the above objectives, a first aspect of this application provides a method for predicting the remaining life of a composite insulator, comprising: The multi-sensor system is used to inspect composite insulators in operation. The multi-sensor system includes at least an image acquisition module, a temperature distribution acquisition module, and an electroluminescence detection module. The target appearance features of the composite insulator are extracted from the data collected by the image acquisition module. The temperature characteristics of the composite insulator are calculated based on the data collected by the temperature distribution acquisition module. The data collected by the electroluminescence detection module is used to obtain the electric field distribution characteristics that reflect the electric field intensity. The target appearance characteristics, temperature characteristics, and electric field distribution characteristics are input into the trained lifetime assessment model to determine the remaining lifetime of the composite insulator.

[0007] In this embodiment of the application, the target appearance features include characterizing the umbrella skirt damage and surface contamination; wherein, the umbrella skirt damage is classified into at least minor damage, severe damage and critical damage according to the severity of the damage; and the surface contamination is classified into at least three stages according to the dynamic process of contamination accumulation: initial contamination, dynamic equilibrium period and aging impact period.

[0008] In this embodiment, the temperature characteristic is the standardized temperature difference ΔT, which is calculated using the following formula: T =

[0009] in, This represents the highest surface temperature of the composite insulator. The ambient background temperature, The surface heat transfer coefficient of the composite insulator after wind speed compensation is given.

[0010] In this embodiment of the application, the electric field distribution characteristic is a physical quantity that is proportional to the square of the electric field intensity amplitude, used to characterize the electric field distribution at the high-voltage end of the composite insulator; when the value of this physical quantity exceeds a preset threshold, it is determined that the electric field distribution is abnormal.

[0011] In this embodiment of the application, the method further includes a life assessment model construction step, which includes: obtaining multiple sets of sample data through laboratory testing and grid-connected operation testing, each set of sample data including at least the appearance characteristics, temperature characteristics, electric field distribution characteristics of the composite insulator and its corresponding actual remaining life; based on the multiple sets of sample data, establishing a comprehensive relationship between appearance characteristics, temperature characteristics, electric field distribution characteristics and remaining life through regression analysis or machine learning algorithms; and constructing a life assessment model based on the comprehensive relationship.

[0012] In this embodiment of the application, the method further includes: establishing and maintaining a composite insulator operation ledger based on a cloud server, the ledger being used to store the target appearance characteristics, temperature characteristics and electric field distribution characteristics obtained from each inspection; and periodically transmitting the data in the ledger to a life assessment model to determine the remaining life of the composite insulator in real time.

[0013] In this embodiment of the application, the method further includes a correction step for the life assessment model, which includes: dynamically correcting the parameters of the life assessment model based on the actual operating life data of the composite insulator and the operating data accumulated in the ledger; and assessing the impact of geographical environment parameters on the life of the composite insulator based on the geographical environment information in the ledger.

[0014] A second aspect of this application provides an apparatus for predicting the remaining life of a composite insulator, comprising: a memory configured to store instructions; The processor is configured to retrieve instructions from memory and, when executing the instructions, to implement a method for predicting the remaining lifetime of a composite insulator according to any of the foregoing.

[0015] A third aspect of this application provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the aforementioned method for predicting the remaining lifetime of a composite insulator.

[0016] A fourth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements a method for predicting the remaining life of a composite insulator according to any one of the preceding claims.

[0017] This solution establishes a quantitative relationship between current multidimensional characteristics and remaining service life through a life assessment model. This allows maintenance units to shift from "reactive maintenance" to "predictive maintenance," enabling them to scientifically formulate replacement plans and allocate resources, avoiding blind replacements or power outages. Furthermore, this solution integrates sensors into drones and uses the model to automatically analyze data, achieving automation, standardization, and precision in inspection work. Therefore, this method can solve the problems of low accuracy and limited versatility in existing composite insulator life prediction models.

[0018] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0019] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings: Figure 1 The schematic diagram illustrates a process flow diagram of a method for predicting the remaining lifetime of a composite insulator according to an embodiment of this application; Figure 2 The schematic diagram illustrates a process flow diagram of a method for predicting the remaining lifetime of a composite insulator according to another embodiment of this application; Figure 3The diagram illustrates the internal structure of a computer device according to an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0021] Figure 1 A schematic flowchart illustrating a method for predicting the remaining life of a composite insulator according to an embodiment of this application is shown. Figure 1 As shown in one embodiment of this application, a method for predicting the remaining lifetime of a composite insulator is provided, the method comprising the following steps: Step 102: Conduct inspections on composite insulators in operation based on a multi-sensor system. The multi-sensor system includes at least an image acquisition module, a temperature distribution acquisition module, and an electroluminescence detection module. Step 104: Extract the target appearance features of the composite insulator from the data acquired by the image acquisition module; Step 106: Calculate the temperature characteristics of the composite insulator using the data collected by the temperature distribution acquisition module; Step 108: Obtain the electric field distribution characteristics reflecting the electric field intensity by collecting data through the electroluminescence detection module; Step 110: Input the target appearance features, temperature features, and electric field distribution characteristics into the trained lifetime assessment model to determine the remaining lifetime of the composite insulator.

[0022] Composite insulators are insulating components used in high-voltage transmission lines, consisting of a glass fiber epoxy resin core rod, silicone rubber skirts, and hardware end fittings. A multi-sensor system is a comprehensive data acquisition platform integrating multiple detection devices. In this solution, it specifically refers to a system integrating an image acquisition module, a temperature distribution acquisition module, and an electroluminescence detection module, typically mounted on a drone, for synchronous, multi-angle data acquisition of the same insulator. The image acquisition module includes equipment for acquiring visible light images of the composite insulator. Specifically, this could be a high-definition visible light camera, a zoom camera, etc. The temperature distribution acquisition module includes equipment for non-contact measurement and acquisition of the surface temperature field information of the composite insulator. Specifically, this could be an infrared thermal imager. The electroluminescence detection module includes equipment for detecting specific wavelength light signals generated by localized electric field concentration or discharge phenomena. Specifically, this could be an ultraviolet imager for detecting ultraviolet photons generated by corona discharge. Therefore, in this solution, the processor can control the multi-sensor system to inspect the composite insulator in operation, acquire the data collected by the image acquisition module, and extract the target appearance features of the composite insulator based on this data. Among them, the target appearance features of composite insulators refer to the key indicators extracted from visible light images that can characterize the external physical state of composite insulators.

[0023] In one embodiment, the processor can also calculate the temperature characteristics of the composite insulator using data collected by the temperature distribution acquisition module. Temperature characteristics refer to quantitative indicators calculated from temperature distribution data that characterize the heating state of the composite insulator. Specifically, temperature characteristics can refer to the standardized temperature difference ΔT, which is the difference between the temperature of the hottest point on the insulator surface and the ambient temperature, after wind speed compensation. In this embodiment, the temperature difference between the highest heating point of the composite insulator and the ambient temperature is used as the primary criterion for the operating status of the composite insulator. If abnormal heating occurs, it needs to be closely monitored and repaired promptly. In other words, temperature characteristics are the core criterion for assessing the insulation state (such as defects at the core rod-sheath interface) and electrical connection state within the insulator. Abnormal heating is usually a precursor to a fault.

[0024] Furthermore, the processor can also acquire the electric field distribution characteristics reflecting the electric field strength through data collected by the electroluminescence detection module. These electric field distribution characteristics are physical quantities derived from the electroluminescence signal that reflect the distribution of the electric field strength around the composite insulator. Specifically, they can refer to indicators such as the average photon count N. Since the photon count is proportional to the square of the electric field strength, an anomaly in the average photon count N directly indicates the activity of electric field concentration or localized discharge. In this embodiment, the average photon count at the highest heating point of the composite insulator is used as the third criterion for the composite insulator's operating status. For composite insulators with abnormal heating, if the average photon count is also abnormal, it indicates an abnormal electric field strength at the high-voltage end, requiring urgent troubleshooting. Electric field distribution characteristics are a core criterion for evaluating the electrical insulation status of insulators and early latent faults, especially sensitive to corona discharge that is undetectable by the naked eye and infrared radiation. Specifically, the composite insulator photon count is the photon count at the highest temperature point (the temperature of the strongest heating point) of the composite insulator. Assuming a space with volume V has a total energy of U = uV, where u is the energy per unit volume, then the average number of photons N in this space can be defined as:

[0025] in, h To reduce Planck's constant, ω is the angular frequency. The vacuum permittivity, Let be the amplitude of the electric field. It can be seen that the average number of photons is related to the amplitude of the electric field strength. The number of photons is proportional to the square of the electric field strength, meaning the photon count reflects the magnitude of the electric field. Since electric field strength is a crucial criterion for identifying anomalies in composite insulators, an abnormality in the average number of photons indicates an abnormal electric field distribution at the high-voltage end of the composite insulator, suggesting an abnormal operating state.

[0026] In one specific embodiment, the electric field distribution characteristic is a physical quantity that is proportional to the square of the electric field intensity amplitude, used to characterize the electric field distribution at the high-voltage end of the composite insulator; when the value of this physical quantity exceeds a preset threshold, it is determined that the electric field distribution is abnormal.

[0027] Next, the processor can input the target appearance features, temperature features, and electric field distribution characteristics into the trained lifetime assessment model to determine the remaining lifetime of the composite insulator. It can be seen that the lifetime assessment model is a mathematical model established through machine learning algorithms or regression analysis. This model takes multi-dimensional data such as "appearance features, temperature features, and electric field distribution characteristics" as input and outputs a predicted value for the remaining lifetime of the composite insulator.

[0028] Traditional methods may rely solely on visual inspection or single electrical testing. This method, however, combines three crucial and complementary assessment dimensions: mechanical appearance (images), thermal condition (temperature), and electrical condition (electric field). For example, a tiny crack (appearance) may be harmless when dry, but if it simultaneously generates heat (temperature) and corona discharge (electric field), it indicates a developing defect and a significantly increased risk level. This multi-dimensional cross-validation greatly improves the accuracy of condition assessment. Secondly, this solution establishes a quantitative relationship between current multi-dimensional characteristics and remaining service life through a lifespan assessment model. This allows maintenance units to shift from "reactive maintenance" to "predictive maintenance," enabling them to scientifically formulate replacement plans and resource allocation, avoiding blind replacements or power outages. Furthermore, this solution integrates sensors into drones, using models to automatically analyze data, achieving automation, standardization, and precision in inspection work. Therefore, this method addresses the problems of low accuracy and limited versatility in existing composite insulator lifespan prediction models.

[0029] In one specific embodiment, the target appearance features include characterizing the condition of the sheds and the surface contamination. The shed damage is categorized into at least three levels based on severity: minor damage, severe damage, and critical damage. The surface contamination is categorized into at least three stages based on the dynamic process of contamination accumulation: initial contamination, dynamic equilibrium period, and aging impact period. In other words, in this embodiment, the surface contamination and shed condition of the composite insulator are used as the second criterion for determining the operating status of the composite insulator; abnormal contamination or severe shed damage requires timely repair. More specifically, the characteristics of minor shed damage include the following three: 1. Only a single umbrella skirt edge has a small notch (<10mm); 2. The surface of the umbrella skirt has shallow scratches and cracks, but the core rod is not damaged; 3. There are no obvious signs of electrical discharge or burning at the damaged area of ​​the umbrella skirt.

[0030] Specifically, severely damaged umbrella skirts exhibit the following three characteristics: 1. Multiple umbrella skirts are damaged, or a single umbrella skirt has a large area missing; 2. The umbrella skirt is damaged to a considerable depth, and the internal fiberglass core rod is visible, but the core rod is not yet exposed or only has slight surface damage. 3. The damaged area of ​​the umbrella skirt shows signs of burning, whitening, and carbonization caused by partial discharge.

[0031] Specifically, the characteristics of a critically damaged umbrella skirt include the following three: 1. The umbrella skirt is torn and peeled off in large areas; 2. The core rod is directly exposed to the air, or has obvious penetrating holes; 3. Arc burns and carbonization channels appear on the core rod; the insulator shows obvious flashover and leakage, or there are signs of loosening at the connection with the hardware.

[0032] Furthermore, the accumulation of contaminants on the surface of composite insulators is a dynamic, complex, and multi-factor-affected evolutionary process, typically divided into three stages: initial contamination, dynamic equilibrium, and aging. The initial contamination stage is characterized by a rapid increase in contamination levels; the dynamic equilibrium stage is characterized by a stabilization of contamination levels, fluctuating around an average value; and the aging stage is characterized by a potential resurgence in contamination levels, or even the appearance of localized contamination anomalies.

[0033] In one embodiment, the temperature characteristic is a standardized temperature difference ΔT, which is calculated using the following formula: T =

[0034] in, This is the highest surface temperature of the composite insulator, i.e., the temperature of the strongest heat-generating point. The ambient background temperature, The surface heat transfer coefficient of the composite insulator after wind speed compensation is given.

[0035] In one embodiment, the method further includes a step of constructing a lifetime assessment model. The construction step includes: acquiring multiple sets of sample data through laboratory testing and grid-connected operation testing, each set of sample data including at least the appearance characteristics, temperature characteristics, electric field distribution characteristics of the composite insulator, and their corresponding actual remaining lifetime; based on the multiple sets of sample data, establishing a comprehensive relationship between appearance characteristics, temperature characteristics, electric field distribution characteristics, and remaining lifetime through regression analysis or machine learning algorithms; and constructing a lifetime assessment model based on the comprehensive relationship.

[0036] Laboratory testing refers to accelerated aging tests conducted on composite insulator samples in a controlled laboratory environment. By applying electrical, thermal, mechanical, and environmental stresses (such as high voltage, high temperature and humidity, ultraviolet radiation, and mechanical cyclic loads) far exceeding normal operating conditions, the aging process of insulators over several years is simulated in a relatively short time. Grid-connected operation testing refers to long-term monitoring of composite insulators that have been in operation for different years on actual transmission lines. This involves periodically collecting data on their appearance, temperature, and electric field under real, complex operating conditions (e.g., using drones), and correlating this data with the insulator's actual operating time. After laboratory and grid-connected operation testing, multiple sets of sample data can be obtained. Each set of sample data includes at least the composite insulator's appearance characteristics, temperature characteristics, electric field distribution characteristics, and their corresponding actual remaining lifespan. Based on multiple sets of sample data, a comprehensive relationship between appearance characteristics, temperature characteristics, electric field distribution characteristics, and remaining lifespan can be established through regression analysis or machine learning algorithms. A lifespan assessment model can then be constructed based on this comprehensive relationship.

[0037] This method, through rigorous, multi-level data preparation and advanced modeling techniques, successfully maps the aging phenomenon of insulators in the physical world into a calculable and optimizable digital model, ultimately achieving a fundamental shift in the remaining life of composite insulators from "empirical guessing" to "scientific prediction". In one embodiment, the method further includes: establishing and maintaining an operational ledger for composite insulators based on a cloud server. The ledger stores target appearance characteristics, temperature characteristics, and electric field distribution characteristics obtained from each inspection. The data in the ledger is periodically transmitted to a life assessment model to determine the remaining lifespan of the composite insulators in real time. The ledger data includes characteristic parameters such as composite insulator model, tower location, installation time, manufacturing time, appearance characteristics, temperature characteristics, electric field distribution characteristics, ambient temperature, ambient wind speed, and geographical location.

[0038] In one embodiment, the method further includes a correction step for the life assessment model, which includes: dynamically correcting the parameters of the life assessment model based on the actual operating life data of the composite insulator and the operating data accumulated in the ledger; and assessing the impact of geographical environmental parameters on the life of the composite insulator based on the geographical environmental information in the ledger.

[0039] Furthermore, for composite insulators with abnormal operating conditions, maintenance measures can be formulated according to the severity of the defect. For minor defects, the inspection cycle can be shortened. Then, the recent weather conditions (such as no rain, fog, drizzle, or other humid weather) should be assessed. If short-term operation is possible under dry conditions, the insulator should be included in the latest power outage maintenance plan for replacement.

[0040] For severe defects, if grid conditions permit, an application can be made to the dispatch center to reduce the operating voltage to decrease the electric field strength and suppress the development of partial discharge. An emergency power outage window can also be requested immediately for prompt replacement. If located in an area with high population density, warning signs can be installed to prevent the risk of falling objects.

[0041] In response to the critical defect, the dispatch center was immediately notified and requested that the line be shut down immediately. The dispatch center isolated the faulty line and immediately activated the emergency plan, organizing a repair team and materials to go to the site for replacement.

[0042] Furthermore, for composite insulators exhibiting abnormal operating conditions, the processor can analyze the causes of the abnormalities, record the data in the cloud server ledger, and compare it with historical data to analyze whether there are product quality issues or family-related defects. For composite insulators operating normally, the processor can call the application life assessment model to evaluate the remaining lifespan of the composite insulator.

[0043] In one embodiment, such as Figure 2As shown, data archives can be collected and stored on a cloud server, including parameters such as the composite insulator's appearance characteristics, the temperature difference between the highest heat point and the ambient temperature, and the average photon count at the highest heat point, based on each autonomous inspection by the drone. The composite insulator life assessment model can then access these data archives in real time to predict the remaining lifespan of the composite insulators. Furthermore, the composite insulator life assessment model can be dynamically revised based on the actual operating lifespan of the composite insulators, and the impact of parameters such as the geographical environment on the lifespan of the composite insulators can be assessed based on operational data.

[0044] Figure 1 This is a flowchart illustrating a method for predicting the remaining lifetime of a composite insulator in one embodiment. It should be understood that, although... Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise explicitly stated herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0045] In one embodiment, an apparatus for predicting the remaining life of a composite insulator is provided, comprising: The memory is configured to store instructions; The processor is configured to retrieve instructions from memory and, when executing the instructions, to implement a method for predicting the remaining lifetime of a composite insulator according to any of the foregoing.

[0046] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured, and methods for predicting the remaining lifetime of composite insulators can be implemented by adjusting kernel parameters.

[0047] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0048] This application provides a storage medium storing a program that, when executed by a processor, implements the method described above for predicting the remaining life of a composite insulator.

[0049] This application provides a processor for running a program, wherein the program executes the above-described method for predicting the remaining life of a composite insulator.

[0050] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor A01, a network interface A02, memory (not shown), and a database (not shown) connected via a system bus. The processor A01 provides computational and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02, and a database (not shown). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A04. The database stores data for predicting the remaining life of composite insulators. The network interface A02 communicates with external terminals via a network connection. When executed by the processor A01, the computer program B02 implements a method for predicting the remaining life of composite insulators.

[0051] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0052] This application provides a computer (electronic) device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of any of the above methods for predicting the remaining life of composite insulators.

[0053] This application also provides a computer program product that, when executed on a data processing device, is adapted to perform a program having method steps for predicting the remaining life of a composite insulator.

[0054] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0055] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0056] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0057] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0058] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0059] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0060] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0061] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0062] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for predicting the remaining life of a composite insulator, characterized in that, The method includes: Inspection of composite insulators in operation is carried out based on a multi-sensor system, wherein the multi-sensor system includes at least an image acquisition module, a temperature distribution acquisition module, and an electroluminescence detection module; The target appearance features of the composite insulator are extracted from the data acquired by the image acquisition module. The temperature characteristics of the composite insulator are calculated based on the data collected by the temperature distribution acquisition module. The data collected by the electroluminescence detection module is used to obtain the electric field distribution characteristics that reflect the electric field strength. The target appearance features, temperature features, and electric field distribution characteristics are input into a trained lifetime assessment model to determine the remaining lifetime of the composite insulator.

2. The method according to claim 1, characterized in that, The target appearance features include characteristics of umbrella skirt damage and surface dirt; The damage to the umbrella skirt is classified into at least three categories based on the severity of the damage: minor damage, severe damage, and critical damage. The surface contamination situation is divided into at least three stages based on the dynamic process of contamination accumulation: initial contamination, dynamic equilibrium period, and aging impact period.

3. The method according to claim 1, characterized in that, The temperature characteristic is the standardized temperature difference ΔT, which is calculated using the following formula: T = in, This is the highest surface temperature of the composite insulator. The ambient background temperature, The surface heat transfer coefficient of the composite insulator after wind speed compensation is given.

4. The method according to claim 1, characterized in that, The electric field distribution characteristic is a physical quantity that is proportional to the square of the electric field intensity amplitude, used to characterize the electric field distribution at the high-voltage end of the composite insulator; when the value of this physical quantity exceeds a preset threshold, it is determined to be an abnormal electric field distribution.

5. The method according to claim 1, characterized in that, The method further includes a life assessment model construction step, which includes: Through laboratory testing and grid-connected operation testing, multiple sets of sample data were obtained. Each set of sample data includes at least the appearance characteristics, temperature characteristics, electric field distribution characteristics and corresponding actual remaining life of the composite insulator. Based on the multiple sets of sample data, a comprehensive relationship between the appearance features, temperature features, electric field distribution characteristics and remaining lifetime is established through regression analysis or machine learning algorithms. The life assessment model is constructed based on the comprehensive relationship.

6. The method according to claim 1, characterized in that, The method further includes: A cloud server is used to establish and maintain an operation ledger for composite insulators. The ledger is used to store the target appearance characteristics, temperature characteristics and electric field distribution characteristics obtained from each inspection. The data in the ledger is periodically transmitted to the life assessment model to determine the remaining life of the composite insulator in real time.

7. The method according to claim 6, characterized in that, The method further includes a correction step for the life assessment model, the correction step including: The parameters of the life assessment model are dynamically adjusted based on the actual service life data of the composite insulator and the service data accumulated in the ledger. Based on the geographical environment information in the ledger, the impact of geographical environment parameters on the lifespan of composite insulators is assessed.

8. A device for predicting the remaining life of a composite insulator, characterized in that, include: The memory is configured to store instructions; The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the method for predicting the remaining lifetime of a composite insulator according to any one of claims 1 to 7.

9. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by a processor, this instruction causes the processor to be configured to perform a method for predicting the remaining life of a composite insulator according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the method for predicting the remaining life of a composite insulator according to any one of claims 1 to 7.

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