Electric power equipment remote diagnosis and field maintenance system based on remote cooperation

Abstract

The invention discloses an electrical equipment remote diagnosis and field maintenance system based on remote cooperation, and relates to the technical field of electrical equipment intelligent operation and maintaining.The electrical equipment remote diagnosis and field maintenance system comprises a data acquisition module, a remote diagnosis module, a remote maintenance module and a local database; the method provides multi-dimensional data support for diagnosis, quantifies an electrothermal parameter relationship by means of a thermoelectric coupling model, accurately identifies an overheating fault, evaluates an insulation aging degree, determines a discharge hazard level, realizes accurate discrimination of multiple types of core faults, outputs a fault risk comprehensive distribution diagram and a maintenance priority, provides clear guidance for operation and maintenance personnel, and improves the reliability of the operation and maintenance personnel. According to the method, the processing pertinence and efficiency are improved, a three-dimensional visualization scheme is generated, fault data are mapped to a digital twinborn body through AR equipment and overlaid on real equipment, remote guidance of experts is supported, data are recorded, compliance is evaluated, and digital management and control of maintenance are achieved.

Description

Technical Field

[0001] This invention relates to the field of intelligent operation and maintenance technology for power equipment, specifically to a remote diagnostic and on-site repair system for power equipment based on remote collaboration. Background Technology

[0002] Power equipment is the core support of the energy supply system. Traditional maintenance methods rely on manual on-site inspections and fault diagnosis, which suffer from problems such as delayed response and high labor costs. In addition, the ability to predict faults is weak, which can easily lead to downtime risks. With the development of the Internet of Things, big data and communication technologies, a technical foundation has been provided for remote sensing of equipment status, accurate fault diagnosis and on-site maintenance collaboration. Power equipment operation and maintenance systems based on remote collaboration have become an important direction for solving traditional pain points and improving operation and maintenance efficiency.

[0003] Existing technologies, such as the invention patent application CN114204680B which discloses a multi-type automated testing equipment fusion remote diagnostic system and method, include a testing data acquisition terminal, a cloud server, and a remote diagnostic terminal. It also provides a method for fusion remote diagnostics of multiple types of automated testing equipment. The system remotely collects power equipment testing data through the data acquisition terminal, supporting technicians to remotely inspect equipment at different locations, shortening the testing cycle. In the authorization verification process, it reduces noise in facial images, improving the accuracy of feature data and verification. Another existing technology, such as the invention patent application CN114362367B which discloses a cloud-edge collaborative transmission line monitoring system and method, and an identification system and method, includes a monitoring system comprising four layers: perception, edge, network, and cloud. The perception layer collects power equipment data; the edge layer preprocesses data; the network layer transmits data; and the cloud layer stores, classifies, and issues instructions. This system solves the problems of low data processing efficiency, difficult transmission, and difficult on-site fault diagnosis under a cloud architecture.

[0004] As can be seen from the above solutions, the current system has obvious shortcomings: existing technologies do not focus on key equipment such as dry-type transformers, fail to integrate their multi-physics field coupling failure mechanisms, have limited diagnostic model functions, and cannot accurately distinguish the interactive effects and independent characteristics of core faults such as overheating, insulation aging, and discharge. At the data processing level, they are mostly limited to single parameter threshold alarms or simple data dashboard displays, failing to achieve dynamic deduction and fault prediction based on thermoelectric coupling simulation, and have insufficient early warning functions. In the maintenance execution stage, existing systems generally lack the ability to visualize on-site interaction. They cannot use AR technology to project fault models onto real equipment with high precision to guide operations, nor do they have a collaborative mechanism to support remote expert intervention and real-time annotation and guidance, resulting in low maintenance efficiency and a high dependence on personal experience. Summary of the Invention

[0005] The purpose of this invention is to provide a remote diagnostic and on-site maintenance system for power equipment based on remote collaboration, which solves the problems existing in the background technology.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The present invention provides a remote diagnostic and on-site maintenance system for power equipment based on remote collaboration, including a data acquisition module: used to collect environmental parameters of urban underground substations, electrical parameters and physical state parameters of dry-type transformers during operation. The environmental parameters include the temperature and humidity distribution and dust concentration of the urban underground substation. The electrical parameters include the current of each phase winding, the hot spot temperature value of each phase winding, the insulation resistance change rate, and the partial discharge initiation voltage. The physical state parameters include the operating status of the cooling fan and the furfural content.

[0007] Remote diagnostic module: used to build a thermoelectric coupling model of dry-type transformers, identify overheating faults of dry-type transformers, assess the degree of insulation aging of dry-type transformers, determine the discharge type and hazard level of dry-type transformers, and finally output a comprehensive distribution map of fault risks and maintenance priorities for dry-type transformers.

[0008] Preferably, the specific method for constructing the thermoelectric coupling model of the dry-type transformer is as follows: using three-dimensional modeling technology, a three-dimensional geometric model is established by integrating the temperature and humidity distribution, dust concentration and equipment structure of the urban underground substation and the dry-type transformer. Based on the electromagnetic and thermophysical field coupling mechanism, the core loss and winding loss of the dry-type transformer during operation are dynamically calculated. The core loss and winding loss are loaded into the three-dimensional geometric model as heat sources. The heat transfer process is simulated through the three-dimensional geometric model to construct the thermoelectric coupling model of the dry-type transformer and quantify the dynamic coupling relationship of the electrothermal parameters of the dry-type transformer.

[0009] Preferably, the method for identifying overheating faults in dry-type transformers is as follows: the environmental parameters of the dry-type transformer, the current of each phase winding, and the operating status of the cooling fan are input into a thermoelectric coupling model. This model dynamically deduces the heat transfer process under the current parameter conditions based on the electromagnetic and thermophysical field coupling mechanism. If the heat generation rate in the dynamic coupling relationship of the electrothermal parameters of the dry-type transformer output by the thermoelectric coupling model is greater than the heat dissipation rate of the equipment within a preset overheating judgment period, then the dry-type transformer is determined to have an overheating fault.

[0010] Preferably, the method for assessing the insulation aging degree of the dry-type transformer is as follows: the insulation resistance change rate, partial discharge initiation voltage, and furfural content of the dry-type transformer are weighted and summed to obtain the insulation aging characteristic value, which is used to assess the insulation aging degree of the dry-type transformer.

[0011] Based on the insulation aging characteristic values ​​of dry-type transformers, they are classified into three insulation aging levels.

[0012] If the insulation aging characteristic value of a dry-type transformer falls within the range of Level 1 insulation aging level stored in the local database, then the insulation aging level of the dry-type transformer is Level 1.

[0013] If the insulation aging characteristic value of a dry-type transformer falls within the range of the second-level insulation aging level stored in the local database, then the insulation aging level of the dry-type transformer is second-level.

[0014] If the insulation aging characteristic value of a dry-type transformer falls within the range of Level 3 insulation aging levels stored in the local database, then the insulation aging level of the dry-type transformer is Level 3.

[0015] Preferably, the specific method for determining the discharge type and hazard level of the dry-type transformer is as follows: obtaining the dust concentration in the urban underground substation and the partial discharge initiation voltage of the dry-type transformer, obtaining the discharge pulse waveform through a high-frequency current sensor, and matching the corresponding discharge pulse waveform features stored in the local database according to the discharge pulse waveform features corresponding to each discharge pulse waveform stored in the local database.

[0016] If the partial discharge initiation voltage and discharge pulse waveform characteristics of a dry-type transformer match the spike defect discharge characteristics stored in the local database, then the discharge type of the dry-type transformer is determined to be spike defect discharge.

[0017] If the partial discharge initiation voltage and discharge pulse waveform characteristics of a certain dry-type transformer match the air gap defect discharge characteristics stored in the local database, then the discharge type of the dry-type transformer is determined to be air gap defect discharge.

[0018] If the partial discharge initiation voltage and discharge pulse waveform characteristics of a dry-type transformer match the surface creepage characteristics stored in the local database, then the discharge type of the dry-type transformer is determined to be surface creepage.

[0019] The discharge type of the dry-type transformer is obtained, and the corresponding hazard level is matched with the hazard level stored in the local database according to the hazard level of each discharge type of the dry-type transformer. The hazard level includes low risk, medium risk and severe risk.

[0020] When the hazard level of a certain dry-type transformer discharge type is identified as low-risk and the dust concentration is less than the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be low-risk. When the hazard level of a certain dry-type transformer discharge type is identified as low-risk and the dust concentration is greater than or equal to the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be medium-risk. When the hazard level of a certain dry-type transformer discharge type is identified as medium-risk and the dust concentration is less than the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be medium-risk. When the hazard level of a certain dry-type transformer discharge type is identified as medium-risk, but the dust concentration is greater than or equal to the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be high-risk. When the hazard level of a certain dry-type transformer discharge type is identified as high-risk, the discharge hazard level of the dry-type transformer is determined to be high-risk regardless of whether the dust concentration is greater than the safety threshold.

[0021] Preferably, the specific method for outputting the comprehensive distribution map of fault risks and maintenance priorities for the dry-type transformer is as follows: Divide the components of the dry-type transformer into regions, obtain the hot spot temperature values ​​of each phase winding of each component, spatially map and overlay the identified overheating faults, insulation aging degrees, discharge types, and hazard levels of the dry-type transformer components with the constructed thermoelectric coupling model, label the discharge type and hazard level in the discharge component region, render the insulation component region with different colors according to the insulation aging level, and overheating fault component regions are overlaid on the heat-generating components of the model in the form of a heat map, ultimately outputting the comprehensive distribution map of fault risks for the dry-type transformer.

[0022] The maintenance priority of each component of a dry-type transformer is based on the comprehensive risk value. ,in This is a characteristic value for overheating faults. If the component has an overheating fault, it is recorded as 1; otherwise, it is recorded as 0. This represents the numerical value for the level of hazard caused by electrical discharge. The value represents the hazard level of insulation aging. When all components of a dry-type transformer fail simultaneously, the maintenance priority is ranked according to the comprehensive risk value of each component. The higher the comprehensive risk value, the higher the priority of maintenance.

[0023] Remote maintenance module: Used to generate 3D visualized maintenance plans, map dry-type transformer fault data to a digital twin using AR devices, support experts to remotely perform virtual annotation and real-time guidance, record maintenance process data, and evaluate the compliance of maintenance operations.

[0024] Preferably, the method for generating the three-dimensional visualization maintenance plan is as follows: calculate the maintenance priority of each component based on the comprehensive distribution map of fault risks of dry-type transformers, and match the corresponding maintenance operation step list stored in the local database with the maintenance operation step list corresponding to the overheating fault, insulation aging degree, and discharge hazard level of the maintenance component.

[0025] Preferably, the method for mapping dry-type transformer fault data to a digital twin using AR devices is as follows: the thermoelectric coupling model after spatial mapping and superposition of overheating faults, insulation aging degree, discharge type and hazard level of dry-type transformer components is associated with the corresponding digital twin and the components are calibrated. Through the spatial positioning and three-dimensional registration technology of AR devices, the fault data is mapped to the corresponding component area of ​​the digital twin in a visual manner, and then superimposed onto the real dry-type transformer in the field of view of on-site maintenance personnel.

[0026] Preferably, the method for supporting remote virtual annotation and real-time guidance by experts is as follows: Experts access a digital twin of the fault data mapped by the AR device terminal and overlay it onto the view of the real dry-type transformer in the field of vision of the on-site maintenance personnel. On the interactive interface of the AR device terminal, the corresponding real components in the digital twin can be virtually annotated and overlaid in the field of vision of the maintenance personnel. At the same time, a two-way voice communication link is established through the network connection between the AR device and its terminal. Experts remotely guide the maintenance personnel on-site operations through voice and real-time images, and can dynamically correct or add virtual annotations.

[0027] Preferably, the specific method for recording maintenance process data and evaluating the compliance of maintenance operations is as follows: the maintenance process data of the maintenance personnel is captured and recorded in real time through the sensors and visual recognition of the AR device; the maintenance process data of the maintenance personnel is compared with the maintenance operation step list; and a judgment is made based on the compliance rules of maintenance operations stored in the local database. If the allowable deviation range between the maintenance process data of the maintenance personnel and the maintenance operation step list exceeds the range of the compliance rules of maintenance operations stored in the local database, it is judged as a violation; otherwise, it is judged as a compliant operation.

[0028] The beneficial effects of the present invention are as follows: (1) The first part of the present invention: by acquiring the environment of the underground substation, electrical parameters of the dry transformer and physical state parameters, it provides multi-dimensional and high-quality data support for subsequent diagnosis.

[0029] (2) The second part of the present invention: By quantifying the relationship between electrothermal parameters through a thermoelectric coupling model, the overheating fault of dry-type transformer can be accurately identified, the degree of insulation aging can be assessed and the discharge hazard level can be determined, and the accurate identification of multiple core faults can be achieved. By outputting a comprehensive distribution map of fault risks and maintenance priorities, the risk status of equipment can be presented intuitively, allowing maintenance personnel to quickly grasp the key information of the fault, providing clear guidance for the allocation and prioritization of maintenance resources, and improving the pertinence and efficiency of fault handling.

[0030] (3) The third part of the present invention: generating a three-dimensional visualization maintenance solution, mapping fault data to a digital twin and superimposing it on the real equipment through an AR device, supporting remote virtual annotation and real-time guidance by experts, synchronously recording maintenance data and evaluating compliance, standardizing operating procedures, improving maintenance efficiency, reducing downtime, and realizing digital management and control of maintenance. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the system modules of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] Reference Figure 1 As shown, the present invention provides a remote diagnostic and on-site maintenance system for power equipment based on remote collaboration, including: a data acquisition module, a remote diagnostic module, a remote maintenance module, and a local database.

[0035] It should be noted that the data acquisition module is connected to the remote diagnostic module, the remote diagnostic module is connected to the remote maintenance module, and the local database is connected to the data acquisition module, the remote diagnostic module, and the remote maintenance module.

[0036] The data acquisition module is used to collect environmental parameters, electrical parameters and physical state parameters of the urban underground substation during operation. The environmental parameters include the temperature and humidity distribution and dust concentration of the urban underground substation. The electrical parameters include the current of each phase winding, the hot spot temperature of each phase winding, the insulation resistance change rate, and the partial discharge initiation voltage. The physical state parameters include the operating status of the cooling fan and the furfural content.

[0037] It should be noted that the temperature and humidity distribution of the urban underground substation is obtained through distributed digital temperature and humidity sensors, the dust concentration is obtained through laser dust concentration sensors, the current of each phase winding is collected through current transformers, the hot spot temperature values ​​of each phase winding are obtained through pre-embedded fiber optic grating temperature sensors, the insulation resistance change rate is collected through an online insulation resistance monitoring device, the partial discharge initiation voltage is obtained through a high-frequency current sensor, the operating status of the cooling fan is collected through a vibration sensor, and the furfural content data is obtained by receiving the analysis results of a laboratory high-performance liquid chromatograph.

[0038] It should be noted that the hot spot temperature value refers to the temperature value of the local point with the highest temperature in the winding of a dry-type transformer. This point is the weakest part of the insulation system, and its temperature directly determines the thermal aging rate and life of the equipment. It is a key parameter for identifying overheating faults.

[0039] It should be noted that the partial discharge initiation voltage refers to the lowest voltage at which a repetitive partial discharge pulse is first observed during the voltage boosting process. The term "partial" refers to the discharge occurring at a local defect in the insulating medium, such as a spike defect or an air gap defect, rather than a complete breakdown.

[0040] Remote diagnostic module: used to build a thermoelectric coupling model of dry-type transformers, identify overheating faults of dry-type transformers, assess the degree of insulation aging of dry-type transformers, determine the discharge type and hazard level of dry-type transformers, and finally output a comprehensive distribution map of fault risks and maintenance priorities for dry-type transformers.

[0041] In a specific embodiment of the present invention, the method for constructing the thermoelectric coupling model of the dry-type transformer is as follows: using three-dimensional modeling technology, a three-dimensional geometric model is established by integrating the temperature and humidity distribution, dust concentration and equipment structure of the urban underground substation and the dry-type transformer. Based on the electromagnetic and thermophysical field coupling mechanism, the core loss and winding loss of the dry-type transformer during operation are dynamically calculated. The core loss and winding loss are loaded into the three-dimensional geometric model as heat sources. The heat transfer process is simulated through the three-dimensional geometric model to construct the thermoelectric coupling model of the dry-type transformer and quantify the dynamic coupling relationship of the electrothermal parameters of the dry-type transformer.

[0042] The equipment structure includes, but is not limited to, the core, windings, insulation layer, and heat dissipation duct of a dry-type transformer.

[0043] It should be noted that the electromagnetic and thermophysical coupling mechanism refers to the conversion of the electromagnetic loss of the dry-type transformer into a heat source. Temperature changes will have a reaction effect on the electrical parameters of the dry-type transformer. Quantifying the dynamic coupling relationship of electrothermal parameters provides physical mechanism support for overheating fault diagnosis, insulation aging assessment and discharge hazard classification. However, thermoelectric coupling is affected by environmental factors.

[0044] For example, consider the dynamic coupling relationship of electrothermal parameters. In a thermoelectric coupling model of a dry-type transformer in an underground substation in a city, the input low-voltage winding current is 100A, the current dust concentration is 50μg / m³, and the cooling fan is operating normally. At this time, the winding loss (heat generation rate) is 4.0kW, and the heat dissipation rate is also 4.0kW. The dry-type transformer is in thermal equilibrium and there is no risk of overheating. When the low-voltage winding current increases to 150A due to a surge in load, the dust concentration remains at 50μg / m³, and the cooling fan is still operating normally. At this time, the winding loss (heat generation rate) is 9.0kW. The heat dissipation rate mainly depends on environmental conditions, not current changes. The dust concentration remains unchanged, and the cooling fan is operating normally, so the heat dissipation rate remains constant at 4.0kW. The dry-type transformer is now operating at a rate where the heat generation rate is greater than the heat dissipation rate, causing the transformer temperature to rise, posing an overheating risk. Furthermore, the increased temperature leads to increased resistance in each phase winding.

[0045] When the low-voltage side current increases from 100A to 150A, the winding loss will increase to 2.25 times the original value because the loss is proportional to the square of the current. This will cause a sudden increase in local temperature. When the winding temperature rises from 70℃ to 100℃, the resistivity will increase to 12% of the original value. Therefore, under the same load, an additional 12% of heat loss will be generated. When the dust concentration increases from 50μg / m³ to 200μg / m³, the heat dissipation efficiency will decrease by 15%, causing the hot spot temperature to rise by 8~10℃ and accelerating insulation aging.

[0046] In one specific embodiment, the core loss and winding loss of a dry-type transformer during operation are dynamically calculated. The specific calculation method is as follows: the core loss is divided into hysteresis loss and eddy current loss. Hysteresis loss refers to the heat generated by the repeated flipping of magnetic domains inside the silicon steel in an alternating magnetic field and molecular friction. The hysteresis loss is calculated according to the Steinmetz equation. Eddy current loss refers to the circular current induced in the silicon steel sheet by the alternating magnetic field. The current flows through the resistor and generates Joule heat. The square of the current is multiplied by the DC resistance and then by the value of the AC resistance increment coefficient caused by eddy current calculated by the Dowell model to obtain the eddy current loss. The values ​​of hysteresis loss and eddy current loss are added together to obtain the core loss. The winding loss refers to the reduction in the effective cross-sectional area of ​​the conductor under high-frequency current. Its equivalent AC resistance is significantly higher than the DC resistance, which will aggravate the loss. In addition, the alternating magnetic fields generated between multiple current-carrying conductors that are close to each other will interfere with each other, inducing eddy currents in adjacent conductors, resulting in additional losses due to further distortion of the current distribution. The winding loss is also obtained by the Dowell model.

[0047] It should be noted that the Steinmetz equation is used to estimate the hysteresis loss of ferromagnetic materials in an alternating magnetic field, while the Dowell model is an existing technology and a classic and widely used engineering model in the fields of power electronics and transformer design. Both are relatively mature and will not be elaborated on here.

[0048] The simulated heat transfer process involves heat being conducted from the high-temperature zone to the surface through the insulating material, with the surface heat being carried away by the air, while the high-temperature surface dissipates heat through infrared radiation.

[0049] In a specific embodiment of the present invention, the method for identifying overheating faults in dry-type transformers is as follows: the environmental parameters of the dry-type transformer, the current of each phase winding, and the operating status of the cooling fan are input into a thermoelectric coupling model. This model dynamically deduces the heat transfer process under the current parameter conditions based on the electromagnetic and thermophysical field coupling mechanism. If the heat generation rate in the dynamic coupling relationship of the electrothermal parameters of the dry-type transformer output by the thermoelectric coupling model is greater than the heat dissipation rate of the equipment within a preset overheating judgment period, then the dry-type transformer is determined to have an overheating fault.

[0050] For example, the overheating determination period ranges from 2 minutes to 10 minutes, such as an overheating determination period of 3 minutes or 5 minutes.

[0051] In a specific embodiment of the present invention, the method for evaluating the insulation aging degree of a dry-type transformer is as follows: the insulation resistance change rate, partial discharge initiation voltage, and furfural content of the dry-type transformer are weighted and summed to obtain insulation aging characteristic values, which are used to evaluate the insulation aging degree of the dry-type transformer.

[0052] Based on the insulation aging characteristic values ​​of dry-type transformers, they are classified into three insulation aging levels.

[0053] If the insulation aging characteristic value of a dry-type transformer falls within the range of Level 1 insulation aging level stored in the local database, then the insulation aging level of the dry-type transformer is Level 1.

[0054] If the insulation aging characteristic value of a dry-type transformer falls within the range of the second-level insulation aging level stored in the local database, then the insulation aging level of the dry-type transformer is second-level.

[0055] If the insulation aging characteristic value of a dry-type transformer falls within the range of Level 3 insulation aging levels stored in the local database, then the insulation aging level of the dry-type transformer is Level 3.

[0056] It should be noted that the rate of change of insulation resistance reflects the trend of deterioration of the conductivity of the insulation material, the partial discharge initiation voltage characterizes the severity of internal defects in the insulation material, and the furfural content is a product of the chemical degradation of the insulation material.

[0057] It should be noted that the aging degree of primary insulation is greater than that of secondary insulation, and the aging degree of secondary insulation is greater than that of tertiary insulation.

[0058] The weighted summation specifically involves summing the insulation state characteristic values ​​of the dry-type transformer with their corresponding weighting coefficients. The weighting coefficients for each insulation state characteristic parameter are obtained from the data warehouse. The weighting coefficients for each insulation state characteristic parameter reflect the degree and direction of the influence of the insulation state on the insulation aging characteristic values. The direction of influence includes both positive and negative influences.

[0059] For example, taking the insulation aging characteristic value obtained from a certain dry-type transformer as an example, the furfural content... The greatest impact is exerted by the partial discharge initiation voltage, which is also positive. The lower the initial voltage value, the more severe the internal defects in the insulation, the faster the aging rate, and the negative impact. Finally, the insulation resistance change rate is affected. The faster the resistance decreases, the faster the overall insulation aging accelerates, with a negative impact. The weighting coefficients for furfural content, partial discharge initiation voltage, and insulation resistance change rate can be set to 0.5, -0.35, and -0.15, respectively. The characteristic value of insulation aging for a dry-type transformer is then calculated as follows: .

[0060] In a specific embodiment of the present invention, the method for determining the discharge type and hazard level of the dry-type transformer is as follows: obtaining the dust concentration in the urban underground substation and the partial discharge initiation voltage of the dry-type transformer, obtaining the discharge pulse waveform through a high-frequency current sensor, and matching the corresponding discharge pulse waveform features stored in the local database according to the discharge pulse waveform features corresponding to each discharge pulse waveform stored in the local database.

[0061] If the partial discharge initiation voltage and discharge pulse waveform characteristics of a dry-type transformer match the spike defect discharge characteristics stored in the local database, then the discharge type of the dry-type transformer is determined to be spike defect discharge.

[0062] If the partial discharge initiation voltage and discharge pulse waveform characteristics of a certain dry-type transformer match the air gap defect discharge characteristics stored in the local database, then the discharge type of the dry-type transformer is determined to be air gap defect discharge.

[0063] If the partial discharge initiation voltage and discharge pulse waveform characteristics of a dry-type transformer match the surface creepage characteristics stored in the local database, then the discharge type of the dry-type transformer is determined to be surface creepage.

[0064] The discharge type of the dry-type transformer is obtained, and the corresponding hazard level is matched with the hazard level stored in the local database according to the hazard level of each discharge type of the dry-type transformer. The hazard level includes low risk, medium risk and severe risk.

[0065] When the hazard level of a certain dry-type transformer discharge type is identified as low-risk and the dust concentration is less than the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be low-risk. When the hazard level of a certain dry-type transformer discharge type is identified as low-risk and the dust concentration is greater than or equal to the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be medium-risk. When the hazard level of a certain dry-type transformer discharge type is identified as medium-risk and the dust concentration is less than the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be medium-risk. When the hazard level of a certain dry-type transformer discharge type is identified as medium-risk, but the dust concentration is greater than or equal to the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be high-risk. When the hazard level of a certain dry-type transformer discharge type is identified as high-risk, the discharge hazard level of the dry-type transformer is determined to be high-risk regardless of whether the dust concentration is greater than the safety threshold.

[0066] It should be noted that matching discharge pulse waveform characteristics is used to transform the original, messy discharge signal into a clear indicator that can identify the discharge type.

[0067] For example, discharge pulse waveform characteristics, such as pulse rise time and discharge quantity fluctuation amplitude.

[0068] For example, the discharge characteristics of spike defects are that the local initiation voltage is usually less than 30% of the rated phase voltage of the equipment, the discharge quantity is usually greater than 1000pC and the amplitude fluctuation range is less than ±15%, the pulse rise time is usually less than 20 nanoseconds, and the pulses are stably concentrated near the peak values ​​of the first and third quadrants of the power frequency voltage in the phase-discharge spectrum. The discharge characteristics of air gap defects are that the local initiation voltage is usually between 30% and 60% of the rated phase voltage, the discharge quantity is usually fluctuating in the range of 200pC to 1500pC and the fluctuation range is greater than ±30%, the pulse rise time is usually between 20 nanoseconds and 200 nanoseconds, and the pulses are scattered and appear as irregular dots in the phase-discharge spectrum. The local initiation voltage of surface creepage characteristics is usually higher than 80% of the rated phase voltage, the discharge quantity range is usually extended from 50pC to 3000pC, and the pulses are extremely densely distributed near the voltage zero crossing point in the phase-discharge spectrum and form a continuous band-like distribution, making it difficult to separate individual pulses.

[0069] It should be noted that the discharge quantity range of the surface creepage is extremely wide. Its broad distribution range may cover the typical discharge quantity range of air gap defect discharge and spike defect discharge in diagnosis. Therefore, in the diagnostic logic of this system, the discharge type cannot be reliably distinguished by the single parameter of discharge quantity alone. It is necessary to combine its most representative characteristics, namely the highest local starting voltage and the pulse densely distributed near the voltage zero crossing point in the phase spectrum and forming a continuous banded distribution, for comprehensive judgment.

[0070] It should be noted that the above discharge characteristic ranges are the optimal ranges for each discharge characteristic obtained by experts through typical experimental data.

[0071] It should be noted that air gap defect discharge is a low-risk discharge type, spike defect discharge is a medium-risk discharge type, and surface creepage is a high-risk discharge type.

[0072] In a specific embodiment of the present invention, the method for finally outputting the comprehensive distribution map of fault risks and maintenance priorities for dry-type transformers is as follows: the components of the dry-type transformer are divided into regions, the hot spot temperature values ​​of each phase winding of each component are obtained, the overheating faults, insulation aging degree, discharge type and hazard level of the identified dry-type transformer components are spatially mapped and superimposed with the constructed thermoelectric coupling model, the discharge type and hazard level are marked in the discharge component region, the insulation component region is rendered with different colors according to the insulation aging level, and the overheating fault component region is superimposed on the heat-generating component of the model in the form of a heat map, and finally the comprehensive distribution map of fault risks for dry-type transformers is output.

[0073] The maintenance priority of each component of a dry-type transformer is based on the comprehensive risk value. ,in This is a characteristic value for overheating faults. If the component has an overheating fault, it is recorded as 1; otherwise, it is recorded as 0. This represents the numerical value for the level of hazard caused by electrical discharge. The value represents the hazard level of insulation aging. When all components of a dry-type transformer fail simultaneously, the maintenance priority is ranked according to the comprehensive risk value of each component. The higher the comprehensive risk value, the higher the priority of maintenance.

[0074] For example, the insulation component area is rendered with different colors according to the insulation aging level. The insulation component area is rendered in red when the insulation aging level is level one, in yellow when the insulation aging level is level two, and in green when the insulation aging level is level three.

[0075] It should be noted that the ratio of the discharge hazard level to the insulation aging hazard level is based on common knowledge and the ratio obtained by electrical experts through historical data experiments.

[0076] It should be noted that the discharge hazard level value is obtained by acquiring the discharge hazard level of the dry-type transformer components, matching the value stored in the local database with the corresponding value of the discharge hazard level stored in the local database.

[0077] It should be noted that the hazard value of the insulation aging level is obtained by acquiring the insulation aging level of the dry-type transformer components and matching the hazard value corresponding to the insulation aging level stored in the local database with the hazard value stored in the local database.

[0078] In one specific embodiment, the overheating fault component area is superimposed on the heat-generating component in the model in the form of a heat map. The specific method is as follows: the heat transfer process is simulated according to the thermoelectric coupling model. When an overheating fault is identified, the heat map is triggered to generate. When the hot spot temperature value of each phase winding of the dry-type transformer component is within the preset safe temperature range, it is marked in blue. When the hot spot temperature value of each phase winding of the dry-type transformer component is within the preset warning temperature range, it is marked in orange. When the hot spot temperature value of each phase winding of the dry-type transformer component is within the preset fault temperature range, it is marked in purple.

[0079] Remote maintenance module: Used to generate 3D visualized maintenance plans, map dry-type transformer fault data to a digital twin using AR devices, support experts to remotely perform virtual annotation and real-time guidance, record maintenance process data, and evaluate the compliance of maintenance operations.

[0080] In a specific embodiment of the present invention, the method for generating a three-dimensional visualization maintenance plan is as follows: calculate the maintenance priority of each component based on the comprehensive distribution map of fault risks of dry-type transformers, and match the corresponding maintenance operation step list stored in the local database with the maintenance operation step list corresponding to the overheating fault, insulation aging degree, and discharge hazard level of the maintenance component.

[0081] It should be noted that the maintenance operation procedure list includes, but is not limited to, the tools required for each type of fault, complete operation guidelines for routine maintenance and component replacement for each type of fault, and precautions during maintenance.

[0082] In a specific embodiment of the present invention, the method of mapping dry-type transformer fault data to a digital twin using AR devices is as follows: the thermoelectric coupling model after spatial mapping and superposition of overheating faults, insulation aging degree, discharge type and hazard level of dry-type transformer components is associated with the corresponding digital twin and the components are calibrated. Through the spatial positioning and three-dimensional registration technology of AR devices, the fault data is mapped to the corresponding component area of ​​the digital twin in a visual manner, and then superimposed on the real dry-type transformer in the field of view of on-site maintenance personnel.

[0083] It should be noted that the thermoelectric coupling model is the core computing engine that drives the digital twin to achieve diagnostic functions, while the digital twin is a comprehensive carrier and presentation platform that contains, integrates, and visualizes the thermoelectric coupling model and all other information.

[0084] It should be noted that data association and component calibration of the thermoelectric coupling model are performed to ensure that the virtual digital twin and the physical real transformer are the same object and in the same coordinate system.

[0085] It should be noted that 3D registration technology refers to the core technology in AR systems. It mainly solves the problem of how to accurately align virtual objects with the real world, ensuring that virtual information can be stably and naturally attached to specific locations in the real scene. This technology is already quite mature and will not be elaborated on here.

[0086] In a specific embodiment of the present invention, the method for supporting remote virtual annotation and real-time guidance by experts is as follows: Experts access a digital twin of the fault data mapped by the terminal of the AR device and overlay it onto the view of the real dry-type transformer in the field of vision of the on-site maintenance personnel. On the interactive interface of the AR device terminal, the corresponding real components in the digital twin can be virtually annotated and overlaid in the field of vision of the maintenance personnel. At the same time, a two-way voice communication link is established through the network connection between the AR device and its terminal. Experts remotely guide the maintenance personnel on-site operations through voice and real-time images, and can dynamically correct or add virtual annotations.

[0087] For example, virtual annotation operations include: pointing with arrows, drawing circles, and adding text annotations to a faulty component of a dry-type transformer.

[0088] In a specific embodiment of the present invention, the method for recording maintenance process data and evaluating the compliance of maintenance operations is as follows: the maintenance process data of the maintenance personnel is captured and recorded in real time through the sensors and visual recognition of the AR device; the maintenance process data of the maintenance personnel is compared with the maintenance operation step list; and a judgment is made based on the compliance rules of maintenance operations stored in the local database. If the allowable deviation range between the maintenance personnel's maintenance process data and the maintenance operation step list exceeds the range of the compliance rules of maintenance operations stored in the local database, it is determined to be a violation; otherwise, it is determined to be a compliant operation.

[0089] For example, maintenance process data, such as the order of operation steps, the type of tools used, and the model of the replaced parts.

[0090] It should be noted that the formulas described above, through the principle of dimensional consistency and mathematical standardization methods, such as normalization, dimensionless parameter conversion, or unit system unification, can translate physical quantities with different properties into unitless standard values ​​or superimposed parameters of the same dimension. This eliminates the interference of different dimensions on the computational logic, allowing the formulas to retain the original data distribution characteristics while possessing mathematical rationality and adaptability to objective laws. The descriptions are merely exemplary embodiments of the present invention and should not be construed as limiting the scope of the invention.

[0091] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A remote diagnostic and on-site maintenance system for power equipment based on remote collaboration, characterized in that, include: Data acquisition module: used to collect environmental parameters, electrical parameters and physical state parameters of dry-type transformers during operation in urban underground substations. The environmental parameters include temperature and humidity distribution and dust concentration in urban underground substations. The electrical parameters include winding current of each phase, hot spot temperature of each phase winding, insulation resistance change rate and partial discharge initiation voltage. The physical state parameters include cooling fan operation status and furfural content. Remote diagnostic module: used to build a thermoelectric coupling model of dry-type transformers, identify overheating faults of dry-type transformers, assess the degree of insulation aging of dry-type transformers, determine the discharge type and hazard level of dry-type transformers, and finally output a comprehensive distribution map of fault risks and maintenance priorities of dry-type transformers. Remote maintenance module: Used to generate 3D visualized maintenance plans, map dry-type transformer fault data to a digital twin using AR devices, support experts to remotely perform virtual annotation and real-time guidance, record maintenance process data, and evaluate the compliance of maintenance operations.

2. The remote diagnostic and on-site maintenance system for power equipment based on remote collaboration according to claim 1, characterized in that, The specific method for constructing the thermoelectric coupling model of the dry-type transformer is as follows: Using 3D modeling technology, a 3D geometric model is established by integrating the temperature and humidity distribution, dust concentration, and equipment structure of the dry-type transformer in the urban underground substation. Based on the electromagnetic and thermophysical field coupling mechanism, the core loss and winding loss of the dry-type transformer during operation are dynamically calculated. The core loss and winding loss are loaded into the 3D geometric model as heat sources. The heat transfer process is simulated through the 3D geometric model, and a thermoelectric coupling model of the dry-type transformer is constructed to quantify the dynamic coupling relationship of the electrothermal parameters of the dry-type transformer.

3. The remote diagnostic and on-site maintenance system for power equipment based on remote collaboration according to claim 2, characterized in that, The specific method for identifying overheating faults in dry-type transformers is as follows: The environmental parameters of the dry-type transformer, the current of each phase winding, and the operating status of the cooling fan are input into the thermoelectric coupling model. The model dynamically deduces the heat transfer process under the current parameter conditions based on the electromagnetic and thermophysical field coupling mechanism. If the heat generation rate in the dynamic coupling relationship of the dry-type transformer electrothermal parameters output by the thermoelectric coupling model is greater than the heat dissipation rate of the equipment within the preset overheating judgment period, the dry-type transformer is judged to have an overheating fault.

4. The remote diagnostic and on-site maintenance system for power equipment based on remote collaboration according to claim 3, characterized in that, The specific method for assessing the insulation aging degree of dry-type transformers is as follows: The insulation aging characteristic value is obtained by weighted summing of the insulation resistance change rate, partial discharge initiation voltage, and furfural content of the dry-type transformer, which is used to assess the degree of insulation aging of the dry-type transformer. Based on the insulation aging characteristic values ​​of dry-type transformers, they are classified into three insulation aging levels. If the insulation aging characteristic value of a dry-type transformer is within the range of Level 1 insulation aging level stored in the local database, then the insulation aging level of the dry-type transformer is Level 1. If the insulation aging characteristic value of a dry-type transformer falls within the range of the second-level insulation aging level stored in the local database, then the insulation aging level of the dry-type transformer is second-level. If the insulation aging characteristic value of a dry-type transformer falls within the range of Level 3 insulation aging levels stored in the local database, then the insulation aging level of the dry-type transformer is Level 3.

5. A remote diagnostic and on-site maintenance system for power equipment based on remote collaboration as described in claim 4, characterized in that, The specific method for determining the discharge type and hazard level of a dry-type transformer is as follows: The dust concentration and partial discharge initiation voltage of the dry-type transformer in the urban underground substation are obtained. The discharge pulse waveform is obtained through a high-frequency current sensor. Based on the discharge pulse waveform characteristics corresponding to each discharge pulse waveform stored in the local database, the corresponding discharge pulse waveform characteristics stored in the local database are matched. If the partial discharge initiation voltage and discharge pulse waveform characteristics of a certain dry-type transformer match the spike defect discharge characteristics stored in the local database, then the discharge type of the dry-type transformer is determined to be spike defect discharge. If the partial discharge initiation voltage and discharge pulse waveform characteristics of a certain dry-type transformer match the air gap defect discharge characteristics stored in the local database, then the discharge type of the dry-type transformer is determined to be air gap defect discharge. If the partial discharge initiation voltage and discharge pulse waveform characteristics of a certain dry-type transformer match the surface creepage characteristics stored in the local database, then the discharge type of the dry-type transformer is determined to be surface creepage. Obtain the discharge type of the dry-type transformer, and match the corresponding hazard level stored in the local database with the hazard level of each discharge type of the dry-type transformer. The hazard level includes low risk, medium risk, and severe risk. When the hazard level of a certain dry-type transformer discharge type is identified as low-risk and the dust concentration is less than the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be low-risk. When the hazard level of a certain dry-type transformer discharge type is identified as low-risk and the dust concentration is greater than or equal to the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be medium-risk. When the hazard level of a certain dry-type transformer discharge type is identified as medium-risk and the dust concentration is less than the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be medium-risk. When the hazard level of a certain dry-type transformer discharge type is identified as medium-risk, but the dust concentration is greater than or equal to the preset safety threshold, the discharge hazard level of the dry-type transformer is determined to be high-risk. When the hazard level of a certain dry-type transformer discharge type is identified as high-risk, the discharge hazard level of the dry-type transformer is determined to be high-risk regardless of whether the dust concentration is greater than the safety threshold.

6. The remote diagnostic and on-site maintenance system for power equipment based on remote collaboration according to claim 5, characterized in that, The specific method for the final output dry-type transformer fault risk comprehensive distribution map and maintenance priority is as follows: The dry-type transformer is divided into regions, and the hot spot temperature values ​​of each phase winding of each component are obtained. The overheating faults, insulation aging degree, discharge type and hazard level of the identified dry-type transformer components are spatially mapped and superimposed with the constructed thermoelectric coupling model. The discharge type and hazard level are marked in the discharge component area, and the insulation component area is rendered with different colors according to the insulation aging level. For the overheating fault component area, the heat-generating component is superimposed on the model in the form of a heat map. Finally, a comprehensive distribution map of fault risk of dry-type transformer is output. The maintenance priority of each component of a dry-type transformer is based on the comprehensive risk value. ,in This is a characteristic value for overheating faults. If the component has an overheating fault, it is recorded as 1; otherwise, it is recorded as 0. This represents the numerical value for the level of electrical discharge hazard. The value represents the hazard level of insulation aging. When all components of a dry-type transformer fail simultaneously, the maintenance priority is ranked according to the comprehensive risk value of each component. The higher the comprehensive risk value, the higher the priority of maintenance.

7. A remote diagnostic and on-site maintenance system for power equipment based on remote collaboration as described in claim 6, characterized in that, The specific method for generating the 3D visualization repair solution is as follows: The maintenance priority of each component is calculated based on the comprehensive distribution map of fault risks of dry-type transformers. Based on the overheating fault, insulation aging degree, and discharge hazard level of the component to be maintained, the corresponding maintenance operation step list stored in the local database is matched with the maintenance operation step list corresponding to the overheating fault, insulation aging degree, and discharge hazard level stored in the local database.

8. A remote diagnostic and on-site maintenance system for power equipment based on remote collaboration as described in claim 7, characterized in that, The specific method for mapping dry-type transformer fault data to a digital twin using AR devices is as follows: The thermoelectric coupling model, which spatially maps and superimposes the overheating faults, insulation aging degree, discharge type and hazard level of dry-type transformer components, is associated with the corresponding digital twin and the components are calibrated. Through the spatial positioning and 3D registration technology of AR equipment, the fault data is visualized and mapped to the corresponding component area of ​​the digital twin, and then superimposed onto the real dry-type transformer in the field of view of the on-site maintenance personnel.

9. A remote diagnostic and on-site maintenance system for power equipment based on remote collaboration as described in claim 8, characterized in that, The specific method for supporting remote virtual annotation and real-time guidance by experts is as follows: Experts access a digital twin mapped with fault data via an AR device terminal and overlay it onto the view of a real dry-type transformer in the field of vision of on-site maintenance personnel. On the interactive interface of the AR device terminal, the corresponding real components in the digital twin can be virtually annotated and overlaid in the field of vision of maintenance personnel. At the same time, a two-way voice communication link is established through the network connection between the AR device and its terminal. Experts can remotely guide maintenance personnel on-site operations through voice and real-time images, and can dynamically correct or add virtual annotations.

10. A remote diagnostic and on-site maintenance system for power equipment based on remote collaboration as described in claim 9, characterized in that, The specific method for recording maintenance process data and assessing the compliance of maintenance operations is as follows: The AR device uses sensors and visual recognition to capture and record maintenance personnel's maintenance process data in real time. The maintenance process data is compared with the maintenance operation step list and judged according to the compliance rules of maintenance operations stored in the local database. If the allowable deviation between the maintenance personnel's maintenance process data and the maintenance operation step list exceeds the range of the maintenance operation compliance rules stored in the local database, it is judged as a violation; otherwise, it is judged as a compliant operation.

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