System for monitoring and evaluating leakage current of line insulator of whole-line multi-base tower

Abstract

The embodiment of the invention provides a line insulator leakage current monitoring and evaluation system for a whole-line multi-base tower, and relates to the technical field of power systems, the system comprises a plurality of tower monitoring nodes and an in-station centralized analysis platform, and each base tower is provided with one tower monitoring node. Each tower monitoring node comprises a data acquisition module, a data analysis module and a communication module, and the data acquisition module is used for acquiring insulator leakage current of a tower; the data analysis module is used for analyzing the state type of the single-base insulator based on the insulator leakage current; the communication module is used for uploading the leakage current of the insulator and the state type of the single-base insulator to the in-station centralized analysis platform; and the in-station centralized analysis platform is used for receiving the insulator leakage current and the single-base insulator state type of each base tower, and performing insulation state evaluation on the whole-line multi-base tower according to the insulator leakage current and the single-base insulator state type. According to the invention, the whole-line multi-base tower evaluation can be realized, and the detection efficiency is improved.

Description

Technical Field

[0001] This disclosure relates to the field of power system technology, and in particular to a system for monitoring and evaluating leakage current of line insulators across multiple towers along a complete power line. Background Technology

[0002] As the core backbone of the power system, the safe and stable operation of transmission lines directly determines the reliability of power supply. During long-term operation, line insulators are prone to internal breakdown leading to increased leakage current, or surface contamination causing surface creepage. Both types of problems can induce line faults. At the same time, lightning strikes during the rainy season can easily cause local insulation damage, and fault location is difficult.

[0003] Traditional operation and maintenance relies on infrared imaging inspection, but the current operation and maintenance inspection method is not comprehensive. It can only conduct single-base sampling inspections, which is difficult to cover large-scale scenarios of hundreds of towers along the entire line. The rate of missed detection of hidden dangers is high, and it lacks the ability to conduct multi-base collaborative analysis, making it impossible to assess the overall insulation status of the entire line. Summary of the Invention

[0004] To solve the above-mentioned technical problems, or at least partially solve them, this disclosure provides a system for monitoring and evaluating leakage current of line insulators across multiple towers along a complete line.

[0005] This disclosure provides a system for monitoring and evaluating the leakage current of line insulators across multiple towers along a complete line. The system includes multiple tower monitoring nodes and a centralized analysis platform within the station. One monitoring node is deployed for each tower. Each monitoring node includes a data acquisition module, a data analysis module, and a communication module. The data acquisition module collects the leakage current of the insulators on the tower. The data analysis module analyzes the condition type of each insulator based on the leakage current. The communication module uploads the leakage current and condition type of each insulator to the centralized analysis platform within the station. The centralized analysis platform receives the leakage current and condition type of each insulator from each tower and evaluates the insulation condition of all towers along the entire line based on these data.

[0006] In one possible implementation, the insulator includes a suspension porcelain insulator and a composite insulator. The grounding end of the composite insulator is connected to the upper end of the suspension porcelain insulator, and the lower end of the suspension porcelain insulator is connected to the tower. The data acquisition module includes a surface leakage current sensor and a total leakage current sensor. The surface leakage current sensor is deployed on the composite insulator of the tower and is used to acquire the surface leakage current of the insulator based on a trigger signal. The total leakage current sensor is deployed on the suspension porcelain insulator of the tower and is used to acquire the total leakage current at the root of the insulator based on a trigger signal.

[0007] In one possible implementation, the data analysis module includes a data calculation unit and a single-base state determination unit. The data calculation unit is used to calculate the internal leakage current of the insulator of each tower based on the surface leakage current and the total leakage current at the root of the insulator. The single-base state determination unit is used to analyze the surface leakage current and the internal leakage current of the insulator based on the state determination conditions to determine the state type of the single-base insulator.

[0008] In one possible implementation, the single-base state determination unit is used to determine the state determination conditions corresponding to each state type based on experimental data. The state determination conditions include a surface leakage current threshold and an internal leakage current threshold. Based on the surface leakage current threshold and the internal leakage current threshold, the unit analyzes the surface leakage current and internal leakage current of the insulator to determine the state type of the single-base insulator. This includes: if the surface leakage current is less than or equal to the first surface leakage current threshold, and the internal leakage current is less than or equal to the first internal leakage current, then the single-base insulator state type is determined to be normal; if the surface leakage current is greater than the first surface leakage current threshold, and the internal leakage current is less than or equal to the first internal leakage current, then the single-base insulator state type is determined to be normal; if the surface leakage current is greater than the first surface leakage current threshold, and the internal leakage current is less than or equal to the first internal leakage current, then the single-base insulator state type is determined to be normal. If the leakage current is less than or equal to the internal leakage current of the first insulator, the single-base insulator is judged to be in a surface pollution warning state, and a single-base surface pollution warning is issued; if the internal leakage current of the insulator is greater than the internal leakage current of the first insulator and less than or equal to the internal leakage current of the second insulator, the single-base insulator is judged to be in an internal breakdown warning state, and a single-base internal breakdown warning is issued; if the leakage current along the surface of the insulator is greater than the second leakage current along the surface threshold, or if the internal leakage current of the insulator is greater than the internal leakage current of the second insulator, the single-base insulator is judged to be in a serious fault warning state, and a single-base serious fault warning is issued; the second leakage current along the surface threshold is greater than the first leakage current along the surface threshold.

[0009] In one possible implementation, the tower monitoring node also includes a local preprocessing module, which is used to set the process noise covariance and the observation noise covariance; and to perform Kalman filtering on the insulator surface leakage current and the total leakage current at the insulator root based on the process noise covariance and the observation noise covariance.

[0010] In one possible implementation, each tower monitoring node also includes an auxiliary power supply module, which converts solar energy into electrical energy through photovoltaic modules and supplies power to the data acquisition module, data analysis module, communication module, and local preprocessing module within the tower monitoring node.

[0011] In one possible implementation, the system allocates a corresponding upload time window for each tower monitoring node according to a polling mechanism. The communication module is used to upload the insulator leakage current to the centralized analysis platform within the station in sequence according to the tower number within the upload time window.

[0012] In one possible implementation, the centralized analysis platform within the station includes a data processing module, a multi-base correlation analysis module, and a full-line insulation condition assessment module. The data processing module is used to verify the insulator leakage current and the condition type of a single-base insulator. The multi-base correlation analysis module is used to assess the insulation condition of multi-base towers based on spatial and temporal dimensions, combined with the insulator leakage current and the condition type of a single-base insulator. The full-line insulation condition assessment module is used to assess the insulation condition of all multi-base towers along the entire line, combined with the condition type of a single-base insulator.

[0013] In one possible implementation, the multi-base correlation analysis module is used to divide the entire line of multi-base towers into multiple regions according to spatial dimensions; count the number of towers of each warning state type in each region; when the number of towers exceeds the number threshold, the corresponding region multi-base warning is issued; and count the variation area of ​​the leakage current inside the insulators of the multi-base towers in each region. When the rate of increase of the leakage current inside the insulator exceeds the rate of increase threshold and the duration exceeds the duration threshold, the corresponding region multi-base severe fault warning is issued.

[0014] In one possible implementation, the overall insulation condition assessment module is used to score individual towers based on the condition type of individual insulators; wherein, the score of a tower in normal condition is greater than that of a tower in surface pollution warning condition, the score of a tower in surface pollution warning condition is greater than that of a tower in internal breakdown warning condition, and the score of a tower in internal breakdown warning condition is greater than that of a tower in severe fault warning condition; weights are assigned to individual towers based on their importance; wherein, the higher the importance, the greater the weight; and a weighted average is performed on the individual tower scores and weights for all multi-tower towers along the entire line to obtain the overall insulation condition score for all multi-tower towers.

[0015] In this implementation, this application achieves full data coverage across the entire line through collaborative data acquisition from each tower, overcoming the limitations of traditional single-tower, single-point monitoring, solving the problem of incomplete coverage, and improving the comprehensiveness and scalability of inspections. Simultaneously, combined with single-tower status analysis from the data analysis module, it enables accurate identification of potential hazards, significantly reducing the rate of missed hazard detection and improving the accuracy of hazard identification. Through synchronous data acquisition, standardized aggregation, precise calculation, and multi-dimensional centralized analysis of each tower, the centralized analysis platform within the station combines leakage current data and single-tower status types from each tower, going beyond single-tower insulator status judgment to comprehensively assess the overall insulation status of the entire line, thereby improving detection efficiency and accuracy. Attached Figure Description

[0016] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0017] Figure 1 This disclosure provides a system for monitoring and evaluating leakage current of line insulators across multiple towers along a complete line. Figure 2 A schematic diagram of a pole and insulator provided in an embodiment of this disclosure; Figure 3 A flowchart illustrating a single-base state determination method provided in an embodiment of this disclosure; Figure 4 A schematic flowchart illustrating a method for assessing the insulation status of an entire line, as provided in an embodiment of this disclosure; Figure 5 This is a schematic diagram of the structure of a computing device provided in an embodiment of the present disclosure. Detailed Implementation

[0018] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0019] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0020] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0021] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0022] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0023] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0024] Current single-base online monitoring technology can only achieve single-point data collection, which cannot form a full-line collaborative analysis. The data value is limited, the real-time performance is poor, the inspection cycle is long, and it cannot capture instantaneous hidden dangers. Moreover, the distributed monitoring architecture is mostly a simple data upload, lacking a multi-dimensional centralized analysis model for the characteristics of insulator faults, and thus cannot achieve the prediction of weak sections.

[0025] To address the aforementioned issues, this disclosure provides a system for monitoring and evaluating the leakage current of insulators across multiple towers along a complete power line. The system includes multiple tower monitoring nodes and a centralized analysis platform within the station. One monitoring node is deployed for each tower, and each monitoring node includes a data acquisition module, a data analysis module, and a communication module. The data acquisition module collects the leakage current of the insulators on the tower; the data analysis module analyzes the condition type of each insulator based on the leakage current; and the communication module uploads the leakage current and condition type of each insulator to the centralized analysis platform. The centralized analysis platform receives the leakage current and condition type of each tower and performs an insulation condition assessment of all towers along the entire line based on these data. Through collaborative data collection from each tower, the system achieves full data coverage across the entire line, overcoming the limitations of traditional single-tower, single-point monitoring, solving the problem of incomplete coverage, and improving the comprehensiveness and scalability of inspections. Simultaneously, by combining the single-base status analysis of the data analysis module, the system achieves accurate identification of potential hazards, significantly reducing the rate of missed hazard detection and improving the accuracy of hazard identification. Through synchronous data collection, standardized aggregation, precise calculation, and multi-dimensional centralized analysis of each tower, the centralized analysis platform within the station combines leakage current data and single-base status types of each tower. Beyond judging the status of individual insulators, it can comprehensively assess the overall insulation status of the entire line, improving detection efficiency and accuracy.

[0026] The system will now be described in detail with reference to specific embodiments.

[0027] Figure 1 This disclosure provides a system for monitoring and evaluating leakage current of line insulators across multiple towers along a complete line. The system includes multiple tower monitoring nodes and a centralized analysis platform within the station, with one monitoring node deployed for each tower.

[0028] Each tower monitoring node includes a data acquisition module, which is used to collect the insulator leakage current of the insulators on the tower.

[0029] Specifically, the data acquisition module is equipped with one or more current sensors. For example, the current sensor is a high-precision Hall current sensor, model ACS712-05B, with an accuracy of ±0.5%.

[0030] In one possible implementation, please refer to Figure 2 , Figure 2 This diagram illustrates a pole and insulator according to an embodiment of the present disclosure. The insulator includes a suspension porcelain insulator and a composite insulator. The grounding terminal of the composite insulator is connected to the upper end of the suspension porcelain insulator, and the lower end of the suspension porcelain insulator is connected to the pole. The composite insulator's skirts and sheath are typically made of polymer materials such as silicone rubber, which are prone to leakage current on their surface due to aging and contamination. The suspension porcelain insulator is a sampling resistor connected in series in the circuit. Its rated mechanical tensile strength is greater than that of the composite insulator. Because it is connected in series, all leakage current flowing through the surface of the composite insulator must also flow through the series-connected porcelain insulators, thus forming a total leakage current on the suspension porcelain insulator.

[0031] In one possible implementation, the suspension porcelain insulator is a single-piece suspension porcelain insulator.

[0032] The data acquisition module includes a surface leakage current sensor and a total leakage current sensor.

[0033] Specifically, the surface leakage current sensor is deployed on a brass, 0.5mm thick, annular conductive sheet attached to the surface of the composite insulator on the tower. Its inner diameter matches the outer diameter of the insulator. By extracting the surface leakage current of the insulator from the sheath of the shed at the connection point between the composite insulator and the suspension porcelain insulator, it directly reflects the degree of surface contamination. The surface leakage current is mainly caused by surface contamination such as industrial dust, salt spray, and moisture, which are externally repairable hazards—contamination that can be eliminated through cleaning. For example, the sampling rate is ≥1 kSps, and the accuracy is ±0.5%.

[0034] The total leakage current sensor is deployed on the suspension porcelain insulator of the tower. A wire connects the steel cap (high-voltage end) and steel foot (grounding end) of the porcelain insulator, through which a Hall sensor passes to collect the total leakage current at the insulator root. For example, the sampling rate is ≥1 kSps, with an accuracy of ±0.5%. Understandably, a sampling rate ≥1 kSps, acquiring data 1000 times per second, means that the time window for a single acquisition is only 1 ms. Even with a 1 ms synchronization error, the change in leakage current within this 1 ms time window is ≤0.001 mA, and its impact on the calculation results is negligible.

[0035] Furthermore, the surface leakage current sensor and the total leakage current sensor are triggered by the same trigger signal, and all nodes are calibrated by the Beidou time signal of the station platform with a synchronization error of ≤1ms, ensuring the time consistency of multi-base data and laying the foundation for subsequent multi-base correlation analysis.

[0036] The above methods enable full-line deployment and dual-channel synchronous data acquisition.

[0037] In another possible implementation, the data acquisition module deploys 18 parallel channels. Channel 1 is a surface leakage current sensor, collecting the surface leakage current of the insulator. Channel 2 is a total leakage current sensor, collecting the total leakage current at the root of the insulator, reflecting the superposition of the surface leakage current and the internal leakage current. Channels 3-18 are reserved for extended functions such as multi-insulator monitoring, environmental parameter (temperature, humidity, pollution level) acquisition, and lightning induced current acquisition, adapting to the needs of multi-scenario and multi-parameter collaborative monitoring.

[0038] It is equipped with 18 parallel channels, supports collaborative monitoring of multiple insulators and multiple environmental parameters, adapts to the expansion needs of complex scenarios, and has strong scalability.

[0039] Each tower of the transmission line is deployed according to the above standards, which enables data collection from the beginning to the end of the line without any blind spots.

[0040] Each tower monitoring node also includes a local preprocessing module, which is used to set the process noise covariance and the observation noise covariance; and to perform Kalman filtering on the leakage current along the insulator surface and the total leakage current at the insulator root based on the process noise covariance and the observation noise covariance.

[0041] Specifically, optimal parameters were calibrated based on 100 sets of measured data, resulting in the process noise covariance Q = 1e⁻⁵ and the observation noise covariance R = 1e⁻². A smaller Q indicates a slower change in leakage current, while a larger R indicates stronger suppression of observed noise such as electromagnetic interference and equipment noise. The filter weights are adaptively adjusted by utilizing the dynamic changes in the signal, such as the slow fluctuations in leakage current and the instantaneous changes in interference. This approach can both preserve the changing trend of the true signal and effectively suppress sudden noise.

[0042] In one possible implementation, the local preprocessing module includes a 16-bit ADC analog-to-digital converter unit, model ADS1115, and a digital filtering algorithm. The moving average window length is set to 10 sampling points to realize analog signal conversion, noise removal, and calculation of data RMS value.

[0043] For example, through actual measurement and verification, the signal-to-noise ratio of the filtered signal is ≥60dB, ensuring that the measurement error of the leakage current along the insulator surface and the total leakage current at the root of the insulator is ≤0.3%, which can lay the foundation for the accuracy of the difference calculation.

[0044] It is understandable that the leakage current along the insulator surface and the total leakage current at the insulator root in the high-voltage electromagnetic environment of the transmission line, along with the induced current generated by the high-voltage electric field of the line, cause high-frequency noise in the acquired signal, making the acquired signal susceptible to electromagnetic coupling interference. Wind and vibration cause momentary instability in the contact between the sensor and the insulator, generating instantaneous spike signals, making the acquired signal susceptible to environmental interference. Noise from the sensor's own electronic components, such as zero-point drift of Hall sensors, also makes the acquired signal susceptible to equipment noise interference. The Kalman filter algorithm is used to remove the above-mentioned interference noise in real time, restoring the true current signal.

[0045] Each tower monitoring node also includes a data analysis module, which is used to analyze the condition type of a single insulator based on the insulator leakage current.

[0046] Specifically, the data analysis module includes a data calculation unit and a single-base state judgment unit.

[0047] The data calculation unit is used to calculate the internal leakage current of the insulators of each tower based on the leakage current along the insulator surface and the total leakage current at the root of the insulator.

[0048] Specifically, the internal leakage current of each tower's insulator is obtained by subtracting the surface leakage current from the total leakage current at the insulator root. The internal leakage current reflects the internal insulation performance of the insulator and is a core indicator for judging potential internal breakdown. The current flows through the porcelain or glass body of the insulator and is mainly caused by irreversible internal damage such as aging, cracks, and breakdown of the internal insulation material, which must be resolved by replacing the insulator.

[0049] This application employs dual-channel synchronous triggering and a Kalman filter algorithm to ensure the accuracy of difference calculations, avoiding misjudgments of faults caused by time asynchrony or noise interference. Multi-stage collaboration enables precise detection. Furthermore, by calculating the difference between the total current and the surface current, the core value reflecting internal insulation performance is directly extracted, fundamentally resolving the industry pain point of ambiguous fault types.

[0050] Actual measurements show that the calculation error caused by asynchronous timing is ≤0.1%. For example, if Itotal = 10mA, Isurface = 8mA, and theoretically Iinternal = 2mA, the maximum error is only 2mA × 0.1% = 0.002mA, which does not affect the state judgment at all. The state threshold is 2mA, and the error is far less than the threshold accuracy requirement.

[0051] The single-base state judgment unit is used to analyze the surface leakage current and internal leakage current of the insulator based on the state judgment conditions to determine the state type of the single-base insulator.

[0052] Specifically, the state determination conditions for each state type are first determined based on experimental data; among them, the state determination conditions include the surface leakage current threshold and the internal leakage current threshold.

[0053] In one possible implementation, measured data from 100 sets of insulators in different states were obtained, yielding some key experimental data. Please refer to Table 1, which contains the measured data for insulators in different states.

[0054] Table 1 Measured data of insulators in different states

[0055] ESDD represents the level of filth.

[0056] For example, the first surface leakage current threshold is set to 5mA, the second surface leakage current threshold is set to 10mA, the internal leakage current of the first insulator is set to 2mA, and the internal leakage current of the second insulator is set to 5mA. These thresholds achieve an accuracy rate of 99.5% in determining the condition of insulators in different states, effectively distinguishing between surface contamination and internal breakdown faults. The threshold settings are scientifically sound and reasonable.

[0057] Furthermore, based on the surface leakage current threshold and the internal leakage current threshold, the surface leakage current and internal leakage current of the insulator are analyzed to determine the state type of a single insulator.

[0058] When the surface leakage current of the insulator is less than or equal to the first surface leakage current threshold, and the internal leakage current of the insulator is less than or equal to the first internal leakage current of the insulator, the single-base insulator is judged to be in a normal state and continuous monitoring is performed. When the surface leakage current of the insulator is greater than the first surface leakage current threshold, and the internal leakage current of the insulator is less than or equal to the first internal leakage current of the insulator, the single-base insulator is judged to be in a surface contamination warning state, and a single-base surface contamination warning is issued, and targeted cleaning is arranged. When the internal leakage current of the insulator is greater than the first internal leakage current of the insulator, but less than or equal to the second internal leakage current of the insulator, the single-base insulator is judged to be in an internal breakdown warning state, and a single-base internal breakdown warning is issued, the monitoring cycle is shortened to 10 seconds / time, and preparation for replacement is made. When the surface leakage current of the insulator is greater than the second surface leakage current threshold, or the internal leakage current of the insulator is greater than the second internal leakage current of the insulator, the single-base insulator is judged to be in a serious fault warning state, and a single-base serious fault warning is issued, and the machine is immediately shut down for maintenance and the insulator is replaced.

[0059] For example, please refer to Table 2, which is a classification table of single-base insulator state types.

[0060] Table 2 Classification of Single-Base Insulator Condition Types

[0061] Furthermore, the single-base state judgment results are stored locally in real time as the basic data for the full-line analysis.

[0062] Each tower monitoring node also includes a local storage module for storing local data. For example, the local storage module includes an 8GB SD card and a 128MB Flash chip, capable of storing 30 days of raw data, fault data, and threshold parameters, ensuring no data loss. It uses a MySQL database for partitioned storage, with raw data storage lasting one year, and status assessment results and analysis reports permanently stored, supporting historical traceability and trend analysis.

[0063] Each tower monitoring node also includes a communication module, which is used to upload insulator leakage current and single-base insulator status type to the centralized analysis platform within the station.

[0064] For example, the communication module adopts 5G wireless communication, model Quectel EC200U, with a data transmission rate of ≥100kbps.

[0065] In one possible implementation, the communication module has a time synchronization function with a synchronization error of ≤1ms. Specifically, the node is calibrated using the BeiDou time signal from the on-site platform, with a synchronization error of ≤1ms, ensuring the time consistency of multi-base data and laying the foundation for subsequent multi-base correlation analysis.

[0066] In another possible implementation, the communication module has a time-division multiplexing upload function. Specifically, the system allocates a corresponding upload time window for each tower monitoring node according to a polling mechanism. The communication module is used to upload the insulator leakage current and the single-base insulator status type to the centralized analysis platform within the station in sequence according to the tower number within the upload time window.

[0067] For example, a polling mechanism is used to allocate the upload time window for each node, with each node having an upload window of 100ms. Uploads are made sequentially according to the tower number to avoid network congestion caused by hundreds of nodes uploading at the same time.

[0068] In another possible implementation, the communication module has a data encapsulation function. Specifically, the communication module encapsulates the collected data in a unified format: "tower number-collection time-channel type-current value-CRC32 checksum," which facilitates batch parsing by the on-site platform. The collection time is accurate to milliseconds, the current value is in mA, and it is rounded to three decimal places.

[0069] In another possible implementation, the communication module has a resume capability. Specifically, when communication is interrupted, the data is temporarily stored in the local storage module and named according to the acquisition timestamp and tower number. After the connection is restored, the data is automatically retransmitted in chronological order to ensure data integrity.

[0070] In another possible implementation, the communication module has data transmission priorities. Fault data has a higher priority than warning data, and warning data has a higher priority than normal data. Upload frequency is allocated according to priority; the higher the priority, the higher the frequency. For example, fault data and warning data are uploaded in real time, while normal data is uploaded in batches every minute.

[0071] In another possible implementation, the communication module has data encryption and verification functions. Specifically, it uses AES-256 encryption for transmission, and the data is accompanied by a CRC32 checksum. After being received by the centralized analysis platform within the station, the integrity is verified. Invalid data is automatically retransmitted, with the number of retransmissions ≤ 3. If it is still invalid, it is marked as data missing and an alarm is triggered.

[0072] Each tower monitoring node also includes an auxiliary power supply module, which comprises a power management unit, a charging / discharging unit, and a battery protection unit. The charging / discharging unit converts solar energy into electrical energy using photovoltaic modules and supplies power to the data acquisition module, data analysis module, communication module, local preprocessing module, and local storage module within the tower monitoring node.

[0073] Specifically, the charging and discharging unit combines photovoltaic modules and lithium iron phosphate batteries for power supply. For example, the auxiliary power supply module is model TP5056, with a photovoltaic module power of 500W and a battery capacity of 100Ah. The photovoltaic modules convert light energy into electrical energy, which is then regulated to charge the battery. The battery provides a stable and reliable 12V power supply to each module in the node.

[0074] In one possible implementation, the auxiliary power supply module incorporates temperature adaptive regulation and overcharge / over-discharge protection functions, implemented through a battery protection unit. Specifically, the auxiliary power supply module includes a temperature regulation unit comprising an NTC temperature sensor, a heating plate, and a thermoelectric cooler. The lithium iron phosphate battery is positioned between the heating plate and the thermoelectric cooler. The heating plate provides temperature compensation in cold winter conditions, while the thermoelectric cooler cools the battery in hot summer conditions, ensuring normal operation of the battery in an environment of -50℃ to 60℃ without additional maintenance.

[0075] The centralized analysis platform within the station includes a data processing module, a multi-base correlation analysis module, and a full-line insulation status assessment module.

[0076] The data processing module is used to verify the leakage current of insulators and the condition type of single-base insulators.

[0077] Specifically, abnormal data in the insulator leakage current is removed. For example, the 3σ criterion is used to remove outliers caused by sensor malfunctions and transmission interference, where σ is the standard deviation of data over the past 10 minutes, and the removal rate is ≤0.3%. The status type of a single insulator is verified, and the current status judgment result is confirmed by combining historical data. For example, the average value information over five minutes is used as historical data. If a single data collection triggers an alarm but the five-minute average value does not reach the threshold, it is determined to be a momentary disturbance and no alarm is triggered to avoid false alarms.

[0078] The multi-base correlation analysis module is used to evaluate the insulation status of multi-base towers based on spatial and temporal dimensions, combined with the state type of single-base insulators.

[0079] Based on the spatial dimension, the entire line of multi-base towers is divided into multiple regions according to the spatial dimension. The number of towers of each warning status type in each region is counted. When the number of towers exceeds the threshold, the corresponding regional multi-base warning is issued.

[0080] For example, every 10 poles form a region. The number of poles in each type of warning status within the region is counted. If the number of surface pollution warning statuses is greater than or equal to 3, it is determined that the environmental pollution level of that section has increased, triggering a section warning and prompting maintenance personnel to carry out regional cleaning.

[0081] Based on the time dimension, the variation area of ​​the leakage current inside the insulator of multi-base towers in each region is statistically analyzed. When the rate of increase of the leakage current inside the insulator is greater than the rate of increase threshold and the duration is greater than the duration threshold, a corresponding regional multi-base severe fault warning is issued.

[0082] For example, by continuously analyzing the leakage current trend of multiple base nodes in the same area, if the leakage current inside the insulator continues to rise, that is, the week-on-week increase is ≥20%, and this condition is met for two consecutive weeks, it is predicted that the overall insulation performance of the insulator in this area will deteriorate, and batch replacement can be planned in advance.

[0083] In this implementation, regions are divided according to spatial dimensions, and the entire line of towers is managed in a grid-like manner. This facilitates the identification of areas with concentrated risks and provides a precise location basis for differentiated operation and maintenance. By triggering early warnings based on the number of towers in a warning state within a region, regional insulation hazard clusters can be identified in a timely manner. The dynamic deterioration trend of insulation performance can be captured, and potential serious faults can be warned in advance to avoid sudden power outages.

[0084] The line insulation condition assessment module is used to assess the insulation condition of all multi-base towers along the entire line by combining the condition types of individual insulators.

[0085] Specifically, single-base insulators are scored based on their condition. Towers in normal condition receive higher scores than those in surface pollution warning condition, which in turn receive higher scores than those in internal breakdown warning condition, and finally, those in internal breakdown warning condition receive higher scores than those in severe fault warning condition.

[0086] For example, a score of 100 is set for a pole in normal condition, a score of 70 is set for a pole in surface contamination warning condition, a score of 20 is set for a pole in internal breakdown warning condition, and a score of 0 is set for a pole in serious fault warning condition.

[0087] The weights of individual towers are assigned based on their importance; the higher the importance, the greater the weight.

[0088] For example, poles that cross highways, railways, or rivers are considered important poles and are weighted 1.2; ordinary poles are weighted 1.0, ensuring that the assessment results are consistent with actual operation and maintenance needs.

[0089] The insulation status score of all multi-tower towers along the entire line is obtained by weighted averaging of the individual tower scores and weights.

[0090] In this implementation, the weighted average algorithm of single-base score and importance weight makes the insulation status score of the whole line more in line with the actual operation and maintenance priority, and can provide scientific and quantitative decision support for the formulation of line maintenance plan.

[0091] Furthermore, the insulation status of all towers along the entire line is graded based on an insulation status score. A score of 80 or higher is considered excellent, 60-80 is considered acceptable, and less than 60 is considered unacceptable. The status of each node or section is visualized using a heatmap, with red indicating faulty and warning nodes and yellow indicating potentially weak sections, providing precise targeting for maintenance.

[0092] Furthermore, when a line trips, the leakage current monitoring and assessment system for insulators on all multi-tower towers along the entire line can trace the fault source. Specifically, based on the multi-tower current mutation data within the fault occurrence time window (10 seconds before tripping to 5 seconds after tripping), it locates the tower area with the most significant current mutation. Based on lightning activity monitoring data, it determines whether lightning breakdown has occurred. Specifically, if there is lightning activity in the area during the fault period and the current mutation amplitude is ≥50mA, it is determined to be lightning breakdown. Based on the results of section correlation analysis, it identifies the concentrated fault area and fault type, providing maintenance personnel with accurate criteria for fault cause judgment. Fault types include lightning breakdown, pollution flashover, and internal breakdown.

[0093] The centralized analysis platform within the station also includes a real-time monitoring interface. This interface displays the status of all nodes along the entire line, data acquisition data, and communication status, and supports filtering and querying by tower number, section, and status type.

[0094] The centralized analysis platform within the station also includes daily assessment reports, which output total insulation scores for the entire line, a list of weak sections, details of early warning nodes, and maintenance priority recommendations. The maintenance priority recommendations are sorted by fault, early warning, and potential weakness.

[0095] The centralized analysis platform within the station also includes an alarm notification module. Fault and early warning information is pushed to maintenance personnel via SMS and APP. The fault and early warning information includes the tower number, fault type, handling suggestions, and navigation location, and is integrated with the Gaode Map API.

[0096] In this implementation, each tower is deployed with nodes to solve the problem of incomplete coverage in traditional inspections, reduce the rate of missed detection of hidden dangers, and improve the accuracy of distinguishing between surface contamination and internal breakdown faults by using Kalman filtering and difference calculation after synchronous dual-channel acquisition, thereby avoiding misjudgment and misrepair and reducing operation and maintenance costs. The line insulator leakage current monitoring and assessment system for multiple towers along the entire line proposed in this application is applicable to high-voltage or ultra-high-voltage transmission lines, long-distance lines crossing complex environments such as mountains, hills, and coastlines, supporting lines for new energy power plants, lines in areas with high pollution or lightning incidence, and lines requiring multi-parameter monitoring. It can reduce inspection costs, promote the transformation of transmission line operation and maintenance from periodic inspections to condition-based maintenance, provide digital support for smart grid dispatching, and facilitate the intelligent upgrading of the power grid. Utilizing BeiDou timing, 18 extended channels enhance scenario adaptability, and a 500W+100Ah power supply combination strengthens its adaptability to harsh outdoor environments. It can be widely applied in power grids and new energy power generation companies, with a broad market application space and an estimated annual promotion volume of over a thousand lines.

[0097] Figure 3 This is a flowchart illustrating a single-base state determination method provided in an embodiment of this disclosure. This method can be executed by a data analysis module, which can be implemented in software and / or hardware, and is generally integrated into a computing device. Figure 3 As shown, the method includes: S201. Calculate the internal leakage current of the insulator for each tower based on the surface leakage current and the total leakage current at the root of the insulator.

[0098] S202. Determine the state determination conditions corresponding to each state type based on the experimental data.

[0099] S203. Based on the surface leakage current threshold and the internal leakage current threshold, analyze the surface leakage current and internal leakage current of the insulator to determine the state type of a single insulator.

[0100] In this implementation, the insulator leakage current is decomposed into two core components: surface leakage current and internal leakage current. This reduces the interference of external factors such as surface contamination on the assessment of internal insulation degradation. The condition determination criteria are based on experimental data, making the threshold standard scientifically grounded, reducing the subjectivity of empirical judgments, and improving the consistency and accuracy of condition classification. By adopting dual-threshold collaborative analysis of surface and internal leakage current, different insulator condition types can be more comprehensively distinguished, effectively reducing the probability of missed or false judgments, and providing accurate and reliable single-base condition data support for subsequent multi-base collaborative assessment across the entire line.

[0101] Figure 4 This is a flowchart illustrating a method for assessing the insulation status of an entire line, provided in an embodiment of this disclosure. This method can be executed by a centralized analysis platform within the station, which can be implemented using software and / or hardware, and is generally integrated into a computing device. Figure 4 As shown, the method includes: S301. Divide the entire line of multi-base towers into multiple areas according to spatial dimensions.

[0102] S302. Count the number of poles for each type of early warning status in each area. When the number of poles exceeds the threshold, perform the corresponding regional multi-base early warning.

[0103] S303. Statistically analyze the variation range of the internal leakage current of the insulators of multi-base towers in each region. When the rate of increase of the internal leakage current of the insulator is greater than the rate of increase threshold and the duration is greater than the duration threshold, issue a corresponding regional multi-base severe fault warning.

[0104] S304. Scoring of single-base towers based on the condition type of single-base insulators.

[0105] S305. Assign weights to individual towers based on their importance.

[0106] S306. Based on the single-base tower score and weight, perform a weighted average of the single-base towers within the multi-base towers along the entire line to obtain the insulation status score of the multi-base towers along the entire line.

[0107] In this implementation, the entire line of towers is managed in a grid-like manner through spatial partitioning. The insulation degradation trend is captured by combining the current rise rate and duration dual thresholds to provide early warning of serious faults. At the same time, a weighted algorithm of single-base score and importance weight is used to output a quantitative score of insulation for the entire line that fits the actual operation and maintenance, which can accurately assess the overall condition of the line.

[0108] To implement the above embodiments, this disclosure also proposes a computer program product, including a computer program / instruction, which, when executed by a processor, implements the single-base state judgment method or the full-line insulation state assessment method in the above embodiments.

[0109] Figure 5 This is a schematic diagram of the structure of a computing device provided in an embodiment of the present disclosure.

[0110] The following is a detailed reference. Figure 5 The diagram illustrates a structural schematic suitable for implementing the computing device 500 in the embodiments of this disclosure. The computing device 500 in the embodiments of this disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The computing device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0111] like Figure 5 As shown, the computing device 500 may include a processor (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from memory 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the computing device 500. The processor 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0112] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows computing device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 A computing device 500 with various devices is shown; however, it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or included alternatively.

[0113] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a memory 508, or installed from a ROM 502. When the computer program is executed by the processor 501, it performs the functions defined in the single-base state determination method or the full-line insulation state assessment method of embodiments of this disclosure.

[0114] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0115] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0116] The aforementioned computer-readable medium may be included in the aforementioned computing device; or it may exist independently and not assembled into the computing device.

[0117] The aforementioned computer-readable medium carries one or more programs, which, when executed by the computing device, cause the computing device to perform the aforementioned single-base state judgment method or the overall insulation state assessment method.

[0118] The computing device can be programmed with computer program code in one or more programming languages ​​or a combination thereof to perform the operations of this disclosure. These programming languages ​​include, but are not limited to, object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0119] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0120] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0121] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0122] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0123] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0124] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0125] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A system for monitoring and evaluating leakage current of line insulators across multiple towers along a complete line, characterized in that, The system includes multiple tower monitoring nodes and an in-station centralized analysis platform. One tower monitoring node is deployed for each tower. Each tower monitoring node includes a data acquisition module, a data analysis module, and a communication module. The data acquisition module is used to collect the insulator leakage current of the insulators on the tower. The data analysis module is used to analyze the state type of a single insulator based on the insulator leakage current. The communication module is used to upload the insulator leakage current and the single-base insulator status type to the centralized analysis platform within the station. The centralized analysis platform within the station is used to receive the insulator leakage current and the single-base insulator condition type of each tower, and to perform insulation condition assessment on all towers along the entire line based on the insulator leakage current and the single-base insulator condition type.

2. The line insulator leakage current monitoring and evaluation system for multiple towers along the entire line according to claim 1, characterized in that, The insulators include suspension porcelain insulators and composite insulators. Therefore, the grounding terminal of the composite insulator is connected to the upper end of the suspension porcelain insulator, and the lower end of the suspension porcelain insulator is connected to the tower. The data acquisition module includes a surface leakage current sensor and a total leakage current sensor. The surface leakage current sensor is deployed on the composite insulator and is used to collect the surface leakage current of the insulator based on a trigger signal. The total leakage current sensor is deployed on the suspension porcelain insulator and is used to collect the total leakage current at the root of the insulator based on the trigger signal.

3. The line insulator leakage current monitoring and evaluation system for multiple towers along the entire line according to claim 2, characterized in that, The data analysis module includes a data calculation unit and a single-base state judgment unit, wherein, The data calculation unit is used to calculate the internal leakage current of the insulator of each tower based on the surface leakage current of the insulator and the total leakage current at the root of the insulator. The single-base state determination unit is used to analyze the surface leakage current and the internal leakage current of the insulator based on the state determination conditions to determine the state type of the single-base insulator.

4. The line insulator leakage current monitoring and evaluation system for multiple towers along the entire line according to claim 3, characterized in that, The single-base state judgment unit is used to determine the state judgment condition corresponding to each state type based on experimental data. The state judgment condition includes the surface leakage current threshold and the internal leakage current threshold. Based on the surface leakage current threshold and the internal leakage current threshold, the surface leakage current and the internal leakage current of the insulator are analyzed to determine the state type of a single-base insulator, including: When the surface leakage current of the insulator is less than or equal to the first surface leakage current threshold, and the internal leakage current of the insulator is less than or equal to the first internal leakage current of the insulator, the single-base insulator is judged to be in a normal state. When the surface leakage current of the insulator is greater than the first surface leakage current threshold, and the internal leakage current of the insulator is less than or equal to the internal leakage current of the first insulator, the single-base insulator is determined to be in a surface pollution warning state, and a single-base surface pollution warning is issued. When the internal leakage current of the insulator is greater than the internal leakage current of the first insulator and less than or equal to the internal leakage current of the second insulator, the single-base insulator is determined to be in an internal breakdown warning state, and a single-base internal breakdown warning is issued. When the surface leakage current of the insulator is greater than the second surface leakage current threshold, or the internal leakage current of the insulator is greater than the internal leakage current of the second insulator, the single-base insulator status is determined to be a severe fault warning state, and a single-base severe fault warning is issued; the second surface leakage current threshold is greater than the first surface leakage current threshold.

5. The line insulator leakage current monitoring and evaluation system for multiple towers along the entire line according to claim 2, characterized in that, The tower monitoring node also includes a local preprocessing module, wherein... The local preprocessing module is used to set the process noise covariance and the observation noise covariance; Kalman filtering is performed on the surface leakage current of the insulator and the total root leakage current of the insulator based on the process noise covariance and the observation noise covariance.

6. The line insulator leakage current monitoring and evaluation system for multiple towers along the entire line according to claim 5, characterized in that, Each of the tower monitoring nodes also includes an auxiliary power supply module, which converts light energy into electrical energy through photovoltaic modules and supplies power to the data acquisition module, data analysis module, communication module and local preprocessing module within the tower monitoring node.

7. The line insulator leakage current monitoring and evaluation system for multiple towers along the entire line according to claim 1, characterized in that, The system allocates a corresponding upload time window to each of the tower monitoring nodes according to a polling mechanism. The communication module is used to upload the insulator leakage current to the centralized analysis platform within the station in sequence according to the tower number within the upload time window.

8. The line insulator leakage current monitoring and evaluation system for multiple towers along the entire line according to claim 3, characterized in that, The centralized analysis platform within the station includes a data processing module, a multi-base correlation analysis module, and a full-line insulation condition assessment module. The data processing module is used to verify the leakage current of the insulator and the state type of the single-base insulator; The multi-base correlation analysis module is used to evaluate the insulation status of multi-base towers based on spatial and temporal dimensions, combined with the insulator leakage current and the single-base insulator state type. The overall insulation status assessment module is used to assess the insulation status of multi-base towers along the entire line by combining the status types of single-base insulators.

9. The line insulator leakage current monitoring and evaluation system for multiple towers along the entire line according to claim 8, characterized in that, The multi-base correlation analysis module is used to divide the entire line of multi-base towers into multiple regions according to spatial dimensions; The number of poles for each type of early warning status is counted in each region. When the number of poles exceeds the threshold, a multi-base early warning for the corresponding region is issued. The variation range of the internal leakage current of the insulators of multi-base towers in each region is statistically analyzed. When the rate of increase of the internal leakage current of the insulator is greater than the rate of increase threshold and the duration is greater than the duration threshold, a corresponding regional multi-base severe fault warning is issued.

10. The line insulator leakage current monitoring and evaluation system for multiple towers along the entire line according to claim 8, characterized in that, The overall insulation status assessment module is used to score single-base towers based on the status type of single-base insulators; wherein, the score of a tower in normal condition is greater than the score of a tower in surface pollution warning condition, the score of a tower in surface pollution warning condition is greater than the score of a tower in internal breakdown warning condition, and the score of a tower in internal breakdown warning condition is greater than the score of a tower in severe fault warning condition. The weights of individual towers are assigned based on their importance; the higher the importance, the greater the weight. Based on the individual tower scores and weights, a weighted average is performed on the individual towers within the multi-tower network along the entire line to obtain the insulation status score of the multi-tower network along the entire line.

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