A method and system for monitoring and filling blind spots of tower leakage current based on environmental self-adaptation

Abstract

The present application relates to the technical field of current monitoring, in particular to a tower leakage current monitoring and blind filling method and system based on environmental adaptation, which comprises device installation initialization, environmental parameter collection, leakage current collection and cloud analysis. On the one hand, the working state of the device is adjusted according to temperature change, which can significantly prolong the endurance time of the device under extreme climate conditions and ensure the uninterrupted operation of the core monitoring function. On the other hand, the warning threshold is dynamically corrected according to humidity change, which can effectively separate the surface leakage current caused by environmental humidity from the body leakage current caused by insulation fault, solve the problem of false alarm of leakage current monitoring in high humidity environment, improve the accuracy and reliability of the warning information, and make the alarm information received by the operation and maintenance personnel truly reflect the insulation state of the equipment rather than environmental interference.

Description

Technical Field

[0001] This invention relates to the field of current monitoring technology, and more specifically, to a method and system for monitoring and compensating for leakage current in towers based on environmental adaptation. Background Technology

[0002] In the operation of power systems, power poles and towers serve as key supporting structures for transmission lines, and their safe and stable operation directly affects the power supply reliability of the entire power grid. As the coverage of the power grid continues to expand, some power poles and towers are deployed in complex geographical environments such as mountainous areas, hilly areas, and remote suburbs. These areas often face problems such as inconvenient transportation and harsh climatic conditions (such as heavy rain, high humidity, fog, and strong electromagnetic interference).

[0003] During long-term operation, power poles are prone to abnormal leakage current due to factors such as line aging, insulator damage, surface contamination, and lightning strikes. Excessive leakage current can accelerate the corrosion of the pole's metal components, trigger insulator flashover, and in severe cases, even lead to pole grounding faults, line tripping, and large-scale power outages, causing huge losses to industrial production and residential life. It also increases the repair costs and safety risks for power operation and maintenance departments.

[0004] Currently, power operation and maintenance departments mainly rely on two methods to monitor tower leakage current: one is regular manual inspections, where maintenance personnel carry portable monitoring equipment to the site to collect data; the other is installing fixed monitoring devices on towers in some key areas. However, manual inspections suffer from limited coverage, long inspection cycles, and poor real-time performance, especially in severe weather or remote areas, where inspections are difficult to conduct on time and cannot detect abnormal leakage current in a timely manner. Existing fixed monitoring devices have "monitoring blind spots." On the one hand, installation costs limit their deployment on all towers; on the other hand, some devices are affected by environmental interference, resulting in low monitoring accuracy and a lack of intelligent analysis capabilities for leakage current data, making it difficult to provide early warnings of potential faults. Therefore, there is an urgent need for an environmentally adaptive tower leakage current monitoring blind spot filling method and system that can fill monitoring blind spots, adapt to complex environments, and possess high accuracy and intelligent early warning functions. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for monitoring and filling blind spots in tower leakage current based on environmental adaptation, so as to solve the problems of coverage blind spots, poor real-time performance, insufficient accuracy and low level of intelligence of traditional monitoring methods in remote mountainous areas and harsh weather conditions.

[0006] To address the aforementioned technical problems, one objective of this invention is to provide an environment-adaptive method for monitoring and compensating for tower leakage current, comprising the following steps: S1. Device Installation and Initialization: Fix the monitoring and blind spot compensation device on the target tower, adjust the non-contact leakage current acquisition module on the monitoring and blind spot compensation device so that its sensing surface faces the grounding conductor of the tower, and enter the ID, the corresponding tower number, and latitude and longitude location information on the operation interface of the cloud monitoring platform to complete the software initialization configuration. S2. Environmental parameter acquisition: Real-time acquisition of environmental parameters of the environment where the tower is located through environmental sensors, and dynamic adjustment of working status and leakage current warning threshold based on the environmental parameters; S3, Leakage Current Acquisition: The non-contact leakage current acquisition module acquires leakage current signals according to the set sampling interval, filters, amplifies and reduces noise on the acquired leakage current signals, outputs leakage current data, and compares the leakage current data with the warning threshold. If the leakage current exceeds the warning threshold, the abnormal data is uploaded to the cloud monitoring platform. S4. Cloud-based analysis: When abnormal data is received on the cloud monitoring platform, tiered early warning information is generated, triggering local audible and visual alarms. The information is then pushed to maintenance personnel via GIS map location. After maintenance personnel complete on-site fault handling based on the early warning information, the handling results are recorded on the cloud platform.

[0007] Preferably, the monitoring blind spot filling device is fixed to the target tower 2-3 meters above the ground by a stainless steel bracket, and is powered by a built-in lithium iron phosphate battery. A wireless communication module is used to connect the monitoring blind spot filling device to the cloud monitoring platform.

[0008] Preferably, the environmental sensor includes a temperature and humidity sensor and a barometric pressure sensor, and the environmental parameters include humidity, temperature and barometric pressure values.

[0009] Preferably, the environmental adaptive acquisition step, which dynamically adjusts the working state according to the environmental parameters, includes the following steps: It continuously receives real-time temperature data from an ambient temperature sensor. When the temperature is sampled three times consecutively below a preset low-temperature threshold, it outputs a low-temperature environment signal, triggering a low-temperature protection mode, including: Reduce the operating frequency of the embedded MCU and adjust the transmit power and wake-up cycle of the wireless communication module, where: Under low temperature warning signals, if the receiver signal strength (RSSI) is higher than -100dBm, the transmit power will be reduced to 14dBm; if the receiver signal strength (RSSI) is higher than -80dBm, the transmit power can be further reduced to 10dBm, and the wake-up period will be extended to 5 minutes.

[0010] Preferably, in the environmental adaptive acquisition step, dynamically adjusting the leakage current warning threshold based on the environmental parameters includes the following steps: When the ambient humidity is higher than the preset humidity threshold for three consecutive samplings, the tower is output as a high-humidity environment signal. Based on a pre-established humidity-leakage current correlation model, the current humidity is input to the model to calculate the theoretical value of the surface leakage current caused by humidity. The warning threshold is then dynamically raised from a first preset value to a second preset value greater than the first preset value to eliminate interference from surface leakage current caused by high humidity on fault diagnosis. Second preset value = First preset value + Theoretical value of surface leakage current + Safety margin.

[0011] Preferably, the non-contact leakage current acquisition module uses a Hall current sensor to acquire leakage current signals at sampling intervals of 30 seconds to 10 minutes. The non-contact leakage current acquisition module also includes a signal conditioning circuit, which is used to filter, amplify, and reduce noise in the raw leakage current signal acquired by the current sensor.

[0012] Preferably, the leakage current data is compared with the warning threshold. If the leakage current exceeds the warning threshold, the abnormal data is uploaded to the cloud monitoring platform, including the following steps: The leakage current data is continuously compared with the dynamically adjusted warning threshold. When the leakage current data exceeds the warning threshold, the abnormal data is marked as the highest priority. A special flag is set in the header of the data packet, the abnormal data is encapsulated into a data packet, and the wireless communication module is immediately woken up from the sleep state to send the data packet at the maximum transmission power. After the transmission is completed, it does not wait for the next timing cycle and immediately re-enters the sleep state.

[0013] Preferably, the graded early warning information includes yellow warnings and red alarms. When the abnormal data is within the warning threshold range of 5-15mA, a yellow warning is triggered. When the abnormal data is greater than the warning threshold of 15mA, a red alarm is triggered. The local audible and visual alarm includes an LED indicator alarm mode and a buzzer alarm mode. When a graded warning message is generated, both the LED indicator alarm mode and the buzzer alarm mode continue to operate until the leakage current drops below the normal threshold, or the alarm is manually reset. When multiple alarm signals exist, red alarms have higher priority than yellow warnings, and a red alarm triggering a yellow warning overrides a yellow warning.

[0014] Preferably, the GIS map positioning also includes marking the location of the abnormal tower on the electronic map with a visual icon, and displaying the tower's real-time data, historical trend curves, and historical handling records.

[0015] The second objective of this invention is to provide an environment-adaptive tower leakage current monitoring and blind spot compensation system, including any one of the above-described environment-adaptive tower leakage current monitoring and blind spot compensation methods, comprising a monitoring and blind spot compensation device, an environmental parameter acquisition unit, a leakage current acquisition unit, and a cloud analysis unit: The monitoring and blind spot compensation device is fixedly installed on the target tower. The monitoring and blind spot compensation device includes a non-contact leakage current acquisition module, and the sensing surface of the non-contact leakage current acquisition module faces the grounding conductor of the tower. The environmental parameter acquisition unit is used to collect environmental parameters of the environment where the tower is located in real time through environmental sensors, and dynamically adjust the working status and leakage current warning threshold according to the environmental parameters. The leakage current acquisition unit is used to control the non-contact leakage current acquisition module to acquire leakage current signals according to the set sampling interval, filter, amplify and reduce noise on the acquired leakage current signals, output leakage current data, and compare the leakage current data with the warning threshold. If the warning threshold is exceeded, the abnormal data is uploaded to the cloud monitoring platform. The cloud-based analysis unit is used to generate tiered early warning information when receiving abnormal data on the cloud-based monitoring platform, trigger local audible and visual alarms, and push the information to maintenance personnel via GIS map location. After the maintenance personnel complete on-site fault handling based on the early warning information, the handling results are recorded on the cloud platform.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: By collecting real-time parameters such as temperature, humidity, and air pressure of the environment in which the tower is located using environmental sensors, and dynamically adjusting the operating status and leakage current warning threshold based on these environmental parameters, the device can significantly extend its operating time under extreme weather conditions and ensure uninterrupted operation of core monitoring functions by adjusting the device's operating status according to temperature changes. On the other hand, by dynamically correcting the warning threshold according to humidity changes, the device can effectively separate the surface leakage current caused by environmental humidity from the leakage current of the main body caused by insulation faults. This solves the problem of false alarms in leakage current monitoring under high humidity conditions, improves the accuracy and reliability of warning information, and ensures that the alarm information received by maintenance personnel truly reflects the insulation status of the equipment rather than environmental interference. Furthermore, the non-contact acquisition method ensures the safety of on-site installation and operation maintenance, avoiding secondary faults that may be caused by traditional contact measurement; multi-level signal processing ensures that high-precision, low-noise leakage current data can still be obtained in environments with strong electromagnetic interference; and the mechanism of comparing abnormal data with dynamic early warning thresholds in real time and uploading them immediately greatly shortens the fault response time, enabling potential leakage current anomalies to be detected and reported in their early stages, filling the response blind spots caused by long inspection cycles or network delays in traditional monitoring methods, and realizing the transformation from periodic monitoring to event-driven real-time monitoring. Attached Figure Description

[0017] Figure 1 This is the overall flowchart of Example 1; Figure 2 This is a flowchart illustrating the principle of environmental parameter acquisition in Example 1. Detailed Implementation

[0018] 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.

[0019] Example 1 like Figure 1 As shown, one of the objectives of this invention is to provide an environment-adaptive method for monitoring and compensating for tower leakage current, comprising the following steps: S1. Device Installation and Initialization: Fix the monitoring and blind spot compensation device on the target tower, adjust the non-contact leakage current acquisition module on the monitoring and blind spot compensation device so that its sensing surface is facing the grounding wire of the tower to ensure the best coupling effect, and enter the ID, corresponding tower number, latitude and longitude location information on the operation interface of the cloud monitoring platform to complete the software initialization configuration, providing an accurate data foundation for subsequent GIS positioning, historical data retrieval, and fault tracing.

[0020] Specifically, the monitoring blind spot filling device is fixed to the target tower 2-3 meters above the ground by a stainless steel bracket. The 2-3 meter height range is the area where the electromagnetic field strength of the grounding down conductor is relatively stable and attenuated. This ensures that the sensor can obtain sufficient sensing signal strength while avoiding strong interference sources near the ground (such as surface stray currents and grounding grid edge effects). The monitoring blind spot filling device is powered by a built-in lithium iron phosphate battery, eliminating the need for external power grid supply. It uses a wireless communication module to connect the monitoring blind spot filling device to the cloud monitoring platform, specifically a LoRaWAN or 4G Cat.1 wireless communication module, which can maintain the connection between the monitoring blind spot filling device and the cloud monitoring platform even in weak network signal environments.

[0021] S2. Environmental Parameter Acquisition: The environmental parameters of the tower's environment are collected in real time by environmental sensors. The working status and leakage current warning threshold are dynamically adjusted according to the environmental parameters to eliminate the impact of environmental factors on the monitoring results and ensure the device's endurance in extreme environments.

[0022] like Figure 2 As shown, the environmental sensors include a temperature and humidity sensor and a barometric pressure sensor. The environmental parameters include humidity, temperature, and barometric pressure values, among which: The temperature and humidity sensor integrates a capacitive humidity sensing element and a bandgap temperature sensing element. The capacitive humidity sensing element is made of a polymer thin film dielectric, and its dielectric constant changes with the ambient humidity, causing a change in the sensor's capacitance value. The built-in analog-to-digital converter converts the capacitance change into a digital signal, and outputs the relative humidity value after calibration and compensation. The bandgap temperature sensing element utilizes the characteristic that the forward voltage drop of the PN junction changes with temperature (approximately -2mV / ℃), which is amplified by a precision amplifier and converted into a digital signal to output the temperature value. The barometric pressure sensor integrates a silicon-based piezoresistive bridge circuit. When the ambient air pressure changes, the silicon diaphragm undergoes micro-strain, which causes the resistance value of the piezoresistive bridge to change, and the output voltage changes accordingly. After amplification and analog-to-digital conversion, the output digital air pressure value (300-1100 hPa) is displayed.

[0023] Furthermore, due to the significant decrease in the ionic conductivity of the electrolyte in lithium iron phosphate batteries at low temperatures (for example, at -20℃, the conductivity is approximately 30%-40% of that at room temperature), the migration rate of lithium ions between the positive and negative electrodes decreases, leading to a sharp increase in the battery's internal resistance. Above -10℃, the increase in internal resistance and capacity decay in lithium iron phosphate batteries are relatively gradual; below -10℃, the internal resistance increases exponentially, the discharge plateau voltage decreases significantly, and the usable capacity drops sharply. Currently, the power consumption design margin of embedded MCUs and wireless communication modules at room temperature can cover the increase in internal resistance above -10℃. Below -10℃, without intervention, the battery output voltage may instantly drop below the device's operating voltage limit (3.3V), causing the device to restart or shut down. Therefore, the environmental adaptive acquisition step dynamically adjusts the operating state according to environmental parameters, including the following steps: It continuously receives real-time temperature data from an ambient temperature sensor. When the temperature value is below a preset low-temperature threshold (-10℃) for three consecutive samplings (i.e., within 30 seconds), it outputs a low-temperature environment signal. This facilitates adjustments based on low temperatures, and the three-consecutive-judgment mechanism avoids false triggering caused by single-sampling noise, thus triggering the low-temperature protection mode, including: Since the operating frequency and power consumption of embedded MCUs (such as the STM32L series) are approximately linearly related, the dynamic power consumption decreases proportionally when the frequency is reduced. Therefore, on the one hand, reducing the operating frequency of the embedded MCU, although leading to a longer execution time for data processing and threshold comparison, is still much shorter than the 1-minute sampling interval after frequency reduction, given that a single data processing cycle only requires a few milliseconds, and thus does not affect real-time performance. Additionally, the transmit power and wake-up cycle of the wireless communication module are adjusted, including: Under low temperature warning signals, if the receiver signal strength (RSSI) is higher than -100dBm, the transmission power will be reduced to 14dBm; if the receiver signal strength (RSSI) is higher than -80dBm, the transmission power can be further reduced to 10dBm. At normal temperature, the module operates at the maximum transmission power (e.g., 20dBm) to ensure communication reliability, and the wake-up cycle is extended to 5 minutes. At normal temperature, the module adopts a 1-minute wake-up cycle. Each wake-up lasts 2-3 seconds to complete data upload and then immediately goes into sleep mode. The extension of the wake-up cycle may increase the delay of regular data upload, but abnormal data is uploaded immediately through the priority reporting mechanism and is not affected by this adjustment. Therefore, in summary, the core monitoring functions of the device are maintained uninterrupted under extremely cold conditions.

[0024] Furthermore, the total leakage current in the tower grounding circuit consists of two parts: first, the body leakage current, which flows through the inside of the insulator and the metal components of the tower, reflecting the true degree of insulation degradation; and second, the surface leakage current, which flows along the surface of the insulator and the tower, mainly determined by the ambient humidity and unrelated to the insulation condition. However, when the humidity is above 85%, a continuous thin water film forms on the surface of the tower insulator and metal components, leading to a significant increase in surface leakage current. The surface leakage current enters the exponential growth region and can quickly climb to over 10mA. When the humidity is below 85%, the increase in surface leakage current is relatively gradual, usually not exceeding 3-4mA. Therefore, in the environmental adaptive acquisition step, the leakage current warning threshold is dynamically adjusted according to environmental parameters, including the following steps: When the ambient humidity is above the preset humidity threshold (85%) for three consecutive samplings, the tower is output as a high-humidity environment signal. Based on a pre-established humidity-leakage current correlation model, the current humidity is input to the model to calculate the theoretical value of the surface leakage current caused by humidity. The warning threshold is then dynamically raised from a first preset value to a second preset value greater than the first preset value to eliminate interference from surface leakage current caused by high humidity in fault diagnosis. The second preset value = the first preset value + the theoretical value of surface leakage current + safety margin (usually 1-2mA to prevent false negatives due to model errors). The ambient humidity is continuously monitored. As long as the humidity is still higher than 85%, the corrected threshold remains effective. Conversely, when the humidity is lower than 80% for three consecutive samplings (a hysteresis interval is set to avoid frequent switching of the threshold at the threshold point), the first preset value is maintained.

[0025] Specifically, the establishment of the humidity-leakage current correlation model includes the following steps: In a laboratory environment, using standard porcelain insulators (the same model as on-site), a simulated tower test platform is built through a temperature and humidity controlled environment chamber. The surface leakage current under different humidity conditions is accurately measured. At least 100 repeated measurements are performed for each humidity condition, and the experimental data are output. The experimental data are statistically analyzed to establish a functional relationship between humidity and the baseline value of surface leakage current. For towers in different regions and with different pollution levels, multiple sets of model fitting parameters (related to insulator type and surface pollution level) can be set. A humidity-leakage current correlation model is established based on the functional relationship. The humidity-leakage current correlation model is configured and distributed through the cloud.

[0026] Taking a typical rainy season scenario as an example: the measured total leakage current is 12.5mA, the current humidity is 92%, and the calculated theoretical value of the surface leakage current is 5.2mA. Therefore, the net leakage current is: 12.5mA - 5.2mA = 7.3mA. Before correction: compared with the first preset warning threshold (the default warning threshold is 5mA), the net leakage current is greater than the warning threshold, triggering a yellow warning (false alarm). However, after correction, compared with the second preset warning threshold (the warning threshold is 11.2mA), the net leakage current of 7.3mA is less than the warning threshold of 11.2mA, and is judged as normal fluctuation, without triggering a warning. Therefore, distinguishing between environmental and fault components in the total leakage current allows the monitoring data to truly reflect the insulation status, which is beneficial for the received warning information to truly reflect insulation faults rather than interference from environmental factors.

[0027] S3. Leakage Current Acquisition: The non-contact leakage current acquisition module acquires leakage current signals according to the set sampling interval, filters, amplifies and reduces noise on the acquired leakage current signals, outputs leakage current data, and compares the leakage current data with the warning threshold. If the leakage current exceeds the warning threshold, the abnormal data is uploaded to the cloud monitoring platform to fill the real-time response blind spot caused by network latency or data congestion in traditional devices.

[0028] The non-contact leakage current acquisition module uses a Hall current sensor to collect leakage current signals at sampling intervals ranging from 30 seconds to 10 minutes. The sampling interval can be remotely adjusted via a cloud platform. The specific principle of the Hall current sensor is as follows: According to Faraday's law of electromagnetic induction, when leakage current flows through the grounding conductor of a tower, a ring-shaped alternating magnetic field is generated around the conductor. The Hall sensor detects the magnetic induction intensity of this magnetic field and converts it into a voltage signal proportional to the current. On the one hand, there is no electrical connection between the sensor and the conductor, which avoids the influence of contact resistance on measurement accuracy and ensures operational safety. On the other hand, the magnetic circuit of the non-contact sensor is fixed, which improves stability and avoids the need to open and close the magnetic circuit of traditional clamp meters. After long-term use, oxidation of the magnetic circuit contact surface can lead to increased errors.

[0029] Specifically, the non-contact leakage current acquisition module also includes a signal conditioning circuit. The signal conditioning circuit is used to filter, amplify, and reduce noise in the raw leakage current signal acquired by the current sensor, including the following steps: A filter circuit employing a second-order Butterworth active low-pass filter is used to eliminate high-frequency electromagnetic interference. Amplification circuits using instrumentation amplifiers with a three-op-amp structure (such as AD620) enhance weak signals; The differential signal (positive and negative) output from the Hall sensor is obtained by subtracting the differential signal from the Hall sensor through a differential amplifier, thus suppressing environmental noise. Based on the above, the collected leakage current signal is converted from an analog signal to a digital signal by an analog-to-digital converter (ADC) after filtering, amplification and noise reduction. The leakage current data is output and data cleaning and optimization are performed before comparing the leakage current data with the monitoring threshold to eliminate occasional interference and random noise.

[0030] The leakage current data is compared with the warning threshold. If it exceeds the warning threshold, the abnormal data is uploaded to the cloud monitoring platform, including the following steps: The leakage current data is continuously compared with the dynamically adjusted warning threshold. When the leakage current data exceeds the warning threshold, the abnormal data is marked as the highest priority. A special flag is set in the header of the data packet, the abnormal data is encapsulated into a data packet, and the wireless communication module is immediately woken up from the sleep state to send the data packet with the maximum transmission power. After the transmission is completed, it does not wait for the next timing cycle and immediately re-enters the sleep state, which helps to shorten the fault response time from minutes to seconds.

[0031] S4. Cloud-based analysis: When abnormal data is received on the cloud monitoring platform, tiered early warning information is generated, triggering local audible and visual alarms. The information is then pushed to maintenance personnel via GIS map location. After maintenance personnel complete on-site fault handling based on the early warning information, the handling results are recorded on the cloud platform.

[0032] Specifically, the tiered early warning information includes yellow warnings and red alarms. When abnormal data is within the warning threshold range of 5-15mA, a yellow warning is triggered. When abnormal data is greater than the warning threshold of 15mA, a red alarm is triggered. The local audible and visual alarm includes an LED indicator alarm mode and a buzzer alarm mode. When a graded warning message is generated, both the LED indicator alarm mode and the buzzer alarm mode continue to operate until the leakage current drops below the normal threshold, or the alarm is manually reset (via remote command or local button). When multiple alarm signals exist, red alarms have higher priority than yellow warnings, and a red alarm triggering a yellow warning overrides a yellow warning.

[0033] Furthermore, GIS map positioning also includes marking the location of abnormal towers on electronic maps with visual icons, and displaying the tower's real-time data, historical trend curves, and historical handling records, which helps to fully understand the on-site situation and rationally allocate resources and tools.

[0034] The second objective of this invention is to provide an environment-adaptive tower leakage current monitoring and blind spot compensation system, applicable to any of the above-mentioned environment-adaptive tower leakage current monitoring and blind spot compensation methods, including a monitoring and blind spot compensation device, an environmental parameter acquisition unit, a leakage current acquisition unit, and a cloud analysis unit: The monitoring and blind spot compensation device is fixedly installed on the target tower. The monitoring and blind spot compensation device includes a non-contact leakage current acquisition module, and the sensing surface of the non-contact leakage current acquisition module faces the grounding conductor of the tower. The environmental parameter acquisition unit is used to collect environmental parameters of the environment where the tower is located in real time through environmental sensors, and dynamically adjust the working status and leakage current warning threshold according to the environmental parameters. The leakage current acquisition unit is used to control the non-contact leakage current acquisition module to acquire leakage current signals according to the set sampling interval, filter, amplify and reduce noise of the acquired leakage current signals, output leakage current data, and compare the leakage current data with the warning threshold. If the warning threshold is exceeded, the abnormal data is uploaded to the cloud monitoring platform. The cloud-based analytics unit generates tiered early warning information when it receives abnormal data on the cloud-based monitoring platform, triggers local audible and visual alarms, and pushes the information to maintenance personnel via GIS map location. After maintenance personnel complete on-site fault handling based on the early warning information, the handling results are recorded on the cloud platform.

[0035] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for monitoring and compensating for tower leakage current based on environmental adaptation, characterized in that, Includes the following steps: S1. Device Installation and Initialization: Fix the monitoring and blind spot compensation device on the target tower, adjust the non-contact leakage current acquisition module on the monitoring and blind spot compensation device so that its sensing surface faces the grounding conductor of the tower, and enter the ID, the corresponding tower number, and latitude and longitude location information on the operation interface of the cloud monitoring platform to complete the software initialization configuration. S2. Environmental parameter acquisition: Real-time acquisition of environmental parameters of the environment where the tower is located through environmental sensors, and dynamic adjustment of working status and leakage current warning threshold based on the environmental parameters; S3, Leakage Current Acquisition: The non-contact leakage current acquisition module acquires leakage current signals according to the set sampling interval, filters, amplifies and reduces noise on the acquired leakage current signals, outputs leakage current data, and compares the leakage current data with the warning threshold. If the leakage current exceeds the warning threshold, the abnormal data is uploaded to the cloud monitoring platform. S4. Cloud-based analysis: When abnormal data is received on the cloud monitoring platform, tiered early warning information is generated, triggering local audible and visual alarms. The information is then pushed to maintenance personnel via GIS map location. After maintenance personnel complete on-site fault handling based on the early warning information, the handling results are recorded on the cloud platform.

2. The method for monitoring and compensating for tower leakage current based on environmental adaptation according to claim 1, characterized in that: The monitoring and blind spot filling device is fixed to the target tower 2-3 meters above the ground by a stainless steel bracket, and is powered by a built-in lithium iron phosphate battery. A wireless communication module is used to connect the monitoring and blind spot filling device to the cloud monitoring platform.

3. The method for monitoring and compensating for tower leakage current based on environmental adaptation according to claim 1, characterized in that: The environmental sensors include a temperature and humidity sensor and a barometric pressure sensor, and the environmental parameters include humidity, temperature and barometric pressure values.

4. The method for monitoring and compensating for tower leakage current based on environmental adaptation according to claim 3, characterized in that: The environmental adaptive acquisition step involves dynamically adjusting the working state based on the environmental parameters, including the following steps: It continuously receives real-time temperature data from an ambient temperature sensor. When the temperature is sampled three times consecutively below a preset low-temperature threshold, it outputs a low-temperature environment signal, triggering a low-temperature protection mode, including: Reduce the operating frequency of the embedded MCU and adjust the transmit power and wake-up cycle of the wireless communication module, where: Under low temperature warning signals, if the receiving signal strength is higher than -100dBm, the transmitting power will be reduced to 14dBm; if the receiving signal strength RSSI is higher than -80dBm, the transmitting power can be further reduced to 10dBm, and the wake-up period will be extended to 5 minutes.

5. The method for monitoring and compensating for tower leakage current based on environmental adaptation according to claim 4, characterized in that: The environmental adaptive acquisition step involves dynamically adjusting the leakage current warning threshold based on the environmental parameters, including the following steps: When the ambient humidity is higher than the preset humidity threshold for three consecutive samplings, the tower is output as a high-humidity environment signal. Based on a pre-established humidity-leakage current correlation model, the current humidity is input to the model to calculate the theoretical value of the surface leakage current caused by humidity. The warning threshold is then dynamically raised from a first preset value to a second preset value greater than the first preset value to eliminate interference from surface leakage current caused by high humidity on fault diagnosis. Second preset value = First preset value + Theoretical value of surface leakage current + Safety margin.

6. The method for monitoring and compensating for tower leakage current based on environmental adaptation according to claim 5, characterized in that: The non-contact leakage current acquisition module uses a Hall current sensor to acquire leakage current signals at sampling intervals of 30 seconds to 10 minutes. The non-contact leakage current acquisition module also includes a signal conditioning circuit, which is used to filter, amplify, and reduce noise in the raw leakage current signal acquired by the current sensor.

7. The method for monitoring and compensating for tower leakage current based on environmental adaptation according to claim 6, characterized in that: The leakage current data is compared with the warning threshold. If it exceeds the warning threshold, the abnormal data is uploaded to the cloud monitoring platform, including the following steps: The leakage current data is continuously compared with the dynamically adjusted warning threshold. When the leakage current data exceeds the warning threshold, the abnormal data is marked as the highest priority. A special flag is set in the header of the data packet, the abnormal data is encapsulated into a data packet, and the wireless communication module is immediately woken up from the sleep state to send the data packet at the maximum transmission power. After the transmission is completed, it does not wait for the next timing cycle and immediately re-enters the sleep state.

8. The method for monitoring and compensating for tower leakage current based on environmental adaptation according to claim 7, characterized in that: The tiered early warning information includes yellow warnings and red alarms. When abnormal data is within the warning threshold range of 5-15mA, a yellow warning is triggered. When abnormal data is greater than the warning threshold of 15mA, a red alarm is triggered. The local audible and visual alarm includes an LED indicator alarm mode and a buzzer alarm mode. When a graded warning message is generated, both the LED indicator alarm mode and the buzzer alarm mode continue to operate until the leakage current drops below the normal threshold, or the alarm is manually reset. When multiple alarm signals exist, red alarms have higher priority than yellow warnings, and a red alarm triggering a yellow warning overrides a yellow warning.

9. The method for monitoring and compensating for tower leakage current based on environmental adaptation according to claim 8, characterized in that: The GIS map positioning also includes marking the location of abnormal towers on the electronic map with visual icons, and displaying the tower's real-time data, historical trend curves, and historical handling records.

10. An environment-adaptive tower leakage current monitoring and blind spot compensation system, applied to the environment-adaptive tower leakage current monitoring and blind spot compensation method according to any one of claims 1-9, characterized in that, It includes a monitoring and blind spot compensation device, an environmental parameter acquisition unit, a leakage current acquisition unit, and a cloud analysis unit: The monitoring and blind spot compensation device is fixedly installed on the target tower. The monitoring and blind spot compensation device includes a non-contact leakage current acquisition module, and the sensing surface of the non-contact leakage current acquisition module faces the grounding conductor of the tower. The environmental parameter acquisition unit is used to collect environmental parameters of the environment where the tower is located in real time through environmental sensors, and dynamically adjust the working status and leakage current warning threshold according to the environmental parameters. The leakage current acquisition unit is used to control the non-contact leakage current acquisition module to acquire leakage current signals according to the set sampling interval, filter, amplify and reduce noise on the acquired leakage current signals, output leakage current data, and compare the leakage current data with the warning threshold. If the warning threshold is exceeded, the abnormal data is uploaded to the cloud monitoring platform. The cloud-based analysis unit is used to generate tiered early warning information when receiving abnormal data on the cloud-based monitoring platform, trigger local audible and visual alarms, and push the information to maintenance personnel via GIS map location. After the maintenance personnel complete on-site fault handling based on the early warning information, the handling results are recorded on the cloud platform.

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