Electric leakage monitoring method and system and intelligent electric leakage protection circuit breaker

Abstract

The invention discloses an electric leakage monitoring method and system and an intelligent electric leakage protection circuit breaker, and relates to the technical field of power grid monitoring, the electric leakage monitoring system and the intelligent electric leakage protection circuit breaker are used for realizing the method, and the method comprises a signal acquisition step and a signal analysis step. The signal analysis step comprises the following steps of: classifying the electric leakage type into direct-current electric leakage or alternating-current electric leakage; if it is judged that direct current type electric leakage exists, time domain waveform features in the residual current signals are extracted; if the electric leakage is judged to be alternating current electric leakage, time domain waveform feature extraction and frequency domain harmonic feature analysis are carried out; judging an electric leakage type; and executing the corresponding earth leakage protection action strategy, and encapsulating and uploading the data frame. According to the scheme, electric leakage protection maloperation and operation refusal can be avoided by identifying the electric leakage type, and for the characteristics of a rural power grid, the problem that a monitoring device is difficult to realize on low-cost hardware due to large computing power overhead can be solved in an electric leakage protection distributed deployment scene.

Description

Technical Field

[0001] This invention relates to the field of power grid monitoring technology, and in particular to a leakage current monitoring method, system, and intelligent leakage current protection circuit breaker. Background Technology

[0002] In low-voltage distribution networks such as 220V / 380V TT systems, compared to TN systems, the equipment casing is grounded. The residual current protection (RCD) function of intelligent circuit breakers is crucial for ensuring electrical safety, achieving leakage protection based on the residual current amplitude within a set threshold. However, due to the inherent characteristics of rural power grids (large distributed capacitance, dispersed loads, non-standard grounding methods, easily aging insulation, and the tendency for non-standard electrical practices due to unauthorized wiring), the core problems commonly found in currently used intelligent circuit breakers include: 1. Frequent false tripping and failure to trip due to leakage protection: Most existing circuit breakers only determine whether to trip based on the residual current amplitude. Failure to trip can lead to abnormal leakage current, failure to trip when the residual current amplitude has not reached the set threshold, resulting in accidents such as electric shock, and causing cascading tripping, leading to power outages in the entire distribution area. False tripping (unnecessary tripping) will reduce the continuity of power supply and affect users' normal power use.

[0003] 2. Low efficiency in troubleshooting leakage current faults: Even if the leakage protection device (RCD) operates accurately, the existing equipment can only provide feedback on the leakage trip, and cannot inform or prompt the maintenance personnel about the specific type of leakage current (such as electric shock to personnel, motor aging, line capacitor leakage, etc.). The maintenance personnel need to carry professional instruments to check point by point on-site, which is time-consuming and labor-intensive. In particular, the rural power grid lines are scattered and have a large span, which further increases the difficulty of troubleshooting and prolongs the fault recovery time.

[0004] Meanwhile, in the existing technology, the technical solution provided in patent application number CN202510326043.7 (a photovoltaic power generation cabinet with leakage protection function and its working method) applies a dynamic benchmark model of leakage current (including leakage waveform monitoring and harmonic analysis) to leakage risk assessment. By constructing a dynamic benchmark model of leakage current based on environmental parameters, and by using time-frequency domain joint analysis and multi-dimensional feature vector extraction, it can accurately assess leakage risk in real time during photovoltaic system operation, and automatically execute differentiated protection strategies based on risk scores, thereby improving detection accuracy; in patent application number CN201710797777.9 ( The technical solution provided by the "Automatic Residual Current Waveform Identification Method Based on Sparse Representation" discloses a method for identifying leakage faults using sparse representation theory; the technical solution provided by patent application number CN202110341890.2 (a protection device based on residual current characteristic analysis) discloses a method for classifying leakage types using machine learning algorithms; and the prior art of patent application number CN201880091048.4, entitled "A Leakage Circuit Breaker," provides a technical solution that includes detecting leakage current of both AC and DC pulse components.

[0005] Further optimizing the technology applied to rural power grid leakage monitoring is undoubtedly of great significance to promoting the development of smart grids. Summary of the Invention

[0006] To address the aforementioned issues in optimizing leakage current monitoring technology for rural power grids, this invention provides a leakage current monitoring method, system, and intelligent leakage current protection circuit breaker. The technical solution provided by this invention not only avoids false tripping or failure to trip of leakage current protection by identifying the type of leakage current, but also, considering the characteristics of rural power grids—wide distribution areas and relatively dispersed power consumption locations—in the scenario of distributed deployment of leakage current protection, this solution can solve the problem that existing monitoring devices are difficult to implement on low-cost hardware due to high computing power overhead.

[0007] To address the above problems, the leakage current monitoring method, system, and intelligent leakage current protection circuit breaker provided by this invention solve the problems through the following technical points: The leakage current monitoring method includes a signal acquisition step and a signal analysis step. The signal acquisition step involves acquiring the residual current signal of the power grid through a signal acquisition device. The signal analysis step involves identifying the leakage current type and making a decision on the leakage current protection action based on the residual current signal. The signal analysis step includes the following steps: S1. Calculate the DC component in the residual current signal, compare the DC component with a preset threshold, and classify the leakage current type into DC leakage current or AC leakage current based on the comparison result. S2. Perform differentiated signal analysis based on the leakage current type classification results of step S1: If the leakage is determined to be DC type, the time-domain waveform features of the residual current signal are extracted. These time-domain waveform features include waveform shape features and amplitude features. If the leakage is determined to be AC, then the following analysis will be performed: Based on the residual current signal, time-domain waveform feature extraction and frequency-domain harmonic feature analysis are performed. The time-domain waveform feature extraction involves extracting the waveform morphology features, amplitude variation features, and amplitude threshold features of the residual current signal. The frequency-domain harmonic feature analysis involves performing a fast Fourier transform on the residual current signal to decompose it into the fundamental component and multiple harmonic components, and calculating the fundamental component ratio, total harmonic distortion rate, and characteristic harmonic ratio. S3. Leakage type matching and determination: Based on the preset leakage type feature comparison table, the signal analysis results of step S2 are compared with the leakage type feature comparison table, and the leakage type is determined according to the comparison results. S4. Action Strategy and Signal Encapsulation: Based on the leakage current type determination result, execute the corresponding leakage current protection action strategy, and encapsulate the leakage current type, analysis result characteristic parameters, and leakage current protection action execution status into a data frame and upload it.

[0008] This solution aims to address the following characteristics and problems of leakage current monitoring in rural power grids: On the one hand, rural power grids are characterized by a wide range of transformer areas and relatively dispersed power consumption locations, requiring large-scale leakage current monitoring and distributed protection deployment; on the other hand, existing technologies, such as sparse representation and machine learning, have high complexity and high hardware computing power requirements, resulting in high monitoring device costs and making it difficult to achieve low-cost, high-density distributed deployment in rural power grid scenarios.

[0009] This solution is based on the following technical principle: During the operation of rural power grids, it is not possible to effectively distinguish between real fault leakage current and false leakage current based solely on the residual current amplitude.

[0010] False leaks mainly fall into two categories: 1. Capacitive leakage current generated by line-to-ground capacitance: It is mainly composed of the fundamental component, the waveform is close to a sine wave, the harmonic content is low, and it exhibits pure capacitive characteristics. The current phase leads the voltage by about 90°, and its magnitude only changes slowly with environmental humidity, temperature and other factors, without abrupt changes. 2. High-frequency interference leakage from power electronic equipment such as frequency converters and switching power supplies: This type of leakage contains a large number of high-frequency harmonic components, exhibits significant waveform distortion, and is a non-standard sine wave. It differs significantly from capacitive leakage in terms of spectrum and waveform characteristics. Real-world fault leakage mainly includes: electric shock accidents (current flows through the human body to the ground; the human body acts as a non-linear resistor, causing waveform distortion and generating harmonic components), equipment insulation aging (resistive leakage, generating resistive current components, with phase in sync with the voltage, and waveform containing low-frequency harmonics), and arc leakage (the waveform exhibits drastic abrupt changes, high-frequency glitches, and abundant odd harmonics).

[0011] Based on the characteristics of the above signals and fault types, the residual current signals acquired in real time are analyzed using relevant analysis methods. Characteristic parameters such as fundamental frequency magnitude, harmonic content, waveform steepness, and phase angle are extracted. This allows for the following: When a large residual current amplitude is detected but its characteristics are mainly purely capacitive, it is determined to be background noise or environmental interference. In this case, to avoid affecting users' power consumption, it is advisable to suppress tripping and only record or issue a warning, thereby preventing circuit breaker malfunctions. When the residual current amplitude does not reach the threshold but the waveform characteristics highly match those of human electric shock or early arcing, the circuit breaker should trip immediately or in advance, thereby preventing circuit breaker failure to operate. At the same time, by constructing a leakage current type characteristic comparison table with a waveform characteristic library (such as high resistivity components and rich low-order harmonics corresponding to insulation aging and moisture, sudden waveform distortion corresponding to human electric shock, significant high-frequency harmonics and pulse groups corresponding to arcing faults, and pure sine waves with phase lead corresponding to distributed capacitance leakage), the accuracy of fault judgment can be greatly improved, the efficiency of troubleshooting can be increased, and the performance requirements of grid-end equipment or side equipment can be reduced.

[0012] The technical solution provided above differs from existing technologies in that, for the residual current signal, this solution introduces DC component detection at the beginning of signal analysis to classify the leakage signal into DC or AC leakage. Based on the classification results for different leakage types, a differentiated signal analysis method is executed in subsequent processes. Specifically: DC leakage only requires time-domain waveform feature extraction, without complex frequency-domain analysis (the essence of Fast Fourier Transform (FFT) is to decompose the signal into sinusoidal components of different frequencies, while the spectral characteristics of DC leakage signals contain only DC components or AC components with amplitudes much smaller than the DC components). Frequency analysis of pulsating DC signals does not yield effective information and wastes computational resources. Performing a unified FFT process, considering response speed, requires a high-performance CPU. Meanwhile, time-domain waveform characteristics are sufficient to determine DC leakage types: pulsating DC signals and pure DC signals can directly indicate rectifier equipment failure; amplitude can characterize the fault level related to leakage severity; amplitude change trends (stable / gradual / abrupt) can indicate the fault stage; and the included polarity characteristics can be used to determine single-tube breakdown in the rectifier bridge. AC leakage requires full-dimensional analysis in both the time and frequency domains.

[0013] This differentiated design not only ensures the accuracy of identifying various types of leakage current, but more importantly, it significantly reduces computing power overhead—DC leakage current skips FFT analysis, which can reduce the average computing load by about 15-20%, enabling the entire algorithm to run stably on low-cost MCUs, perfectly adapting to the stringent hardware cost requirements of rural power grid distributed deployment scenarios.

[0014] Meanwhile, this technical solution, through collaborative analysis in the time and frequency domains, can accurately distinguish between "false leakage / electrical interference" and "real fault leakage." Specifically, for AC leakage, time-domain waveform characteristics (waveform shape, amplitude variation, amplitude threshold) can be used to preliminarily determine the signal nature, while frequency-domain characteristics (fundamental frequency ratio, total harmonic distortion rate, characteristic harmonic ratio) provide specific quantitative basis. For example, when a large residual current amplitude is detected but the waveform is close to a pure sine wave and the harmonic content is low, it can be determined as a non-fault signal such as line distributed capacitance leakage, thereby suppressing tripping and avoiding false tripping. When a residual current amplitude is detected but the waveform suddenly distorts and the total harmonic distortion rate (THD) is high, the solution can be used to distinguish between "false leakage / electrical interference" and "real fault leakage." I When high levels of high and odd harmonics are abundant, it can be determined that there is a real fault such as electric shock to personnel, thus tripping the circuit breaker in advance and avoiding failure to operate.

[0015] It should be noted that the technical purpose of DC component detection and leakage current type classification in step S1 is to prioritize the identification of DC leakage currents for corresponding signal analysis methods, rather than completely excluding the analysis of AC leakage currents (the AC component of AC leakage current is superimposed on the DC waveform, specifically manifested as increased waveform ripple or waveform distortion; therefore, the time-domain waveform characteristics of DC leakage currents can detect large-amplitude AC leakage currents and sudden AC leakage currents (causing abrupt amplitude changes)). In a specific application, to avoid ignoring small-amplitude AC leakage currents accompanying DC leakage currents when the DC component exceeds a preset threshold (e.g., in transformer area leakage current monitoring, small AC leakage current signals are often overlooked by DC components), a specific application is used. In single-household or meter box bus leakage monitoring, due to short signal lines, less interference, and small current amplitudes, small-amplitude AC leakage is less likely to be ignored. Therefore, the system continuously monitors residual current signals in leakage monitoring of distribution areas. The leakage type classification in step S1 and the signal analysis in step S2 are executed alternately in adjacent analyses: if the residual current signal determination result of the current cycle is DC leakage, DC signal analysis is performed and the leakage type determination result is output. If AC leakage fault characteristics (such as amplitude abrupt change, waveform distortion) appear in the residual current signal of the next cycle, the system will re-determine the leakage type classification in the S1 classification of that cycle (at this time, the DC component may remain unchanged) and enter the AC leakage signal analysis path. The above alternate execution is intended to dynamically switch steps through residual current signal analysis, ensuring the efficiency of DC leakage processing while not missing AC leakage faults occurring simultaneously, based on the level of leakage monitoring location in the power grid.

[0016] It should be further clarified that the leakage current type classification in step S1 is only used to select the subsequent signal analysis path and is not the final tripping decision basis. The specific leakage current type (such as electric shock, insulation aging, rectifier equipment breakdown, etc.) determined by leakage current type feature matching in step S3 is the basis for the detailed leakage current type of the action strategy in step S4. For example, for DC leakage current, if it is determined to be a fault type such as rectifier equipment breakdown or DC bus leakage, then tripping protection will be performed; if it is determined to be a non-fault type such as normal EMI filter leakage of the switching power supply, then only a warning will be issued and recorded, without tripping. The same applies to AC leakage current. Therefore, as those skilled in the art, the differentiated analysis path design of this invention, while ensuring computing power efficiency, does not change the core safety logic of determining the protection action based on the leakage current type.

[0017] A further technical solution to the leakage current monitoring method is as follows: In the signal acquisition step, the number of sampling points of the signal acquisition device in one cycle is 2 to the power of N, where N is a positive integer; In the signal analysis step, the residual current signal used is the signal obtained by noise processing and mean filtering of the original signal acquired by the signal acquisition device. The preset threshold is a dynamic threshold, which is adaptively adjusted according to the operating status of the power grid and / or environmental parameters.

[0018] The above scheme proposes a technical solution to optimize signal acquisition and preprocessing of the original signal. Specifically, the number of sampling points is set to 2 to the power of N (e.g., 256 points / cycle, 512 points / cycle). In one specific implementation, considering the balance between computing power and data accuracy requirements, a sampling density of 2048 sampling points per cycle is adopted (a sampling density of 2048 sampling points / cycle can provide a sampling rate of approximately 24.4kHz at a 50Hz power frequency, which is sufficient to capture complete information of the 2nd to 21st harmonics and meet the accuracy requirements of rural power grid leakage monitoring). This sampling point setting allows direct use of the MCU's hardware multiplier for fast radix-2 FFT calculation, further reducing computing power consumption. Noise processing and mean filtering can remove random noise and spike interference, improving the accuracy of subsequent feature extraction. More specifically, a sliding window mean filtering (e.g., averaging 3-5 consecutive points) can effectively suppress high-frequency random noise and spike interference in the power grid without losing the main waveform features, providing a clean base signal for subsequent time-domain and frequency-domain analysis.

[0019] In this solution, the preset threshold is set as a dynamic threshold, adaptively adjusted based on grid operating status (such as load size) and environmental parameters (such as temperature, humidity, current date, and current time). This aims to address the poor adaptability of fixed thresholds in complex rural power grid environments. The preset threshold is used to determine whether the DC component exceeds the limit. For photovoltaic / energy storage devices that may exist in the rural power grid, the operating period of these devices is related to the current time. For example, during the daytime when photovoltaic power generation occurs, the inverter may generate background DC components. In this case, appropriately raising the threshold can avoid misjudging normal equipment operation as a DC leakage fault. At night, when photovoltaic power is off, the threshold is lowered to maintain sensitivity to DC faults. Seasonal switching of rectifier equipment: During the busy farming season, a large number of agricultural machines with rectifier circuits are used. When equipment (such as water pumps and threshers) is in use, the background DC component may increase. Dynamically raising the threshold can avoid misjudgment, and restoring the threshold to a low level during the off-season. DC load baseline changes in the distribution area: daily / weekly / seasonal baselines of the DC component in the leakage monitoring area are established based on historical data. The threshold is dynamically adjusted to adapt to long-term trends. For example, if the DC baseline in a distribution area permanently increases due to the addition of charging piles, the system can learn and adjust the threshold accordingly. The impact of ambient temperature on rectifier devices includes the potential increase in leakage current of semiconductor devices under high-temperature conditions, which can be addressed by appropriately raising the threshold and restoring it to a low-temperature environment. The aging trend of rectifier equipment includes the potential gradual increase in DC leakage current of long-term operating rectifier equipment. The threshold can be dynamically adjusted based on long-term trends in historical data to maintain sensitivity before the fault worsens.

[0020] The adaptive adjustment is implemented as follows: Collect historical leakage current data of the power grid within a preset time period; Based on the historical leakage current data, determine the reference current threshold under the current operating conditions; The reference current threshold is corrected based on the real-time operating status of the power grid to obtain a preset threshold.

[0021] The above provides a method for adaptive threshold adjustment based on historical power grid data. Specifically, the preset time period can be the past month, quarter, or year, etc. The reference current threshold can be obtained using statistical analysis methods. Specific implementation methods include, but are not limited to: dividing a day into multiple time periods, statistically analyzing the mean μ and standard deviation σ of the historical DC component for each time period, and the reference current threshold equal to μ + kσ (the value of k can be obtained by using the measured DC component as the calculation result within a fault-free reporting operation period within the leakage current monitoring range, and substituting it into μ and σ for extrapolation, as shown in 2-4); statistically analyzing historical data by month, season, and year to establish historical leakage current data curves; based on the development trend of these curves, for example, by analyzing the annual curve to identify the gradual upward trend of DC component caused by equipment aging, by analyzing the historical leakage current data curves to capture the periodic changes in busy / slack farming seasons and rainy / dry seasons, and by analyzing the monthly curves to reflect the load evolution characteristics in the middle and end of the busy farming season, the system can predict the expected range of DC component under the current operating conditions and determine the reference current threshold accordingly. Finally, the baseline threshold is dynamically corrected based on the real-time operating status of the power grid (such as current load, temperature, and humidity) to obtain the final preset threshold, thereby enabling the preset threshold to adaptively track equipment aging trends and seasonal changes.

[0022] The dynamic threshold is the selection result of a preset threshold selected from the threshold library: the threshold library has multiple preset thresholds corresponding to different leakage current levels, and each preset threshold is matched with selection basis parameters; The selection result is obtained based on one or more of the following selection parameters: current ambient temperature, current ambient humidity, and current load of the residual current signal acquisition line.

[0023] The above provides a dynamic threshold acquisition method that is easy to deploy on low-cost MCUs. Specifically, this technical solution provides another adaptive adjustment implementation method based on a threshold library lookup table. In this solution, the system pre-builds a threshold library, which stores multiple preset thresholds corresponding to different leakage current levels. Each threshold is associated with specific selection criteria parameters (such as temperature range, humidity range, load range, time period range, etc.). In actual operation, the system collects the current ambient temperature, current ambient humidity, and current load of the residual current signal acquisition line in real time. It matches these real-time parameters with the selection criteria parameters in the threshold library, finds and selects the most suitable preset threshold as the current threshold used for DC component comparison in step S1. For example, when the temperature is 30-35℃, humidity >80%, and load >80%, a high leakage current level preset threshold (e.g., 12mA) is matched to the "high temperature, high humidity, heavy load" scenario to avoid misjudging background DC during peak photovoltaic power generation as a fault. When the temperature is <30℃, humidity <60%, and load <50%, a low leakage current level preset threshold (e.g., 5mA) is matched to the "low temperature, dry, light load" scenario to maintain sensitivity to early DC faults. The lookup-based dynamic adjustment provided by this solution requires no complex calculations; only simple condition matching is needed to complete the preset threshold selection. It has the advantages of fast response speed, extremely low computing power overhead, and ease of engineering implementation, and is particularly suitable for low-cost MCU platforms that are widely deployed in rural power grids and have limited resources.

[0024] In step S3, under the classification of leakage current types in DC leakage current, the time-domain waveform features in the leakage current type feature lookup table include pulsating DC waveform features and pure DC straight waveform features.

[0025] The above scheme further refines the feature comparison table for DC leakage in step S3, specifically, under the premise that step S1 determines it to be DC leakage, the leakage type feature comparison table used in step S3 sets two key time-domain waveform features for DC leakage: one is the pulsating DC waveform feature, which corresponds to leakage scenarios of equipment with half-wave rectification or full-wave rectification but poor filtering (such as primary breakdown of switching power supply, single tube damage of rectifier bridge, thyristor voltage regulation circuit failure, etc.), and its waveform is characterized by existing only in the positive or negative half-cycle and having a pulsating shape; the other is the pure DC straight waveform feature, which corresponds to DC leakage scenarios after rectification and smoothing filtering (such as leakage from inverter DC bus to ground, decreased insulation of photovoltaic array to ground, leakage from battery pack to ground, etc.), and its waveform is characterized by a basically constant amplitude and no zero crossing. In this solution, by distinguishing between these two characteristics, the system can further locate the specific faulty equipment type and fault mode based on the initial classification of DC leakage current. For example, pulsating DC characteristics often point to damage to the rectifier device itself, while pure DC characteristics often point to insulation problems on the DC bus or DC load side. This provides maintenance personnel with more accurate fault location guidance, narrowing the scope of investigation from "existence of DC leakage current" to such as "rectifier circuit failure" or "DC bus insulation degradation", significantly improving the efficiency of troubleshooting DC leakage current faults.

[0026] In step S3, under the classification of leakage current types in AC leakage current, the waveform morphology features in the leakage current type feature lookup table include standard pure sine wave features, slightly distorted sine wave features, severely distorted sine wave features, and pulsed waveform features. The amplitude variation characteristics in the leakage current type characteristic comparison table include stable amplitude characteristics, gradual increase characteristics, steep increase and sudden change characteristics, instantaneous fluctuation characteristics, and intermittent occurrence characteristics; In step S2, the amplitude threshold feature is the comparison result with the preset amplitude threshold.

[0027] The above scheme provides a multi-dimensional feature comparison table for AC leakage in the matching and judgment step S3. Specifically, under the classification of AC leakage, the leakage type feature comparison table includes three dimensions of feature parameters: waveform morphology features are divided into standard pure sine wave features (corresponding to non-fault signals such as line distributed capacitance leakage), slightly distorted sine wave features (corresponding to motor start-stop interference or early insulation aging), severely distorted sine wave features (corresponding to frequency converter high-frequency interference or severe insulation aging), and pulse waveform features (corresponding to intermittent arc faults); amplitude change features are divided into stable amplitude features (corresponding to steady-state leakage), gradually increasing features (corresponding to insulation aging and deterioration process), steep increase and sudden change features (corresponding to sudden faults such as electric shock), instantaneous fluctuation features (corresponding to external impact interference), and intermittent occurrence features (corresponding to arc faults); amplitude threshold features are the comparison result of the effective value of the residual current extracted in step S2 and the preset amplitude threshold (such as 30mA) (i.e., "exceeding the limit" or "not exceeding the limit").

[0028] In this solution, through the above multi-dimensional leakage current type feature comparison table, the system can accurately identify various real faults and false interferences in AC leakage current. For example, when the waveform is a "standard pure sine wave", the amplitude change is a "stable amplitude", and the amplitude threshold is "exceeding the limit", it can be determined as a non-fault signal of line distributed capacitance leakage, thereby triggering software shielding to avoid false tripping. When the waveform is a "sudden distortion", the amplitude change is a "sharp increase and sudden change", and the amplitude threshold may be "not exceeding the limit" but has rich harmonic characteristics, it can be determined as a high-risk fault of electric shock, thereby triggering a 0.03s instantaneous trip to avoid failure to trip. The multi-dimensional feature collaborative judgment mechanism provided by this solution fundamentally solves the problem of false tripping and failure to trip caused by traditional leakage protection relying solely on amplitude judgment.

[0029] In step S2, the Fast Fourier Transform uses a Hanning window for windowing to suppress spectral leakage and employs a radix-2 FFT algorithm. The total harmonic distortion (THD) I Through the formula: Calculate, where I1 is the effective value of the fundamental current, I n This represents the effective value of the nth harmonic current. The characteristic harmonic proportions include the amplitude proportions of the 3rd, 5th, and 7th harmonics.

[0030] The above scheme provides a specific implementation method for frequency domain harmonic characteristic analysis. In this scheme, the Fast Fourier Transform (FFT) in step S2 uses a Hanning window for windowing processing, aiming to suppress the spectral leakage caused by frequency fluctuations in rural power grid environments. Frequent changes in rural power grid load may cause small fluctuations in the power frequency. If not processed by a window function, the fundamental frequency energy will leak to adjacent frequency points, forming false harmonic interference. The Hanning window, as a raised cosine window, has a moderate main lobe width and fast side lobe attenuation, which can effectively suppress such leakage and ensure the accuracy of harmonic analysis. The radix-2 FFT algorithm is used, which is directly adapted to the design with 2 to the power of N sampling points. It can call the MCU hardware multiplier to achieve fast calculation, significantly reducing computing power consumption. The total harmonic distortion (THD) is... I The calculation method is used to quantify the overall severity of waveform distortion. This technical solution adopts the characteristic harmonic proportion, including the amplitude proportion of the 3rd, 5th, and 7th harmonics, aiming to address the following issues: First, the 3rd harmonic is a zero-sequence harmonic, mainly generated by single-phase nonlinear loads (such as energy-saving lamps, LED power supplies, and switching power supplies) in rural power grids. The three-phase 3rd zero-sequence harmonics are superimposed in phase on the neutral line, which is one of the main causes of excessive neutral line current, neutral line overload and heating, and even electrical fires. At the same time, the dominance of the 3rd harmonic is also an important indicator of three-phase imbalance or random grounding of the neutral line. Second, the 5th harmonic is a negative-sequence harmonic, and the 7th harmonic is a positive-sequence harmonic. Both are typical characteristic harmonics of three-phase rectifier equipment, commonly found in power electronic devices such as frequency converters, photovoltaic inverters, and charging piles. When the content of the 5th and 7th harmonics is abnormally high, it is often related to aging of rectifier devices, abnormal triggering, abnormal operation of inverters, or DC bus / The leakage of the circuit can be used as a basis for judging leakage faults and device abnormalities. This solution can achieve fine differentiation of fault types in the frequency domain by extracting the amplitude ratio of the three characteristic harmonics (3rd, 5th and 7th). The 3rd harmonic dominates and points to faults related to single-phase rectifier loads or neutral wire problems, while the 5th and 7th harmonics dominate and point to faults related to three-phase rectifier equipment. This provides key frequency domain basis for the leakage type matching and judgment in step S3, and significantly improves the identification accuracy of typical fault sources in rural power grids.

[0031] The leakage current protection action strategy in step S4 includes: for non-fault leakage current determination results, executing leakage current protection action to trigger shielding; For the fault-type leakage current determination results, the leakage current protection action is triggered according to the risk level, specifically tripping. When it is determined to be a personnel electric shock leakage current type, the tripping time is ≤0.03s, and when it is determined to be an intermittent leakage current fault type, the tripping time is ≤0.2s. The data frame is in JSON format and includes a timestamp, device ID, leakage current type determination result, residual current RMS value, and total harmonic distortion (THD). I Field.

[0032] The above solution provides a precise hierarchical protection strategy and data interaction mechanism based on leakage current type determination. Specifically, in the leakage current protection action strategy in step S4, the system performs differentiated processing based on the determination result in step S3: For non-fault leakage current determination results (such as line distributed capacitance leakage, motor start-stop interference, inverter high-frequency interference, normal EMI leakage of switching power supply, etc.), the system performs leakage current protection action trigger shielding, that is, only records the event log locally and informs the background by uploading data frames, but the leakage current protection hardware does not trip, thereby avoiding unnecessary power outages and ensuring power supply continuity; For fault leakage current type determination results, the system triggers tripping according to risk level, among which personnel electric shock leakage current type is given the highest priority, with tripping time ≤0.03s (meeting the national standard requirements for personal electric shock protection), and intermittent leakage current fault types (such as arc faults) adopt anti-jitter tripping strategy, with tripping time ≤0.2s, to avoid frequent tripping due to the intermittent characteristics of arc. In the data encapsulation and interaction strategy, the data frame adopts JSON format, which is a lightweight and easy-to-parse data exchange format that facilitates interfacing with various IoT platforms. The data frame includes at least a timestamp (recording the time of the event), device ID (uniquely identifying the device), leakage current type determination result (such as specific types like "personal electric shock" or "insulation aging"), residual current RMS value (reflecting the severity of leakage current), and total harmonic distortion (THD). I (Reflecting the degree of waveform distortion) Five core fields. This strategy allows maintenance personnel to directly obtain a complete fault diagnosis report containing multiple types of information through the backend. No blind on-site inspection is needed during subsequent processing, effectively improving fault diagnosis and handling efficiency. For example, receiving a report with "Device ID: NLB202405001, Leakage Type: Electric Shock, THD" I Upon receiving the information "28.5%", personnel can be immediately dispatched to the area covered by the equipment for confirmation and rescue, greatly shortening the investigation and rescue time.

[0033] This solution also relates to a leakage current monitoring system, which is used to implement the leakage current monitoring method described in any of the above embodiments, wherein the system includes: Signal acquisition equipment used to collect residual current signals; It has a built-in leakage current monitoring method as described in any of the above, and a control module for performing signal analysis; The communication module used to upload data frames to the operation and maintenance backend; An execution module used to disconnect the line by performing leakage protection actions according to trip commands; Power supply modules used to supply power to the various power-consuming modules of this system; Storage module used for local storage of data frames.

[0034] The above provides a hardware system for implementing the aforementioned leakage current monitoring method. This system includes six core modules: a signal acquisition device for acquiring residual current signals from the power grid, specifically a high-precision residual current transformer that converts the 0-100mA residual current into a 0-2V voltage signal and sends it to the control module; and a control module that incorporates the leakage current monitoring method described above, responsible for signal analysis, leakage current type determination, and action decision-making. In one specific implementation, as a low-cost hardware implementation, an ARM processor with a clock frequency ≤72MHz is used. The Cortex-M series MCU (such as STM32F103) is used for the communication module, which uploads the data frame packaged in step S4 to the operation and maintenance backend. In one specific implementation, a dual-mode design supporting 4G / 5G remote communication and RS485 local communication is adopted, which not only meets the needs of remote centralized monitoring but also facilitates on-site debugging and maintenance. The execution module includes a magnetic latching relay and its drive circuit, which is used to perform leakage protection action to disconnect the line according to the trip command issued by the control module. Its fast response characteristics can meet the requirement of 0.03s instantaneous trip. In one specific implementation, the power supply module adopts a wide voltage input switching power supply (85-265V AC) to provide stable power supply for each module of the system. In one specific implementation, the storage module uses a Flash chip ring to store historical data frames with a capacity of not less than 8MB, which can store not less than 10,000 historical records, facilitating fault tracing and statistical analysis.

[0035] The above solution provides a detection system with a complete closed loop, from signal acquisition, analysis and judgment, action execution to data reporting, and is suitable for large-scale distributed deployment in scenarios such as main switches, branch lines, and household terminals in rural power grid areas.

[0036] This solution also relates to an intelligent residual current circuit breaker, including the residual current monitoring system described above.

[0037] The above solution applies the aforementioned leakage current monitoring system to an intelligent leakage current protection circuit breaker, providing a directly installable intelligent leakage current protection circuit breaker. Specifically, this intelligent leakage current protection circuit breaker includes the leakage current monitoring system described above. In one implementation, all modules of the system are integrated into a standard DIN rail-mounted housing, with dimensions consistent with ordinary miniature circuit breakers (such as 2P / 4P standard modules). The installation interface is identical to that of conventional leakage protection circuit breakers, requiring no modification to existing distribution boxes or additional space. It allows for plug-and-play replacement, and status indicator lights (such as operation indicator lights, power indicator lights, and on / off indicator lights) are provided on the front of the circuit breaker. The circuit breaker features a status indicator light, an alarm indicator light, a trip status indicator light, and a manual test button, allowing on-site maintenance personnel to quickly understand the equipment status and perform functional self-tests. Standard wiring terminals are located on the back of the circuit breaker, supporting a typical top-in, bottom-out wiring configuration. More specifically, the circuit breaker supports two operating modes: local mode and remote mode. In local mode, even if communication is interrupted, the control module can still independently perform leakage current monitoring and trip protection, ensuring that basic safety functions are not affected by communication issues. In remote mode, the communication module interacts with the cloud-based maintenance platform in real time, receiving remote parameter configurations and firmware upgrades, and reporting real-time monitoring data.

[0038] The present invention has the following beneficial effects: The technical solution provided by this solution can not only avoid false tripping or failure to trip of leakage protection by identifying the type of leakage, but also, given the characteristics of rural power grids, such as wide distribution areas and relatively dispersed power consumption locations, this solution adopts a differentiated signal analysis strategy in the distributed deployment scenario of leakage protection. This can solve the problem that existing monitoring devices are difficult to implement on low-cost hardware due to high computing power overhead. Attached Figure Description

[0039] Figure 1 A flowchart of a specific embodiment of the leakage current monitoring method described in this solution; Figure 2 This is a schematic diagram of a specific embodiment of the leakage current monitoring system described in this solution. Detailed Implementation

[0040] The present invention will be further described in detail below with reference to the embodiments, but the present invention is not limited to the following embodiments: Example 1: like Figure 1 and Figure 2 As shown, the leakage current monitoring method includes a signal acquisition step and a signal analysis step. The signal acquisition step involves acquiring the residual current signal of the power grid through a signal acquisition device. The signal analysis step involves identifying the leakage current type and making a decision on the leakage current protection action based on the residual current signal. The signal analysis step includes the following steps: S1. Calculate the DC component in the residual current signal, compare the DC component with a preset threshold, and classify the leakage current type into DC leakage current or AC leakage current based on the comparison result. S2. Perform differentiated signal analysis based on the leakage current type classification results of step S1: If the leakage is determined to be DC type, the time-domain waveform features of the residual current signal are extracted. These time-domain waveform features include waveform shape features and amplitude features. If the leakage is determined to be AC, then the following analysis will be performed: Based on the residual current signal, time-domain waveform feature extraction and frequency-domain harmonic feature analysis are performed. The time-domain waveform feature extraction involves extracting the waveform morphology features, amplitude variation features, and amplitude threshold features of the residual current signal. The frequency-domain harmonic feature analysis involves performing a fast Fourier transform on the residual current signal to decompose it into the fundamental component and multiple harmonic components, and calculating the fundamental component ratio, total harmonic distortion rate, and characteristic harmonic ratio. S3. Leakage type matching and determination: Based on the preset leakage type feature comparison table, the signal analysis results of step S2 are compared with the leakage type feature comparison table, and the leakage type is determined according to the comparison results. S4. Action Strategy and Signal Encapsulation: Based on the leakage current type determination result, execute the corresponding leakage current protection action strategy, and encapsulate the leakage current type, analysis result characteristic parameters, and leakage current protection action execution status into a data frame and upload it.

[0041] This solution aims to address the following characteristics and problems of leakage current monitoring in rural power grids: On the one hand, rural power grids are characterized by a wide range of transformer areas and relatively dispersed power consumption locations, requiring large-scale leakage current monitoring and distributed protection deployment; on the other hand, existing technologies, such as sparse representation and machine learning, have high complexity and high hardware computing power requirements, resulting in high monitoring device costs and making it difficult to achieve low-cost, high-density distributed deployment in rural power grid scenarios.

[0042] This solution is based on the following technical principle: During the operation of rural power grids, it is not possible to effectively distinguish between real fault leakage current and false leakage current based solely on the residual current amplitude.

[0043] False leaks mainly fall into two categories: 1. Capacitive leakage current generated by line-to-ground capacitance: It is mainly composed of the fundamental component, the waveform is close to a sine wave, the harmonic content is low, and it exhibits pure capacitive characteristics. The current phase leads the voltage by about 90°, and its magnitude only changes slowly with environmental humidity, temperature and other factors, without abrupt changes. 2. High-frequency interference leakage from power electronic equipment such as frequency converters and switching power supplies: This type of leakage contains a large number of high-frequency harmonic components, exhibits significant waveform distortion, and is a non-standard sine wave. It differs significantly from capacitive leakage in terms of spectrum and waveform characteristics. Real-world fault leakage mainly includes: electric shock accidents (current flows through the human body to the ground; the human body acts as a non-linear resistor, causing waveform distortion and generating harmonic components), equipment insulation aging (resistive leakage, generating resistive current components, with phase in sync with the voltage, and waveform containing low-frequency harmonics), and arc leakage (the waveform exhibits drastic abrupt changes, high-frequency glitches, and abundant odd harmonics).

[0044] Based on the characteristics of the above signals and fault types, the residual current signals acquired in real time are analyzed using relevant analysis methods. Characteristic parameters such as fundamental frequency magnitude, harmonic content, waveform steepness, and phase angle are extracted. This allows for the following: When a large residual current amplitude is detected but its characteristics are mainly purely capacitive, it is determined to be background noise or environmental interference. In this case, to avoid affecting users' power consumption, it is advisable to suppress tripping and only record or issue a warning, thereby preventing circuit breaker malfunctions. When the residual current amplitude does not reach the threshold but the waveform characteristics highly match those of human electric shock or early arcing, the circuit breaker should trip immediately or in advance, thereby preventing circuit breaker failure to operate. At the same time, by constructing a leakage current type characteristic comparison table with a waveform characteristic library (such as high resistivity components and rich low-order harmonics corresponding to insulation aging and moisture, sudden waveform distortion corresponding to human electric shock, significant high-frequency harmonics and pulse groups corresponding to arcing faults, and pure sine waves with phase lead corresponding to distributed capacitance leakage), the accuracy of fault judgment can be greatly improved, the efficiency of troubleshooting can be increased, and the performance requirements of grid-end equipment or side equipment can be reduced.

[0045] The technical solution provided above differs from existing technologies in that, for the residual current signal, this solution introduces DC component detection at the beginning of signal analysis to classify the leakage signal into DC or AC leakage. Based on the classification results for different leakage types, a differentiated signal analysis method is executed in subsequent processes. Specifically: DC leakage only requires time-domain waveform feature extraction, without complex frequency-domain analysis (the essence of Fast Fourier Transform (FFT) is to decompose the signal into sinusoidal components of different frequencies, while the spectral characteristics of DC leakage signals contain only DC components or AC components with amplitudes much smaller than the DC components). Frequency analysis of pulsating DC signals does not yield effective information and wastes computational resources. Performing a unified FFT process, considering response speed, requires a high-performance CPU. Meanwhile, time-domain waveform characteristics are sufficient to determine DC leakage types: pulsating DC signals and pure DC signals can directly indicate rectifier equipment failure; amplitude can characterize the fault level related to leakage severity; amplitude change trends (stable / gradual / abrupt) can indicate the fault stage; and the included polarity characteristics can be used to determine single-tube breakdown in the rectifier bridge. AC leakage requires full-dimensional analysis in both the time and frequency domains.

[0046] This differentiated design not only ensures the accuracy of identifying various types of leakage current, but more importantly, it significantly reduces computing power overhead—DC leakage current skips FFT analysis, which can reduce the average computing load by about 15-20%, enabling the entire algorithm to run stably on low-cost MCUs, perfectly adapting to the stringent hardware cost requirements of rural power grid distributed deployment scenarios.

[0047] Meanwhile, this technical solution, through collaborative analysis in the time and frequency domains, can accurately distinguish between "false leakage / electrical interference" and "real fault leakage." Specifically, for AC leakage, time-domain waveform characteristics (waveform shape, amplitude variation, amplitude threshold) can be used to preliminarily determine the signal nature, while frequency-domain characteristics (fundamental frequency ratio, total harmonic distortion rate, characteristic harmonic ratio) provide specific quantitative basis. For example, when a large residual current amplitude is detected but the waveform is close to a pure sine wave and the harmonic content is low, it can be determined as a non-fault signal such as line distributed capacitance leakage, thereby suppressing tripping and avoiding false tripping. When a residual current amplitude is detected but the waveform suddenly distorts and the total harmonic distortion rate (THD) is high, the solution can be used to distinguish between "false leakage / electrical interference" and "real fault leakage." I When high levels of high and odd harmonics are abundant, it can be determined that there is a real fault such as electric shock to personnel, thus tripping the circuit breaker in advance and avoiding failure to operate.

[0048] It should be noted that the technical purpose of DC component detection and leakage current type classification in step S1 is to prioritize the identification of DC leakage currents for corresponding signal analysis methods, rather than completely excluding the analysis of AC leakage currents (the AC component of AC leakage current is superimposed on the DC waveform, specifically manifested as increased waveform ripple or waveform distortion; therefore, the time-domain waveform characteristics of DC leakage currents can detect large-amplitude AC leakage currents and sudden AC leakage currents (causing abrupt amplitude changes)). In a specific application, to avoid ignoring small-amplitude AC leakage currents accompanying DC leakage currents when the DC component exceeds a preset threshold (e.g., in transformer area leakage current monitoring, small AC leakage current signals are often overlooked by DC components), a specific application is used. In single-household or meter box bus leakage monitoring, due to short signal lines, less interference, and small current amplitudes, small-amplitude AC leakage is less likely to be ignored. Therefore, the system continuously monitors residual current signals in leakage monitoring of distribution areas. The leakage type classification in step S1 and the signal analysis in step S2 are executed alternately in adjacent analyses: if the residual current signal determination result of the current cycle is DC leakage, DC signal analysis is performed and the leakage type determination result is output. If AC leakage fault characteristics (such as amplitude abrupt change, waveform distortion) appear in the residual current signal of the next cycle, the system will re-determine the leakage type classification in the S1 classification of that cycle (at this time, the DC component may remain unchanged) and enter the AC leakage signal analysis path. The above alternate execution is intended to dynamically switch steps through residual current signal analysis, ensuring the efficiency of DC leakage processing while not missing AC leakage faults occurring simultaneously, based on the level of leakage monitoring location in the power grid.

[0049] It should be further clarified that the leakage current type classification in step S1 is only used to select the subsequent signal analysis path and is not the final tripping decision basis. The specific leakage current type (such as electric shock, insulation aging, rectifier equipment breakdown, etc.) determined by leakage current type feature matching in step S3 is the basis for the detailed leakage current type of the action strategy in step S4. For example, for DC leakage current, if it is determined to be a fault type such as rectifier equipment breakdown or DC bus leakage, then tripping protection will be performed; if it is determined to be a non-fault type such as normal EMI filter leakage of the switching power supply, then only a warning will be issued and recorded, without tripping. The same applies to AC leakage current. Therefore, as those skilled in the art, the differentiated analysis path design of this invention, while ensuring computing power efficiency, does not change the core safety logic of determining the protection action based on the leakage current type.

[0050] Example 2: This embodiment is a further refinement of embodiment 1: In the signal acquisition step, the number of sampling points of the signal acquisition device in one cycle is 2 to the power of N, where N is a positive integer; In the signal analysis step, the residual current signal used is the signal obtained by noise processing and mean filtering of the original signal acquired by the signal acquisition device. The preset threshold is a dynamic threshold, which is adaptively adjusted according to the operating status of the power grid and / or environmental parameters.

[0051] The above scheme proposes a technical solution to optimize signal acquisition and preprocessing of the original signal. Specifically, the number of sampling points is set to 2 to the power of N (e.g., 256 points / cycle, 512 points / cycle). In one specific implementation, considering the balance between computing power and data accuracy requirements, a sampling density of 2048 sampling points per cycle is adopted (a sampling density of 2048 sampling points / cycle can provide a sampling rate of approximately 24.4kHz at a 50Hz power frequency, which is sufficient to capture complete information of the 2nd to 21st harmonics and meet the accuracy requirements of rural power grid leakage monitoring). This sampling point setting allows direct use of the MCU's hardware multiplier for fast radix-2 FFT calculation, further reducing computing power consumption. Noise processing and mean filtering can remove random noise and spike interference, improving the accuracy of subsequent feature extraction. More specifically, a sliding window mean filtering (e.g., averaging 3-5 consecutive points) can effectively suppress high-frequency random noise and spike interference in the power grid without losing the main waveform features, providing a clean base signal for subsequent time-domain and frequency-domain analysis.

[0052] In this solution, the preset threshold is set as a dynamic threshold, adaptively adjusted based on grid operating status (such as load size) and environmental parameters (such as temperature, humidity, current date, and current time). This aims to address the poor adaptability of fixed thresholds in complex rural power grid environments. The preset threshold is used to determine whether the DC component exceeds the limit. For photovoltaic / energy storage devices that may exist in the rural power grid, the operating period of these devices is related to the current time. For example, during the daytime when photovoltaic power generation occurs, the inverter may generate background DC components. In this case, appropriately raising the threshold can avoid misjudging normal equipment operation as a DC leakage fault. At night, when photovoltaic power is off, the threshold is lowered to maintain sensitivity to DC faults. Seasonal switching of rectifier equipment: During the busy farming season, a large number of agricultural machines with rectifier circuits are used. When equipment (such as water pumps and threshers) is in use, the background DC component may increase. Dynamically raising the threshold can avoid misjudgment, and restoring the threshold to a low level during the off-season. DC load baseline changes in the distribution area: daily / weekly / seasonal baselines of the DC component in the leakage monitoring area are established based on historical data. The threshold is dynamically adjusted to adapt to long-term trends. For example, if the DC baseline in a distribution area permanently increases due to the addition of charging piles, the system can learn and adjust the threshold accordingly. The impact of ambient temperature on rectifier devices includes the potential increase in leakage current of semiconductor devices under high-temperature conditions, which can be addressed by appropriately raising the threshold and restoring it to a low-temperature environment. The aging trend of rectifier equipment includes the potential gradual increase in DC leakage current of long-term operating rectifier equipment. The threshold can be dynamically adjusted based on long-term trends in historical data to maintain sensitivity before the fault worsens.

[0053] Example 3: This embodiment is a further refinement of embodiment 2: The adaptive adjustment is implemented as follows: Collect historical leakage current data of the power grid within a preset time period; Based on the historical leakage current data, determine the reference current threshold under the current operating conditions; The reference current threshold is corrected based on the real-time operating status of the power grid to obtain a preset threshold.

[0054] The above provides a method for adaptive threshold adjustment based on historical power grid data. Specifically, the preset time period can be the past month, quarter, or year, etc. The reference current threshold can be obtained using statistical analysis methods. Specific implementation methods include, but are not limited to: dividing a day into multiple time periods, statistically analyzing the mean μ and standard deviation σ of the historical DC component for each time period, and the reference current threshold equal to μ + kσ (the value of k can be obtained by using the measured DC component as the calculation result within a fault-free reporting operation period within the leakage current monitoring range, and substituting it into μ and σ for estimation, as shown in values ​​2 to 4); statistically analyzing historical data by month, season, and year to establish historical leakage current data curves; based on the development trend of these curves, for example, by analyzing the annual curve to identify the gradual upward trend of DC component caused by equipment aging, by analyzing the historical leakage current data curves to capture the periodic changes in busy / slack farming seasons and rainy / dry seasons, and by analyzing the monthly curves to reflect the load evolution characteristics in the middle and end of the busy farming season, the system can predict the expected range of DC component under the current operating conditions and determine the reference current threshold accordingly. Finally, the baseline threshold is dynamically corrected based on the real-time operating status of the power grid (such as current load, temperature, and humidity) to obtain the final preset threshold, thereby enabling the preset threshold to adaptively track equipment aging trends and seasonal changes.

[0055] Example 4: This embodiment is a further refinement of embodiment 2: The dynamic threshold is the selection result of a preset threshold selected from the threshold library: the threshold library has multiple preset thresholds corresponding to different leakage current levels, and each preset threshold is matched with selection basis parameters; The selection result is obtained based on one or more of the following selection parameters: current ambient temperature, current ambient humidity, and current load of the residual current signal acquisition line.

[0056] The above provides a dynamic threshold acquisition method that is easy to deploy on low-cost MCUs. Specifically, this technical solution provides another adaptive adjustment implementation method based on a threshold library lookup table. In this solution, the system pre-builds a threshold library, which stores multiple preset thresholds corresponding to different leakage current levels. Each threshold is associated with specific selection criteria parameters (such as temperature range, humidity range, load range, time period range, etc.). In actual operation, the system collects the current ambient temperature, current ambient humidity, and current load of the residual current signal acquisition line in real time. It matches these real-time parameters with the selection criteria parameters in the threshold library, finds and selects the most suitable preset threshold as the current threshold used for DC component comparison in step S1. For example, when the temperature is 30-35℃, humidity >80%, and load >80%, a high leakage current level preset threshold (e.g., 12mA) is matched to the "high temperature, high humidity, heavy load" scenario to avoid misjudging background DC during peak photovoltaic power generation as a fault. When the temperature is <30℃, humidity <60%, and load <50%, a low leakage current level preset threshold (e.g., 5mA) is matched to the "low temperature, dry, light load" scenario to maintain sensitivity to early DC faults. The lookup-based dynamic adjustment provided by this solution requires no complex calculations; only simple condition matching is needed to complete the preset threshold selection. It has the advantages of fast response speed, extremely low computing power overhead, and ease of engineering implementation, and is particularly suitable for low-cost MCU platforms that are widely deployed in rural power grids and have limited resources.

[0057] Example 5: This embodiment is a further refinement of embodiment 1: In step S3, under the classification of leakage current types in DC leakage current, the time-domain waveform features in the leakage current type feature lookup table include pulsating DC waveform features and pure DC straight waveform features.

[0058] The above scheme further refines the feature comparison table for DC leakage in step S3, specifically, under the premise that step S1 determines it to be DC leakage, the leakage type feature comparison table used in step S3 sets two key time-domain waveform features for DC leakage: one is the pulsating DC waveform feature, which corresponds to leakage scenarios of equipment with half-wave rectification or full-wave rectification but poor filtering (such as primary breakdown of switching power supply, single tube damage of rectifier bridge, thyristor voltage regulation circuit failure, etc.), and its waveform is characterized by existing only in the positive or negative half-cycle and having a pulsating shape; the other is the pure DC straight waveform feature, which corresponds to DC leakage scenarios after rectification and smoothing filtering (such as leakage from inverter DC bus to ground, decreased insulation of photovoltaic array to ground, leakage from battery pack to ground, etc.), and its waveform is characterized by a basically constant amplitude and no zero crossing. In this solution, by distinguishing between these two characteristics, the system can further locate the specific faulty equipment type and fault mode based on the initial classification of DC leakage current. For example, pulsating DC characteristics often point to damage to the rectifier device itself, while pure DC characteristics often point to insulation problems on the DC bus or DC load side. This provides maintenance personnel with more accurate fault location guidance, narrowing the scope of investigation from "existence of DC leakage current" to such as "rectifier circuit failure" or "DC bus insulation degradation", significantly improving the efficiency of troubleshooting DC leakage current faults.

[0059] Example 6: This embodiment is a further refinement of embodiment 1: In step S3, under the classification of leakage current types in AC leakage current, the waveform morphology features in the leakage current type feature lookup table include standard pure sine wave features, slightly distorted sine wave features, severely distorted sine wave features, and pulsed waveform features. The amplitude variation characteristics in the leakage current type characteristic comparison table include stable amplitude characteristics, gradual increase characteristics, steep increase and sudden change characteristics, instantaneous fluctuation characteristics, and intermittent occurrence characteristics; In step S2, the amplitude threshold feature is the comparison result with the preset amplitude threshold.

[0060] The above scheme provides a multi-dimensional feature comparison table for AC leakage in the matching and judgment step S3. Specifically, under the classification of AC leakage, the leakage type feature comparison table includes three dimensions of feature parameters: waveform morphology features are divided into standard pure sine wave features (corresponding to non-fault signals such as line distributed capacitance leakage), slightly distorted sine wave features (corresponding to motor start-stop interference or early insulation aging), severely distorted sine wave features (corresponding to frequency converter high-frequency interference or severe insulation aging), and pulse waveform features (corresponding to intermittent arc faults); amplitude change features are divided into stable amplitude features (corresponding to steady-state leakage), gradually increasing features (corresponding to insulation aging and deterioration process), steep increase and sudden change features (corresponding to sudden faults such as electric shock), instantaneous fluctuation features (corresponding to external impact interference), and intermittent occurrence features (corresponding to arc faults); amplitude threshold features are the comparison result of the effective value of the residual current extracted in step S2 and the preset amplitude threshold (such as 30mA) (i.e., "exceeding the limit" or "not exceeding the limit").

[0061] In this solution, through the above multi-dimensional leakage current type feature comparison table, the system can accurately identify various real faults and false interferences in AC leakage current. For example, when the waveform is a "standard pure sine wave", the amplitude change is a "stable amplitude", and the amplitude threshold is "exceeding the limit", it can be determined as a non-fault signal of line distributed capacitance leakage, thereby triggering software shielding to avoid false tripping. When the waveform is a "sudden distortion", the amplitude change is a "sharp increase and sudden change", and the amplitude threshold may be "not exceeding the limit" but has rich harmonic characteristics, it can be determined as a high-risk fault of electric shock, thereby triggering a 0.03s instantaneous trip to avoid failure to trip. The multi-dimensional feature collaborative judgment mechanism provided by this solution fundamentally solves the problem of false tripping and failure to trip caused by traditional leakage protection relying solely on amplitude judgment.

[0062] Example 7: This embodiment is a further refinement of embodiment 1: In step S2, the Fast Fourier Transform uses a Hanning window for windowing to suppress spectral leakage and employs a radix-2 FFT algorithm. The total harmonic distortion (THD) I Through the formula: Calculate, where I1 is the effective value of the fundamental current, I n This represents the effective value of the nth harmonic current. The characteristic harmonic proportions include the amplitude proportions of the 3rd, 5th, and 7th harmonics.

[0063] The above scheme provides a specific implementation method for frequency domain harmonic characteristic analysis. In this scheme, the Fast Fourier Transform (FFT) in step S2 uses a Hanning window for windowing processing, aiming to suppress the spectral leakage caused by frequency fluctuations in rural power grid environments. Frequent changes in rural power grid load may cause small fluctuations in the power frequency. If not processed by a window function, the fundamental frequency energy will leak to adjacent frequency points, forming false harmonic interference. The Hanning window, as a raised cosine window, has a moderate main lobe width and fast side lobe attenuation, which can effectively suppress such leakage and ensure the accuracy of harmonic analysis. The radix-2 FFT algorithm is used, which is directly adapted to the design with 2 to the power of N sampling points. It can call the MCU hardware multiplier to achieve fast calculation, significantly reducing computing power consumption. The total harmonic distortion (THD) is... I The calculation method is used to quantify the overall severity of waveform distortion. This technical solution adopts the characteristic harmonic proportion, including the amplitude proportion of the 3rd, 5th, and 7th harmonics, aiming to address the following issues: First, the 3rd harmonic is a zero-sequence harmonic, mainly generated by single-phase nonlinear loads (such as energy-saving lamps, LED power supplies, and switching power supplies) in rural power grids. The three-phase 3rd zero-sequence harmonics are superimposed in phase on the neutral line, which is one of the main causes of excessive neutral line current, neutral line overload and heating, and even electrical fires. At the same time, the dominance of the 3rd harmonic is also an important indicator of three-phase imbalance or random grounding of the neutral line. Second, the 5th harmonic is a negative-sequence harmonic, and the 7th harmonic is a positive-sequence harmonic. Both are typical characteristic harmonics of three-phase rectifier equipment, commonly found in power electronic devices such as frequency converters, photovoltaic inverters, and charging piles. When the content of the 5th and 7th harmonics is abnormally high, it is often related to aging of rectifier devices, abnormal triggering, abnormal operation of inverters, or DC bus / The leakage of the circuit can be used as a basis for judging leakage faults and device abnormalities. This solution can achieve fine differentiation of fault types in the frequency domain by extracting the amplitude ratio of the three characteristic harmonics (3rd, 5th and 7th). The 3rd harmonic dominates and points to faults related to single-phase rectifier loads or neutral wire problems, while the 5th and 7th harmonics dominate and point to faults related to three-phase rectifier equipment. This provides key frequency domain basis for the leakage type matching and judgment in step S3, and significantly improves the identification accuracy of typical fault sources in rural power grids.

[0064] Example 8: This embodiment is a further refinement of embodiment 1: The leakage current protection action strategy in step S4 includes: for non-fault leakage current determination results, executing leakage current protection action to trigger shielding; For the fault-type leakage current determination results, the leakage current protection action is triggered according to the risk level, specifically tripping. When it is determined to be a personnel electric shock leakage current type, the tripping time is ≤0.03s, and when it is determined to be an intermittent leakage current fault type, the tripping time is ≤0.2s. The data frame is in JSON format and includes a timestamp, device ID, leakage current type determination result, residual current RMS value, and total harmonic distortion (THD). I Field.

[0065] The above solution provides a precise hierarchical protection strategy and data interaction mechanism based on leakage current type determination. Specifically, in the leakage current protection action strategy in step S4, the system performs differentiated processing based on the determination result in step S3: For non-fault leakage current determination results (such as line distributed capacitance leakage, motor start-stop interference, inverter high-frequency interference, normal EMI leakage of switching power supply, etc.), the system performs leakage current protection action trigger shielding, that is, only records the event log locally and informs the background by uploading data frames, but the leakage current protection hardware does not trip, thereby avoiding unnecessary power outages and ensuring power supply continuity; For fault leakage current type determination results, the system triggers tripping according to risk level, among which personnel electric shock leakage current type is given the highest priority, with tripping time ≤0.03s (meeting the national standard requirements for personal electric shock protection), and intermittent leakage current fault types (such as arc faults) adopt anti-jitter tripping strategy, with tripping time ≤0.2s, to avoid frequent tripping due to the intermittent characteristics of arc. In the data encapsulation and interaction strategy, the data frame adopts JSON format, which is a lightweight and easy-to-parse data exchange format that facilitates interfacing with various IoT platforms. The data frame includes at least a timestamp (recording the time of the event), device ID (uniquely identifying the device), leakage current type determination result (such as specific types like "personal electric shock" or "insulation aging"), residual current RMS value (reflecting the severity of leakage current), and total harmonic distortion (THD). I With five core fields (reflecting the degree of waveform distortion), this strategy allows maintenance personnel to directly obtain a complete fault diagnosis report containing multiple types of information through the backend. This eliminates the need for blind on-site inspections during subsequent processing, effectively improving the efficiency of fault diagnosis and handling. For example, upon receiving information such as "Device ID: NLB202405001, Leakage Type: Electric Shock, THDI: 28.5%", personnel can be immediately organized to go to the area covered by the device for confirmation and rescue, greatly shortening the investigation and rescue time.

[0066] Example 9: This embodiment, based on Embodiment 1, provides a leakage current monitoring system. This system is used to implement the leakage current monitoring method described in Embodiment 1, wherein the system includes: Signal acquisition equipment used to collect residual current signals; It has a built-in leakage current monitoring method as described in any of the above, and a control module for performing signal analysis; The communication module used to upload data frames to the operation and maintenance backend; An execution module used to disconnect the line by performing leakage protection actions according to trip commands; Power supply modules used to supply power to the various power-consuming modules of this system; Storage module used for local storage of data frames.

[0067] The above provides a hardware system for implementing the aforementioned leakage current monitoring method. This system includes six core modules: a signal acquisition device for acquiring residual current signals from the power grid, specifically a high-precision residual current transformer that converts the 0-100mA residual current into a 0-2V voltage signal and sends it to the control module; and a control module that incorporates the leakage current monitoring method described above, responsible for signal analysis, leakage current type determination, and action decision-making. In one specific implementation, as a low-cost hardware implementation, an ARM processor with a clock frequency ≤72MHz is used. The Cortex-M series MCU (such as STM32F103) is used for the communication module, which uploads the data frame packaged in step S4 to the operation and maintenance backend. In one specific implementation, a dual-mode design supporting 4G / 5G remote communication and RS485 local communication is adopted, which not only meets the needs of remote centralized monitoring but also facilitates on-site debugging and maintenance. The execution module includes a magnetic latching relay and its drive circuit, which is used to perform leakage protection action to disconnect the line according to the trip command issued by the control module. Its fast response characteristics can meet the requirement of 0.03s instantaneous trip. In one specific implementation, the power supply module adopts a wide voltage input switching power supply (85-265V AC) to provide stable power supply for each module of the system. In one specific implementation, the storage module uses a Flash chip ring to store historical data frames with a capacity of not less than 8MB, which can store not less than 10,000 historical records, facilitating fault tracing and statistical analysis.

[0068] The above solution provides a detection system with a complete closed loop, from signal acquisition, analysis and judgment, action execution to data reporting, and is suitable for large-scale distributed deployment in scenarios such as main switches, branch lines, and household terminals in rural power grid areas.

[0069] Example 10: Based on Embodiment 1, this embodiment provides an intelligent leakage current protection circuit breaker, including the leakage current monitoring system described in Embodiment 1.

[0070] The above solution applies the aforementioned leakage current monitoring system to an intelligent leakage current protection circuit breaker, providing a directly installable intelligent leakage current protection circuit breaker. Specifically, this intelligent leakage current protection circuit breaker includes the leakage current monitoring system described above. In one implementation, all modules of the system are integrated into a standard DIN rail-mounted housing, with dimensions consistent with ordinary miniature circuit breakers (such as 2P / 4P standard modules). The installation interface is identical to that of conventional leakage protection circuit breakers, requiring no modification to existing distribution boxes or additional space. It allows for plug-and-play replacement, and status indicator lights (such as operation indicator lights, power indicator lights, and on / off indicator lights) are provided on the front of the circuit breaker. The circuit breaker features a status indicator light, an alarm indicator light, a trip status indicator light, and a manual test button, allowing on-site maintenance personnel to quickly understand the equipment status and perform functional self-tests. Standard wiring terminals are located on the back of the circuit breaker, supporting a typical top-in, bottom-out wiring configuration. More specifically, the circuit breaker supports two operating modes: local mode and remote mode. In local mode, even if communication is interrupted, the control module can still independently perform leakage current monitoring and trip protection, ensuring that basic safety functions are not affected by communication issues. In remote mode, the communication module interacts with the cloud-based maintenance platform in real time, receiving remote parameter configurations and firmware upgrades, and reporting real-time monitoring data.

[0071] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific embodiments of the present invention are limited to these descriptions. For those skilled in the art, other embodiments derived without departing from the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A leakage current monitoring method, comprising a signal acquisition step and a signal analysis step, wherein the signal acquisition step involves acquiring the residual current signal of the power grid through a signal acquisition device, and the signal analysis step involves identifying the leakage current type and making a decision on the execution of leakage current protection actions based on the residual current signal, characterized in that... The signal analysis step includes the following steps: S1. Calculate the DC component in the residual current signal, compare the DC component with a preset threshold, and classify the leakage current type into DC leakage current or AC leakage current based on the comparison result. S2. Perform differentiated signal analysis based on the leakage current type classification results of step S1: If the leakage is determined to be DC type, the time-domain waveform features of the residual current signal are extracted. These time-domain waveform features include waveform shape features and amplitude features. If the leakage is determined to be AC, then the following analysis will be performed: Based on the residual current signal, time-domain waveform feature extraction and frequency-domain harmonic feature analysis are performed. The time-domain waveform feature extraction involves extracting the waveform morphology features, amplitude variation features, and amplitude threshold features of the residual current signal. The frequency-domain harmonic feature analysis involves performing a fast Fourier transform on the residual current signal to decompose it into the fundamental component and multiple harmonic components, and calculating the fundamental component ratio, total harmonic distortion rate, and characteristic harmonic ratio. S3. Leakage type matching and determination: Based on the preset leakage type feature comparison table, the signal analysis results of step S2 are compared with the leakage type feature comparison table, and the leakage type is determined according to the comparison results. S4. Action Strategy and Signal Encapsulation: Based on the leakage current type determination result, execute the corresponding leakage current protection action strategy, and encapsulate the leakage current type, analysis result characteristic parameters, and leakage current protection action execution status into a data frame and upload it.

2. The leakage current monitoring method according to claim 1, characterized in that, In the signal acquisition step, the number of sampling points of the signal acquisition device in one cycle is 2 to the power of N, where N is a positive integer; In the signal analysis step, the residual current signal used is the signal obtained by noise processing and mean filtering of the original signal acquired by the signal acquisition device. The preset threshold is a dynamic threshold, which is adaptively adjusted according to the operating status of the power grid and / or environmental parameters.

3. The leakage current monitoring method according to claim 2, characterized in that, The adaptive adjustment is implemented as follows: Collect historical leakage current data of the power grid within a preset time period; Based on the historical leakage current data, determine the reference current threshold under the current operating conditions; The reference current threshold is corrected based on the real-time operating status of the power grid to obtain a preset threshold.

4. The leakage current monitoring method according to claim 2, characterized in that, The dynamic threshold is the selection result of a preset threshold selected from the threshold library: the threshold library has multiple preset thresholds corresponding to different leakage current levels, and each preset threshold is matched with selection basis parameters; The selection result is obtained based on one or more of the following selection parameters: current ambient temperature, current ambient humidity, and current load of the residual current signal acquisition line.

5. The leakage current monitoring method according to claim 1, characterized in that, In step S3, under the classification of leakage current types in DC leakage current, the time-domain waveform features in the leakage current type feature lookup table include pulsating DC waveform features and pure DC straight waveform features.

6. The leakage current monitoring method according to claim 1, characterized in that, In step S3, under the classification of leakage current types in AC leakage current, the waveform morphology characteristics in the leakage current type characteristic lookup table include standard pure sine wave characteristics, slightly distorted sine wave characteristics, severely distorted sine wave characteristics, and pulsed waveform characteristics. The amplitude variation characteristics in the leakage current type characteristic comparison table include stable amplitude characteristics, gradual increase characteristics, steep increase and sudden change characteristics, instantaneous fluctuation characteristics, and intermittent occurrence characteristics; In step S2, the amplitude threshold feature is the comparison result with the preset amplitude threshold.

7. The leakage current monitoring method according to claim 1, characterized in that, In step S2, the Fast Fourier Transform uses a Hanning window for windowing to suppress spectral leakage and employs a radix-2 FFT algorithm. The total harmonic distortion (THD) I Through the formula: Calculate, where I1 is the effective value of the fundamental current, I n This represents the effective value of the nth harmonic current. The characteristic harmonic proportions include the amplitude proportions of the 3rd, 5th, and 7th harmonics.

8. The leakage current monitoring method according to claim 1, characterized in that, The leakage current protection action strategy in step S4 includes: for non-fault leakage current determination results, executing leakage current protection action to trigger shielding; For the fault-type leakage current determination results, the tripping is triggered according to the risk level. Specifically, when the fault is determined to be a personnel electric shock leakage current type, the tripping time is ≤0.03s, and when the fault is determined to be an intermittent leakage current fault type, the tripping time is ≤0.2s. The data frame is in JSON format and includes a timestamp, device ID, leakage current type determination result, residual current RMS value, and total harmonic distortion (THD). I Field.

9. A leakage current monitoring system, characterized in that, This system is used to implement the leakage current monitoring method according to any one of claims 1 to 8, wherein the system comprises: Signal acquisition equipment used to collect residual current signals; The system incorporates the leakage current monitoring method according to any one of claims 1 to 8 and a control module for performing signal analysis. The communication module used to upload data frames to the operation and maintenance backend; An execution module used to disconnect the line by performing leakage protection actions according to trip commands; Power supply modules used to supply power to the various power-consuming modules of this system; Storage module used for local storage of data frames.

10. An intelligent residual current circuit breaker, characterized in that, Includes the leakage current monitoring system as described in claim 9.

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