Electric arc dynamic suppression method for hot plugging of electric meter connector

Abstract

The invention discloses an electric arc dynamic suppression method for hot plugging of an electric meter connector, relates to the technical field of electric energy metering equipment, and aims to solve the problems of electric arc generation, overproof metering error and the like caused by passive protection and lack of dynamic cooperative control in the prior art. The core of the method is that gap distance and power grid voltage phase signals are acquired in real time through a microcontroller, and the plugging speed, the signal injection and the position fine adjustment are dynamically regulated and controlled in three stages of pre-contact, low-current transition and full connection; and a machine learning model is combined to optimize a parameter threshold value, a redundancy safety mechanism and a multi-phase electric meter cooperative control strategy, so that double management and control of arc peak energy and metering errors are realized. The method can actively inhibit arc generation, avoid connector ablation and insulation deterioration, guarantee metering continuity and accuracy, adapt to complex power grid and environment working conditions, and meet the precision requirement of the intelligent electric meter.

Description

Technical Field

[0001] This invention relates to the field of electrical energy metering equipment technology, specifically to a method for dynamically suppressing arcing during live plugging and unplugging of electricity meter connectors. Background Technology

[0002] As the core equipment of modern power metering systems, the reliable connection of smart meters' connector interfaces and the stable transmission of electrical signals are crucial. During on-site operation and maintenance, to meet the needs of periodic verification and fault replacement, staff frequently need to perform live plugging and unplugging operations on smart meters in operation. However, during this process, the dynamically changing gap between the plug and socket can easily cause arcing, leading to electric arc discharge.

[0003] Currently, existing technical solutions to this problem have significant limitations. Most solutions focus on passive protection after the arc occurs, such as using arc-quenching materials with high dielectric strength or improving the composition of contact alloys to withstand and absorb arc energy. However, these methods cannot intervene at the critical stage of arc ignition, especially when the gap is within a critical range prone to arc ignition during insertion and removal, lacking effective active suppression measures. Another solution attempts to control the timing of insertion and removal by detecting the zero-crossing point of the grid voltage, but to achieve reliable disconnection, this often leads to excessively long power outage times, which violates the strict requirements for metering continuity in relevant smart meter technical standards, making it difficult to apply in engineering practice.

[0004] Furthermore, existing technologies generally neglect the dynamic coupling relationship between electrical parameters and mechanical states during hot-plugging. Commercially available connectors often employ a fixed-speed mechanical design, failing to respond in real-time to key parameters such as gap changes, nonlinear fluctuations in contact resistance, and grid phase. This lack of sensing and control capabilities not only directly leads to arcing but also causes instantaneous metering errors to exceed limits. Moreover, the reliability and stability of existing solutions significantly decrease when there is harmonic interference in the grid or changes in environmental conditions. For three-phase meters, existing technologies lack a coordinated control mechanism for phase-to-phase voltage differences and contact timing, potentially leading to the superposition of arc energy and further deterioration of metering accuracy.

[0005] Overall, existing technologies have a relatively singular perspective, focusing primarily on local improvements or post-incident remedies, failing to achieve real-time perception and multi-parameter collaborative optimization control of critical states throughout the entire insertion and removal process at the system level. Therefore, there is an urgent need in this field for an arc suppression method that can dynamically and intelligently and precisely control the insertion and removal process while ensuring metering continuity, in order to fundamentally improve operational safety and metering accuracy. Summary of the Invention

[0006] The purpose of this invention is to provide a method for dynamically suppressing arcing during live plugging and unplugging of meter connectors, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for dynamically suppressing arcing during live insertion and removal of an electricity meter connector, comprising the following phased control process: During the meter insertion and removal process, the microcontroller acquires the gap distance signal between the meter plug and the socket and the grid voltage phase signal in real time. When the gap distance is detected to be within the first preset threshold range, the pre-contact stage control is initiated: the insertion and removal speed is dynamically adjusted to the first preset low speed range, and a low-frequency test signal is injected into the plug terminal simultaneously. At the same time, the phase synchronization window of the signal injection is determined based on the grid voltage phase signal, and a microampere-level conduction path is established within the phase synchronization window. When the gap distance is detected to enter the second preset threshold range, low current transition phase control is initiated: the insertion and extraction speed is increased to the second preset speed range, the output current of the test signal is linearly increased, the resistance change rate of the contact interface is monitored in real time, and when the resistance change rate exceeds the first preset fluctuation threshold, the position fine-tuning mechanism is triggered, and the signal injection is terminated within the preset phase angle range before the end of the grid voltage half-cycle. When it is confirmed that the gap distance is completely closed and the contact resistance is stable within the preset safety threshold, the full connection stage control is started: the test signal is turned off, the insertion and extraction speed is increased to the third preset high speed range to complete the mechanical locking, and the metering system self-test process is executed to verify the arc suppression effect. The combination of parameters, including the first preset threshold range, the second preset threshold range, the first preset low-speed range, the second preset speed range, the first preset fluctuation threshold, and the preset phase angle range, limits the peak energy of the electric arc generated during insertion and removal to below the carbonization threshold of the insulating material, and controls the metering error within the accuracy level requirements of the smart meter.

[0008] Furthermore, in the pre-contact stage control, the first preset threshold range of the gap distance is greater than zero and less than or equal to the safety distance threshold corresponding to the initial insertion / removal speed. The safety distance threshold is dynamically set according to the power grid voltage level and the dielectric strength of the connector material. The lower limit of the first preset low-speed range is greater than zero and less than 50% of the initial insertion / removal speed, and the upper limit is determined according to the mechanical characteristics of the insertion / removal mechanism and the response delay time, so that when the insertion / removal speed is within the first preset low-speed range, the product of the gap distance change rate and the potential difference change rate is lower than the arc ignition critical value.

[0009] Furthermore, in the pre-contact stage control, the frequency range of the low-frequency test signal is 50Hz to 200Hz, and the width of its phase synchronization window is dynamically adjusted according to the grid frequency fluctuation tolerance. When the grid frequency fluctuation is detected to exceed the preset tolerance, the width of the phase synchronization window is expanded proportionally, while the amplitude of the test signal is reduced to maintain the stability of the conduction path. The dynamic adjustment mechanism of the phase synchronization window is negatively correlated with the grid frequency fluctuation tolerance, so that within the range of ±2Hz grid frequency fluctuation, the phase error between the signal injection time and the grid voltage zero crossing point is always controlled within the safe window.

[0010] Furthermore, in the low current transition stage control, the position fine-tuning mechanism includes: when the contact resistance change rate is detected to exceed a first preset fluctuation threshold, pausing the insertion / removal operation and driving the stepper motor to perform a micrometer-level reverse displacement; after the contact resistance returns to stability, the insertion / removal conditions are reassessed; the amplitude of the micrometer-level reverse displacement is dynamically set according to the resistance fluctuation amplitude; when the resistance fluctuation amplitude is in a first range, a first-level displacement is performed; when the resistance fluctuation amplitude is in a second range, a second-level displacement is performed; wherein the first-level displacement is less than the second-level displacement, and the amplitude of each displacement level is less than the mechanical clearance tolerance of the insertion / removal mechanism.

[0011] Furthermore, in the fully connected stage control, the self-test process of the metering system includes: injecting a feature verification signal into the metering chip, collecting signal response data and comparing it with a benchmark model; when the arc energy integral value is detected to exceed the safety threshold, an emergency backoff mechanism is triggered: controlling the stepper motor to drive the plug to move in the reverse direction to a safe distance, and simultaneously starting a fault diagnosis program to analyze the cause of the arc; the safe distance is dynamically set according to the current temperature rise status of the connector, and when the temperature rise exceeds the preset threshold, the safe distance range is expanded, so that secondary arcs can still be effectively avoided under the thermal aging conditions of the insulation material.

[0012] Furthermore, it also includes a redundant safety control mechanism that automatically switches to a backup monitoring mode when the main sensor signal fails. The backup monitoring mode determines the gap state based on the instantaneous rate of change of contact resistance. When the rate of change of resistance exceeds a second preset fluctuation threshold, it determines that there is a risk of arcing and initiates an emergency backoff. The second preset fluctuation threshold is dynamically calibrated according to the characteristics of the connector material and environmental parameters. Its calibration rules include: reducing the fluctuation threshold in high temperature and high humidity environments and increasing the fluctuation threshold in clean and dry environments, so that the effectiveness of arc suppression can still be maintained under sensor failure conditions.

[0013] Furthermore, the parameter thresholds of the three-stage control process are dynamically optimized through a machine learning model. The machine learning model is trained based on historical plug-in / plug-out data, and the input features include grid voltage waveform, ambient temperature and humidity, and the number of times the connector is used. The output is the optimal combination of parameter thresholds for each stage. When the grid harmonic distortion rate is detected to exceed the preset level, the machine learning model automatically adjusts the current growth rate of the low current transition stage, so that stable control of contact resistance can still be achieved under non-ideal grid conditions.

[0014] Furthermore, the input features of the machine learning model also include sensor fault signals; when the main sensor signal is detected to be faulty, the machine learning model automatically switches to fault optimization mode and dynamically adjusts the emergency backoff parameters in the redundancy safety control mechanism, including expanding the safety distance range and shortening the fault diagnosis cycle, so that the effectiveness of arc suppression can still be maintained in the state of sensor fault, while avoiding the interruption of plugging and unplugging operations due to excessive triggering of the redundancy mechanism.

[0015] Furthermore, the machine learning model sets differentiated optimization strategies for the power grid harmonic state; when the power grid harmonic distortion rate is detected to be in the first interval, the first optimization strategy is used to adjust the phase synchronization window width in the pre-contact stage; when the power grid harmonic distortion rate is detected to be in the second interval, the second optimization strategy is used to adjust the current growth rate in the low current transition stage; the switching threshold between the first optimization strategy and the second optimization strategy is dynamically set according to the thermal characteristics of the connector material, so that the arc suppression effect can still meet the requirements in a high harmonic power grid environment with THD>8%.

[0016] Furthermore, the meter is a multi-phase meter, and the method further includes: Simultaneously monitor the voltage phase signal and gap distance signal of each phase line; Based on the voltage phase difference of each phase line, the start time of the pre-contact stage of each phase line is set respectively, so that the signal injection of each phase line is within the zero-crossing point ± safe phase window of its corresponding phase voltage. During the low current transition phase, the current growth rate is dynamically adjusted according to the voltage vector difference between each phase line to ensure that the contact timing difference between each phase line is less than a preset threshold. During the full-connection phase, the interphase interference compensation process is executed: the metering data of each phase line is collected, the interphase coupling error is calculated and corrected in real time. The preset threshold is dynamically calculated based on the metering principle of the multiphase meter, so that under three-phase unbalanced conditions, the total arc energy generated by the plugging and unplugging of each phase line is lower than the safety limit, and the metering error caused by inter-phase interference is controlled within ±0.2%.

[0017] Compared with the prior art, the beneficial effects of the present invention are: by dynamically controlling the insertion and removal speed, signal injection and position fine adjustment in stages, it responds in real time to the changes in gap distance and power grid phase, thereby suppressing electric arc and maintaining metering accuracy while ensuring metering continuity. It has the advantages of effectively suppressing the generation of electric arc during hot insertion and removal, preventing connector ablation and insulation performance degradation, and ensuring the accuracy and continuity of metering data. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the phased control process according to an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1 A method for dynamically suppressing arcing during live plugging and unplugging of electricity meter connectors, comprising the following phased control process: During the meter insertion and removal process, the microcontroller acquires the gap distance signal between the meter plug and the socket and the grid voltage phase signal in real time. When the gap distance is detected to be within the first preset threshold range, the pre-contact stage control is initiated: the insertion and removal speed is dynamically adjusted to the first preset low speed range, and a low-frequency test signal is injected into the plug terminal simultaneously. At the same time, the phase synchronization window of the signal injection is determined based on the grid voltage phase signal, and a microampere-level conduction path is established within the phase synchronization window. When the gap distance is detected to enter the second preset threshold range, the low current transition phase control is activated: the insertion and extraction speed is increased to the second preset speed range, the output current of the test signal is linearly increased, the resistance change rate of the contact interface is monitored in real time, and when the resistance change rate exceeds the first preset fluctuation threshold, the position fine adjustment mechanism is triggered, and the signal injection is terminated within the preset phase angle range before the end of the grid voltage half cycle. When it is confirmed that the gap is completely closed and the contact resistance is stable within the preset safety threshold, the full connection stage control is started: the test signal is turned off, the insertion and extraction speed is increased to the third preset high speed range to complete the mechanical locking, and the metering system self-test process is executed to verify the arc suppression effect. The combination of parameters, including the first preset threshold range, the second preset threshold range, the first preset low-speed range, the second preset speed range, the first preset fluctuation threshold, and the preset phase angle range, limits the peak energy of the electric arc generated during insertion and removal to below the carbonization threshold of the insulating material, and controls the metering error within the accuracy level requirements of the smart meter.

[0021] In practical applications, the gap distance signal can be understood as data reflecting the physical distance between the plug and the socket. It can be acquired using laser rangefinders or ultrasonic sensors. For example, a high-precision displacement sensor can be used to measure the relative movement distance between the plug and the socket, primarily to accurately capture the critical state during the plugging and unplugging process. The grid voltage phase signal refers to the time point information of the periodic changes in grid voltage. It can be obtained through a voltage transformer combined with a phase detection circuit. For example, a phase-locked loop circuit can be used to extract the zero-crossing point of the grid voltage, primarily to achieve precise control over the timing of signal injection.

[0022] Furthermore, the low-frequency test signal in the pre-contact stage control can be in the form of a sine wave or a square wave. Its frequency range can be selected according to different numerical intervals based on the specific application scenario, such as choosing an appropriate frequency value between 10Hz and 50Hz. This is mainly to achieve low-energy conduction during initial contact. The width of the phase synchronization window can be dynamically adjusted through software algorithms. For example, a fixed phase offset can be set based on the real-time fluctuations of the grid voltage. This is mainly to ensure that the signal injection time is consistent with the phase of the grid voltage.

[0023] In the low-current transition phase control, the position fine-tuning mechanism can be achieved through minute displacements using a stepper motor drive plug. For example, a piezoelectric ceramic actuator can be used to perform nanometer-level displacement adjustments, primarily to eliminate instability at the contact interface. The selection of the preset phase angle range can be based on the waveform characteristics of the mains voltage. For example, signal injection can be terminated within a specific time period of the falling edge of the mains voltage, mainly to prevent the accumulation of arc energy caused by current interruption under high voltage conditions.

[0024] The self-test process of the metering system in the fully connected stage control can be achieved by sending a verification signal to the metering chip and analyzing the response data. For example, a test signal with known amplitude and frequency can be generated using a standard signal source, mainly to verify whether the arc suppression effect meets the requirements.

[0025] The innovation of this application lies in its proactive intervention in the entire insertion and removal process through a phased dynamic control mechanism, which solves the problems of arc generation and excessive metering errors. Specifically, it senses the dynamic changes in the gap distance and grid phase in real time and implements multi-parameter coordinated control based on this, avoiding the limitations of passive protection or power interruption in traditional solutions. In the pre-contact stage, a low-frequency test signal is injected within the phase synchronization window. By utilizing the synergistic effect of low voltage phase and extremely small current, the possibility of arc generation due to initial gap breakdown is avoided at the source. In the low-current transition stage, the current is linearly increased in conjunction with resistance change rate monitoring and position fine-tuning. This prevents arcing caused by sudden current changes and eliminates metering fluctuations caused by contact jitter through micron-level displacement. In the full connection stage, mechanical locking is achieved by shutting off the test signal and increasing the insertion and removal speed, while simultaneously executing the metering system self-test process to ensure metering accuracy. This proactive, dynamic, and multi-parameter coordinated control logic is significantly different from the passive arc extinguishing devices or simple mechanical speed limiting schemes in existing technologies, thus systematically solving the problems of arc risk and metering inaccuracy in dynamic insertion and removal.

[0026] The working principle of this application embodiment is as follows: During the meter insertion and removal operation, the microcontroller acquires the gap distance signal between the meter plug and the socket and the grid voltage phase signal in real time, providing basic data support for subsequent dynamic control. When the gap distance is detected to be within the first preset threshold range, the pre-contact stage control is initiated, wherein the insertion and removal speed is dynamically adjusted to the first preset low-speed range to reduce the product of the gap change rate and the potential difference abrupt change rate, thereby avoiding reaching the critical condition for arc ignition; at the same time, a low-frequency test signal is injected into the plug terminal, and the phase synchronization window for signal injection is determined based on the grid voltage phase signal. Within this window, a microampere-level conduction path is established to achieve arc-free initial contact. Furthermore, when the gap distance is detected to enter the second preset threshold range, a low-current transition phase control is initiated, increasing the insertion / removal speed to the second preset speed range to improve efficiency. Simultaneously, the output current of the test signal is linearly increased to ensure a smooth transition during the contact process. During this process, the resistance change rate of the contact interface is monitored in real time. When the resistance change rate exceeds the first preset fluctuation threshold, a position fine-tuning mechanism is triggered, eliminating contact instability through micron-level reverse displacement. In addition, signal injection is terminated within a preset phase angle range before the end of the grid voltage half-cycle to prevent the generation of high-energy arcs. When it is confirmed that the gap distance is completely closed and the contact resistance is stable within a preset safety threshold, a full-connection phase control is initiated, shutting off the test signal and increasing the insertion / removal speed to the third preset high-speed range to complete mechanical locking and avoid redundant operations. Simultaneously, the metering system self-test process is executed to verify the arc suppression effect and ensure metering accuracy. Thus, the combined effect of the parameters—first preset threshold range, second preset threshold range, first preset low-speed range, second preset speed range, first preset fluctuation threshold, and preset phase angle range—limits the peak energy of the arc generated during insertion / removal to below the carbonization threshold of the insulating material, and controls the metering error within the accuracy requirements of the smart meter. Specifically, this phased dynamic control mechanism fundamentally solves the problems of arc generation and excessive metering error by sensing the dynamic changes of the gap distance and the power grid phase in real time and implementing multi-parameter coordinated regulation based on this, while ensuring metering continuity.

[0027] This application further proposes that in the pre-contact stage control, the first preset threshold range of the gap distance is greater than zero and less than or equal to the safety distance threshold corresponding to the initial insertion and extraction speed. The safety distance threshold is dynamically set according to the grid voltage level and the dielectric strength of the connector material. The lower limit of the first preset low speed range is greater than zero and less than 50% of the initial insertion and extraction speed, and the upper limit is determined according to the mechanical characteristics of the insertion and extraction mechanism and the response delay time, so that when the insertion and extraction speed is within the first preset low speed range, the product of the gap distance change rate and the potential difference change rate is lower than the arc ignition critical value.

[0028] The first preset threshold range refers to a specific numerical range within which the gap distance is within a given value. This range can be dynamically adjusted based on real-time monitoring data. Specifically, the setting of this range requires a comprehensive evaluation considering the grid voltage level and the dielectric strength of the connector material. The aim is to ensure that arc-prone areas can be effectively identified under different operating conditions, avoiding insufficient adaptability due to a fixed threshold. The safe distance threshold can be understood as a dynamic parameter generated based on the grid voltage level and the dielectric strength of the connector material. It can be implemented by establishing a mathematical model or using a lookup table, aiming to enable the system to adaptively adjust to cope with high voltage or material aging scenarios. The first preset low-speed range refers to limiting the insertion and extraction speed to a specific speed range. Its lower limit is greater than zero and less than 50% of the initial insertion and extraction speed. This setting aims to prevent insertion and extraction stalls from prolonging exposure time. At the same time, by controlling the upper limit within 50% of the initial speed, it suppresses sudden increases in the gap distance change rate, thereby reducing the risk of a surge in the potential difference abrupt change rate. In addition, the consideration of the mechanical characteristics and response delay time of the insertion and extraction mechanism is to ensure that the speed adjustment command can respond to mechanical inertia in a timely manner, avoiding speed loss due to delay.

[0029] Specifically, during the pre-contact stage control process, the system first acquires the gap distance signal between the meter plug and socket and the grid voltage phase signal in real time to determine whether the gap distance falls within a first preset threshold range. When the gap distance is detected to be within this range, the system automatically initiates pre-contact stage control and dynamically adjusts the insertion and removal speed to a first preset low-speed range. Based on this, while injecting a low-frequency test signal into the plug terminals, the system determines the phase synchronization window for signal injection based on the grid voltage phase signal to establish a microampere-level conduction path. To ensure control effectiveness, the setting of the first preset threshold range fully considers changes in grid voltage levels and the dielectric strength of the connector material, allowing the safety distance threshold to be dynamically adjusted according to operating conditions. Simultaneously, the upper and lower limits of the first preset low-speed range are combined with the mechanical characteristics and response delay time of the insertion and removal mechanism to ensure that speed adjustment commands can respond promptly to mechanical inertia, preventing speed runaway due to delay. Through the above technical solution, the product of the gap distance change rate and the potential difference mutation rate is always maintained below the arc ignition critical value, thereby effectively blocking the physical conditions for arc ignition.

[0030] In summary, the above-described solution addresses the risk of arc ignition caused by parameter ambiguity by precisely defining the key parameter thresholds in the pre-contact stage. Its core lies in transforming the dynamic coupling relationship between gap distance and insertion / removal speed into a quantifiable control boundary, ensuring the proactive and adaptive nature of arc suppression. Furthermore, this solution, combined with the aforementioned phased control process, further enhances the system's robustness and metering continuity, enabling dynamic, intelligent, and precise control of the insertion / removal process under various operating conditions.

[0031] This application further proposes that in the pre-contact stage control, the frequency range of the low-frequency test signal is 50Hz to 200Hz, and the width of the phase synchronization window is dynamically adjusted according to the grid frequency fluctuation tolerance. When the grid frequency fluctuation is detected to exceed the preset tolerance, the width of the phase synchronization window is expanded proportionally, while the amplitude of the test signal is reduced to maintain the stability of the conduction path. The dynamic adjustment mechanism of the phase synchronization window is negatively correlated with the grid frequency fluctuation tolerance, so that within the range of ±2Hz grid frequency fluctuation, the phase error between the signal injection time and the grid voltage zero crossing point is always controlled within the safe window.

[0032] In practical applications, low-frequency test signals refer to electrical signals used to establish microampere-level conduction paths. Their frequency range is limited to 50Hz to 200Hz, and can be implemented using waveforms such as sine waves, square waves, or triangular waves. The purpose of selecting this frequency range is to avoid high-frequency interference disturbing the microampere-level current path while ensuring the phase synchronization of the signal with the grid voltage. The phase synchronization window refers to the safe time interval during which the signal can be injected. Its width can be dynamically adjusted according to the grid frequency fluctuation tolerance, for example, by monitoring the grid frequency fluctuation in real time and calculating the window size using linear or nonlinear algorithms. The purpose of this design is to precisely lock the safe injection timing near the voltage zero-crossing point, thereby avoiding the accumulation of phase errors caused by a fixed window. Furthermore, the dynamic adjustment mechanism refers to an adjustment strategy based on a negative correlation, which can be implemented through software algorithms or hardware circuits. Its purpose is to optimize the matching between the window width and the fluctuation characteristics, ensuring that the phase error remains within a controllable range.

[0033] Specifically, in the pre-contact stage control, the frequency range of the low-frequency test signal is selected to match the fundamental frequency characteristics of the power grid, providing a basis for dynamic adjustment of the phase window. When the power grid frequency fluctuates, the system monitors the degree of fluctuation in real time and dynamically changes the width of the phase synchronization window according to preset rules. If the detected power grid frequency fluctuation exceeds the preset tolerance, the window width is expanded proportionally, while the amplitude of the test signal is reduced to maintain the stability of the conduction path. This process reduces the current output through the synergistic relationship between amplitude and window width, avoiding current surges caused by decreased timing accuracy, thereby ensuring that the microampere-level conduction path is not disrupted. The design of the above dynamic adjustment mechanism ensures that within the range of ±2Hz power grid frequency fluctuation, the phase error between the signal injection time and the zero-crossing point of the power grid voltage is always controlled within a safe window, fundamentally suppressing the conditions for arc ignition.

[0034] The above technical solution solves the technical challenge of unstable conduction paths under power grid frequency fluctuations, ensuring the reliable establishment of microampere-level conduction paths in fluctuating environments. This solution not only improves the safety of live plug-in / plug-out operations but also lays the foundation for precise control in subsequent stages, thereby significantly enhancing the overall stability and reliability of the method.

[0035] This application further proposes a position fine-tuning mechanism in the low-current transition stage control, which includes: when the contact resistance change rate is detected to exceed a first preset fluctuation threshold, the insertion and removal operation is paused and the stepper motor is driven to perform a micron-level reverse displacement. After the contact resistance returns to stability, the insertion and removal conditions are re-evaluated. The amplitude of the micron-level reverse displacement is dynamically set according to the resistance fluctuation amplitude. When the resistance fluctuation amplitude is in the first range, the first-level displacement is executed, and when the resistance fluctuation amplitude is in the second range, the second-level displacement is executed. The first-level displacement is less than the second-level displacement, and the amplitude of each displacement level is less than the mechanical clearance tolerance of the insertion and removal mechanism.

[0036] Specifically, the position fine-tuning mechanism refers to a control strategy that adjusts the contact resistance in real time during insertion and removal to address abnormal fluctuations. This can be achieved using a stepper motor in conjunction with a high-precision displacement sensor. In practical applications, the contact resistance change rate refers to the change in contact resistance per unit time, which can be calculated using a differential algorithm on continuously sampled data to accurately determine the stability of the contact state. Micrometer-level reverse displacement refers to the minute distance the plug moves in the reverse direction along the insertion / removal path when abnormal fluctuations are detected, driven by a stepper motor. This can be achieved through microstepping drive technology or closed-loop control to prevent arcing caused by excessive insertion and removal.

[0037] In detail, this scheme achieves precise control of contact resistance fluctuations through a graded response. During the low-current transition phase, when the system detects that the contact resistance change rate exceeds the first preset fluctuation threshold, it immediately pauses the insertion / removal operation, effectively preventing a potential arcing deterioration. Subsequently, the system selectively executes different levels of reverse displacement based on the specific magnitude of the resistance fluctuation: for minor fluctuations, a smaller first-level displacement is used for adjustment, which can quickly restore stability and avoid unnecessary operational delays; for significant fluctuations, a larger second-level displacement is used to ensure effective overcoming of the unstable state of the contact interface. This graded response mechanism matches the fine-tuning action with the problem scale, and by limiting the displacement amplitude at each level within the mechanical clearance tolerance range, it effectively prevents mechanical interference or damage caused by over-adjustment. The aforementioned dynamic graded fine-tuning mechanism, combined with the control flow of the pre-contact and full-connection phases, achieves refined control of the insertion / removal process while ensuring metering continuity, thereby significantly improving the arc suppression effect and the stability of the insertion / removal operation.

[0038] The above technical solution not only solves the problem that the fixed displacement strategy cannot adapt to the differences in the scale of fluctuations, but also achieves precise control of contact resistance fluctuations through a graded response mechanism, effectively improving the stability of the insertion and extraction process and the arc suppression effect.

[0039] This application further proposes that in the fully connected stage control, the self-test process of the metering system includes: injecting a characteristic verification signal into the metering chip, collecting signal response data and comparing it with the benchmark model; when the arc energy integral value is detected to exceed the safety threshold, an emergency backoff mechanism is triggered: controlling the stepper motor to drive the plug to move in the reverse direction to a safe distance, and at the same time starting the fault diagnosis program to analyze the cause of the arc; the safe distance is dynamically set according to the current temperature rise status of the connector, and when the temperature rise exceeds the preset threshold, the safe distance range is expanded, so that secondary arcs can still be effectively avoided under the thermal aging conditions of the insulation material.

[0040] The metering system self-inspection process refers to the process of constructing a closed-loop feedback mechanism to address potential arc risks by actively verifying the metering system status. This can be achieved by injecting characteristic verification signals of specific frequency and amplitude into the metering chip and comparing the collected response data with a benchmark model, aiming to accurately capture instantaneous signal distortion caused by arcs. In practical applications, the arc energy integral value refers to the quantification of the arc impact into a quantifiable numerical indicator based on the inherent response characteristics of the metering chip under interference-free conditions. This can be achieved through real-time monitoring and cumulative calculation of arc energy, providing an objective basis for subsequent decision-making. The emergency backoff mechanism can be understood as a protection mechanism that judges the system risk level based on the cumulative effect of arc energy and takes corresponding measures. It can physically separate the contact points and block the current path by controlling the stepper motor to drive the plug to a safe distance, aiming to prevent the regeneration of secondary arcs. The safe distance refers to the physical interval dynamically adjusted according to the current temperature rise of the connector. It can be achieved by using a temperature sensor to monitor the connector temperature rise in real time and dynamically setting the safe distance range through an algorithm, aiming to take into account the performance degradation characteristics of insulation materials during thermal aging.

[0041] Specifically, this solution achieves precise quantification of the impact of electric arcs by injecting characteristic verification signals into the metering chip and collecting response data for comparison with a benchmark model. When the arc energy integral value exceeds the safety threshold, an emergency backoff mechanism is immediately triggered, driving the plug to reverse to a safe distance via a stepper motor, while simultaneously initiating a fault diagnosis program to analyze the cause of the arc. This design incorporates fault location and preventative maintenance into the process, ensuring that the root cause of the problem is traceable. In particular, the dynamic setting of the safety distance fully considers the performance changes of the insulation material during thermal aging. When the temperature rise exceeds the preset threshold, the safety distance range is automatically expanded, and the safety margin is adjusted according to the degree to which the temperature rise weakens the dielectric strength of the material. Through the above technical solution, after the meter insertion and removal operation is fully closed and the contact resistance is stable, the accumulation of arc energy can be identified and processed in a timely manner, effectively avoiding carbonization of the insulation material or distortion of metering data. Especially when the connector temperature rises abnormally, the safety strategy can be dynamically adjusted, significantly reducing the risk of secondary arcs.

[0042] This application further proposes a redundant safety control mechanism that automatically switches to a backup monitoring mode when the main sensor signal fails. The backup monitoring mode determines the gap status based on the instantaneous change rate of the contact resistance. When the resistance change rate exceeds a second preset fluctuation threshold, it determines that there is a risk of arcing and initiates an emergency backoff. The second preset fluctuation threshold is dynamically calibrated according to the connector material characteristics and environmental parameters. Its calibration rules include: reducing the fluctuation threshold in high temperature and high humidity environments and increasing the fluctuation threshold in clean and dry environments, so that the effectiveness of arc suppression can still be maintained under sensor failure conditions.

[0043] Specifically, the redundant safety control mechanism refers to a technical solution that provides additional protection when the main sensor fails, which can be implemented using a dual-channel or multi-channel monitoring system. The backup monitoring mode is a detection method independent of the main sensor, which indirectly reflects the insertion / removal gap status by real-time acquisition of changes in contact resistance. The second preset fluctuation threshold is a dynamically adjustable parameter that can adaptively adjust according to environmental conditions and material properties, aiming to ensure accurate identification of arc risks under different operating conditions.

[0044] In detail, this technical solution addresses the safety hazards caused by sensor failure by constructing a complete monitoring and response system. When the main sensor signal is lost, the system can automatically switch to a backup monitoring mode, ensuring the continuity of monitoring functions. The backup monitoring mode uses the instantaneous rate of change of contact resistance as the core criterion. Since contact resistance is strongly correlated with the state of the metal contact surface, its change characteristics can directly reflect the critical state during the insertion and removal process. When the detected rate of change of resistance exceeds a set threshold, the system immediately determines that there is a risk of arcing and triggers an emergency backoff. This rapid response mechanism effectively avoids uncontrolled arcing. Simultaneously, the dynamic calibration mechanism of the second preset fluctuation threshold considers the impact of environmental factors on the performance of the connector. In high-temperature and high-humidity environments, the threshold is lowered to improve detection sensitivity, while in clean and dry environments, the threshold is appropriately relaxed to reduce false triggering. This adaptive adjustment strategy ensures the reliability of the system under various operating conditions. Combined with the aforementioned three-stage control process, this solution significantly improves the overall safety and stability of the arc suppression system through multi-dimensional monitoring methods and flexible parameter adjustment strategies.

[0045] This application further proposes that the parameter thresholds of the three-stage control process are dynamically optimized through a machine learning model. The machine learning model is trained based on historical plug-in data, and the input features include grid voltage waveform, ambient temperature and humidity, and the number of times the connector is used. The output is the optimal combination of parameter thresholds for each stage. When the grid harmonic distortion rate is detected to exceed the preset level, the machine learning model automatically adjusts the current growth rate of the low current transition stage, so that stable control of contact resistance can still be achieved under non-ideal grid conditions.

[0046] In practical applications, machine learning models refer to algorithm-based data analysis tools that can be constructed using generalization methods such as deep neural networks, support vector machines, or random forests. Specifically, acquiring power grid voltage waveforms can be accomplished through high-precision sampling circuits, aiming to reflect the real-time state of power grid quality and provide fundamental data for parameter optimization. Monitoring environmental temperature and humidity can be achieved using integrated sensor modules, aiming to quantify the impact of external conditions on contact interface performance. Counting the number of times connectors are used can be accomplished through built-in counters, aiming to assess the degree of mechanical wear and dynamically correct for aging effects.

[0047] Specifically, this solution extracts multi-dimensional correlation patterns from historical plug-in / plug-out data using a machine learning model, incorporating grid conditions, environmental variables, and equipment lifespan into a unified decision-making framework. First, in the pre-contact phase, the model generates key parameters such as the phase synchronization window width based on the grid voltage waveform and harmonic components, ensuring that the phase error between the signal injection moment and the grid voltage zero-crossing point remains within a safe range. Second, in the low-current transition phase, the model dynamically corrects the current growth rate based on real-time detected harmonic distortion rate, effectively suppressing the impact of harmonic-induced voltage phase jitter on the contact process and preventing drastic fluctuations in contact resistance due to sudden current changes. Finally, in the full-connection phase, the model comprehensively considers factors such as the number of times the connector has been used and ambient temperature and humidity to generate optimal self-test parameters for the metering system, ensuring that the arc suppression effect meets standard requirements. Through this technical solution, a shift from passive response to proactive prediction in control paradigms is achieved, significantly improving arc suppression effectiveness and metering accuracy in complex grid environments.

[0048] This application further proposes that the input features of the machine learning model also include sensor fault signals; when the main sensor signal is detected to be faulty, the machine learning model automatically switches to fault optimization mode and dynamically adjusts the emergency backoff parameters in the redundancy safety control mechanism, including expanding the safety distance range and shortening the fault diagnosis cycle, so that the effectiveness of arc suppression can still be maintained in the state of sensor fault, while avoiding the interruption of plugging and unplugging operations due to excessive triggering of the redundancy mechanism.

[0049] Specifically, a machine learning model refers to an intelligent algorithm system trained on historical data, which can be implemented using various machine learning methods, such as support vector machines, neural networks, or decision trees. Sensor fault signals can be understood as data characteristics reflecting abnormal operating states of the main sensor. They can be generated through real-time monitoring and analysis of sensor output signals, aiming to provide a basis for proactively identifying sensor failure scenarios. Fault optimization mode is a special operating logic designed for sensor fault scenarios. It can dynamically adjust the control strategy based on the characteristics of the fault signal, thereby ensuring system stability under abnormal operating conditions. Emergency backoff parameters include the safe distance range and the fault diagnosis cycle. Expanding the safe distance range can be achieved by increasing the reverse displacement of the stepper motor, while shortening the fault diagnosis cycle can be accomplished by optimizing the time window of the diagnostic algorithm.

[0050] In detail, this solution integrates sensor fault signals into the input feature system of a machine learning model, enabling intelligent perception and dynamic response to sensor failure scenarios. Specifically, when the main sensor signal fails, the machine learning model can determine the current operating condition in real time based on the input fault signal and automatically switch to fault optimization mode. During this process, the model dynamically adjusts key parameters in the redundant safety control mechanism by analyzing the fault signal. For example, it expands the safe distance range based on the correlation between the temperature rise of the insulation material and the risk of arcing, or compresses the fault diagnosis cycle based on the urgency of the fault signal. This intelligent parameter adjustment method not only effectively avoids false triggering caused by the lag in fixed threshold calibration, but also significantly improves the robustness of the system in complex environments. Furthermore, the above solution, combined with the aforementioned three-stage control process, can maintain the effectiveness of arc suppression in complex scenarios such as partial sensor failure or sudden environmental changes, while ensuring the continuity of plugging and unplugging operations. In this way, the problem of frequent misjudgments caused by the rigidity of fixed threshold settings in the backup monitoring mode is solved, thereby improving operational safety while ensuring metering continuity and system reliability.

[0051] This application further proposes a machine learning model to set differentiated optimization strategies for power grid harmonic conditions. When the power grid harmonic distortion rate is detected to be in the first interval, the first optimization strategy is used to adjust the phase synchronization window width in the pre-contact stage. When the power grid harmonic distortion rate is detected to be in the second interval, the second optimization strategy is used to adjust the current growth rate in the low current transition stage. The switching threshold between the first and second optimization strategies is dynamically set according to the thermal characteristics of the connector material, so that the arc suppression effect can still meet the requirements of IEC 62053-22 standard in a high harmonic power grid environment with THD>8%.

[0052] Specifically, a machine learning model refers to an algorithm system trained on historical data, which can be implemented using machine learning methods such as deep neural networks, support vector machines, or random forests. In practical applications, differentiated optimization strategies can be understood as multiple parameter adjustment schemes formulated according to different power grid harmonic states, aiming to improve the system's adaptability to complex power grid environments. The first optimization strategy refers to the dynamic adjustment mechanism for the phase synchronization window width during the pre-contact stage, which can be achieved by changing the weighting coefficients in the window width calculation formula or introducing nonlinear correction factors. The second optimization strategy refers to the adjustment mechanism for the current growth rate during the low-current transition stage, which can be achieved through piecewise linear function fitting or adaptive filtering algorithms.

[0053] In detail, this technical solution achieves precise control of arc suppression parameters under high harmonic environments by constructing a differentiated optimization mechanism driven by power grid harmonic states. When the power grid harmonic distortion rate is detected to be in the first range, the system automatically activates the first optimization strategy, dynamically adjusting the phase synchronization window width during the pre-contact stage to ensure precise matching between the signal injection moment and the voltage zero-crossing point. This adjustment mechanism effectively addresses waveform distortion caused by harmonics, maintains the stability of the microampere-level conduction path, and thus suppresses the ignition of the initial arc. When the power grid harmonic distortion rate is detected to be in the second range, the system switches to the second optimization strategy, adjusting the current growth rate during the low-current transition stage to compensate for the nonlinear fluctuations in contact resistance caused by harmonics, ensuring a smooth transition. Notably, the switching threshold between the first and second optimization strategies is not a fixed value but is dynamically set based on the thermal characteristics of the connector material. This allows the system to automatically adjust the strategy switching point according to the change in dielectric properties of the material during temperature rise, avoiding failure under thermal stress due to a fixed threshold.

[0054] Through the above technical solution, even in a high-harmonic power grid environment with THD>8%, the system can still maintain a stable arc suppression effect, ensuring that metering accuracy and insulation safety requirements are effectively met. Furthermore, this solution, combined with the aforementioned three-stage control process, forms a complete dynamic optimization system, which not only improves the system's adaptability to complex power grid conditions but also significantly enhances the reliability and stability of the arc suppression effect.

[0055] This application further proposes that the meter is a multiphase meter, and the method includes: synchronously monitoring the voltage phase signal and gap distance signal of each phase line; based on the voltage phase difference of each phase line, setting the start time of the pre-contact stage for each phase line respectively, so that the signal injection of each phase line is within the zero-crossing point ± safe phase window of its corresponding phase voltage; in the low current transition stage, dynamically adjusting the current growth rate according to the voltage vector difference between each phase line to ensure that the contact timing difference of each phase line is less than a preset threshold; in the full connection stage, executing the interphase interference compensation process: collecting the metering data of each phase line, calculating the interphase coupling error and performing real-time correction; wherein, the preset threshold is dynamically calculated according to the metering principle of the multiphase meter, so that under the three-phase unbalanced working condition, the total arc energy generated by the insertion and removal operation of each phase line is lower than the safety limit, and the metering error caused by interphase interference is controlled within ±0.2%.

[0056] Specifically, synchronous monitoring refers to the real-time acquisition of voltage phase signals and gap distance signals of each phase line through sensors. This can be achieved using high-precision Hall sensors or photoelectric encoders, aiming to provide an accurate real-time status basis to avoid timing mismatches caused by missing information. The pre-contact stage initiation timing refers to the independently set operating starting point based on the voltage phase differences of each phase line. This can be achieved using a timer module in a microcontroller combined with a phase detection algorithm, aiming to ensure precise signal injection matching of the zero-crossing windows of each phase to avoid the risk of arc ignition. In practical applications, the current growth rate during the low-current transition stage refers to the dynamically adjusted growth rate based on the voltage vector difference. This can be achieved using PID control algorithms or fuzzy control algorithms, aiming to finely control the contact speed of each phase to prevent the superposition of arc energy. Furthermore, the interphase interference compensation process refers to the real-time correction process by collecting metering data of each phase line and calculating interphase coupling errors. This can be achieved using a digital signal processor combined with an adaptive filtering algorithm, aiming to eliminate electromagnetic coupling interference to ensure metering accuracy.

[0057] Specifically, this scheme achieves precise control over the live insertion and removal process of multi-phase meters by constructing a multi-phase collaborative control mechanism. First, the synchronous monitoring module continuously collects the voltage phase signal and gap distance signal of each phase line, which is transmitted to the control unit for subsequent decision-making. Based on the collected phase differences, the control unit calculates the initiation timing of the pre-contact stage for each phase line. Since there is an inherent time difference between the zero-crossing points of the voltages of each phase in a multi-phase power grid, this method of independently setting the initiation timing allows the signal injection to accurately match the zero-crossing window of each phase, thereby effectively avoiding the critical risk of arcing caused by phase asynchrony. During the low-current transition stage, the system dynamically adjusts the current growth rate according to the voltage vector difference between each phase line. This adjustment method directly reflects the instantaneous magnitude of the phase-to-phase potential difference. By finely controlling the contact speed of each phase, the contact timing difference between each phase line is kept within a minimal range, preventing the superposition of arc energy between different phase lines due to insufficient timing dispersion. During the fully connected phase, the system executes an interphase interference compensation process. It collects metering data from each phase line and calculates interphase coupling errors for real-time correction. Dynamic compensation is performed for electromagnetic coupling interference caused by insertion and removal operations, ensuring the accuracy of the metering system under complex operating conditions. The dynamic calculation mechanism for preset thresholds reflects the adaptive nature of the solution. Under three-phase unbalanced conditions, the thresholds are dynamically adjusted according to metering principles, allowing the solution to adapt to actual operating conditions. This maintains metering accuracy while ensuring the safety of the total arc energy, demonstrating the integrity and robustness of multiphase system control.

[0058] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for dynamically suppressing arcing during live plugging and unplugging of an electricity meter connector, characterized in that, This includes the following phased control process: During the meter insertion and removal process, the microcontroller acquires the gap distance signal between the meter plug and the socket and the grid voltage phase signal in real time. When the gap distance is detected to be within the first preset threshold range, the pre-contact stage control is initiated: the insertion and removal speed is dynamically adjusted to the first preset low speed range, and a low-frequency test signal is injected into the plug terminal simultaneously. At the same time, the phase synchronization window of the signal injection is determined based on the grid voltage phase signal, and a microampere-level conduction path is established within the phase synchronization window. When the gap distance is detected to enter the second preset threshold range, low current transition phase control is initiated: the insertion and extraction speed is increased to the second preset speed range, the output current of the test signal is linearly increased, the resistance change rate of the contact interface is monitored in real time, and when the resistance change rate exceeds the first preset fluctuation threshold, the position fine-tuning mechanism is triggered, and the signal injection is terminated within the preset phase angle range before the end of the grid voltage half-cycle. When it is confirmed that the gap distance is completely closed and the contact resistance is stable within the preset safety threshold, the full connection stage control is started: the test signal is turned off, the insertion and extraction speed is increased to the third preset high speed range to complete the mechanical locking, and the metering system self-test process is executed to verify the arc suppression effect. The combination of parameters, including the first preset threshold range, the second preset threshold range, the first preset low-speed range, the second preset speed range, the first preset fluctuation threshold, and the preset phase angle range, limits the peak energy of the electric arc generated during insertion and removal to below the carbonization threshold of the insulating material, and controls the metering error within the accuracy level requirements of the smart meter.

2. The method for dynamic suppression of live insertion and removal arcing of meter connectors according to claim 1, characterized in that: In the pre-contact stage control, the first preset threshold range of the gap distance is greater than zero and less than or equal to the safety distance threshold corresponding to the initial insertion / removal speed. The safety distance threshold is dynamically set according to the power grid voltage level and the dielectric strength of the connector material. The lower limit of the first preset low-speed range is greater than zero and less than 50% of the initial insertion / removal speed, and the upper limit is determined according to the mechanical characteristics of the insertion / removal mechanism and the response delay time, so that when the insertion / removal speed is within the first preset low-speed range, the product of the gap distance change rate and the potential difference change rate is lower than the arc ignition critical value.

3. The method for dynamic suppression of live insertion and removal arcing of meter connectors according to claim 2, characterized in that: In the pre-contact stage control, the frequency range of the low-frequency test signal is 50Hz to 200Hz, and the width of its phase synchronization window is dynamically adjusted according to the grid frequency fluctuation tolerance. When the grid frequency fluctuation is detected to exceed the preset tolerance, the width of the phase synchronization window is expanded proportionally, while the amplitude of the test signal is reduced to maintain the stability of the conduction path. The dynamic adjustment mechanism of the phase synchronization window is negatively correlated with the grid frequency fluctuation tolerance, so that within the range of ±2Hz grid frequency fluctuation, the phase error between the signal injection time and the grid voltage zero crossing point is always controlled within the safe window.

4. The method for dynamic suppression of live insertion and removal arcing of meter connectors according to claim 3, characterized in that: In the low-current transition phase control, the position fine-tuning mechanism includes: when the contact resistance change rate is detected to exceed a first preset fluctuation threshold, the insertion / removal operation is paused and the stepper motor is driven to perform a micrometer-level reverse displacement. After the contact resistance returns to stability, the insertion / removal conditions are reassessed. The amplitude of the micrometer-level reverse displacement is dynamically set according to the resistance fluctuation amplitude. When the resistance fluctuation amplitude is in the first range, the first-level displacement is executed, and when the resistance fluctuation amplitude is in the second range, the second-level displacement is executed. The first-level displacement is smaller than the second-level displacement, and the amplitude of each displacement level is smaller than the mechanical clearance tolerance of the insertion / removal mechanism.

5. The method for dynamic suppression of live insertion and removal arcing of meter connectors according to claim 4, characterized in that: In the fully connected stage control, the self-test process of the metering system includes: injecting a feature verification signal into the metering chip, collecting signal response data and comparing it with a benchmark model; when the arc energy integral value is detected to exceed the safety threshold, an emergency backoff mechanism is triggered: controlling the stepper motor to drive the plug to move in the reverse direction to a safe distance, and simultaneously starting a fault diagnosis program to analyze the cause of the arc; the safe distance is dynamically set according to the current temperature rise status of the connector, and when the temperature rise exceeds the preset threshold, the safe distance range is expanded, so that secondary arcs can still be effectively avoided under the thermal aging conditions of the insulation material.

6. The method for dynamic suppression of live insertion and removal arcing of meter connectors according to claim 5, characterized in that: It also includes a redundant safety control mechanism that automatically switches to a backup monitoring mode when the main sensor signal fails. The backup monitoring mode determines the gap status based on the instantaneous change rate of the contact resistance. When the resistance change rate is detected to exceed the second preset fluctuation threshold, it is determined that there is a risk of electric arc and an emergency backoff is initiated. The second preset fluctuation threshold is dynamically calibrated based on the connector material characteristics and environmental parameters. Its calibration rules include: reducing the fluctuation threshold in high temperature and high humidity environments and increasing the fluctuation threshold in clean and dry environments, so that the effectiveness of arc suppression can still be maintained under sensor failure conditions.

7. The method for dynamic suppression of live insertion and removal arcing of meter connectors according to claim 5, characterized in that: The parameter thresholds of the three-stage control process are dynamically optimized through a machine learning model. The machine learning model is trained based on historical plug-in / plug-out data. The input features include grid voltage waveform, ambient temperature and humidity, and the number of times the connector is used. The output is the optimal combination of parameter thresholds for each stage. When the grid harmonic distortion rate is detected to exceed the preset level, the machine learning model automatically adjusts the current growth rate of the low current transition stage, so that stable control of contact resistance can still be achieved under non-ideal grid conditions.

8. The method for dynamic suppression of live insertion and removal arcing of meter connectors according to claim 6, characterized in that: The input features of the machine learning model also include sensor fault signals; when the main sensor signal is detected to be faulty, the machine learning model automatically switches to fault optimization mode and dynamically adjusts the emergency backoff parameters in the redundancy safety control mechanism, including expanding the safety distance range and shortening the fault diagnosis cycle, so that the effectiveness of arc suppression can still be maintained in the state of sensor fault, while avoiding the interruption of plugging and unplugging operations due to excessive triggering of the redundancy mechanism.

9. The method for dynamic suppression of live insertion and removal arcing of meter connectors according to claim 7, characterized in that: The machine learning model sets differentiated optimization strategies for the power grid harmonic state. When the power grid harmonic distortion rate is detected to be in the first interval, the first optimization strategy is used to adjust the phase synchronization window width in the pre-contact stage. When the power grid harmonic distortion rate is detected to be in the second interval, the second optimization strategy is used to adjust the current growth rate in the low current transition stage. The switching threshold between the first and second optimization strategies is dynamically set according to the thermal characteristics of the connector material, so that the arc suppression effect can still meet the requirements in a high harmonic power grid environment with THD>8%.

10. The method for dynamic suppression of live insertion and removal arcing of meter connectors according to claim 1, characterized in that, The meter is a multiphase meter, and the method further includes: Simultaneously monitor the voltage phase signal and gap distance signal of each phase line; Based on the voltage phase difference of each phase line, the start time of the pre-contact stage of each phase line is set respectively, so that the signal injection of each phase line is within the zero-crossing point ± safe phase window of its corresponding phase voltage. During the low current transition phase, the current growth rate is dynamically adjusted according to the voltage vector difference between each phase line to ensure that the contact timing difference between each phase line is less than the preset threshold. During the full-connection phase, the interphase interference compensation process is executed: the metering data of each phase line is collected, the interphase coupling error is calculated and corrected in real time. The preset threshold is dynamically calculated based on the metering principle of the multiphase meter, so that under three-phase unbalanced conditions, the total arc energy generated by the plugging and unplugging of each phase line is lower than the safety limit, and the metering error caused by inter-phase interference is controlled within ±0.2%.

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