Intelligent control method for power consumption of vacuum circuit breaker

Abstract

The present invention discloses an intelligent power consumption control method for a vacuum circuit breaker, specifically relating to the technical field of circuit breakers. By acquiring the environmental parameters and historical operating data of the circuit breaker, an electromagnetic response model of a permanent magnet mechanism is constructed, and the relationship between the PWM frequency and the resonant region is determined in real time and dynamically adjusted. A test pulse mechanism is introduced to verify the operating conditions, and closed-loop monitoring of the current and magnetic field response is combined to ensure the accuracy of the operation. After the operation is completed, the holding current is automatically turned off, and a low-power consumption mode is entered. This method effectively improves the operating reliability, operation accuracy, and energy efficiency of the circuit breaker in complex environments.

Description

Technical Field

[0001] The present invention relates to the technical field of circuit breakers, and in particular to an intelligent power consumption control method for a vacuum circuit breaker. Background Art

[0002] Intelligent power consumption control for vacuum circuit breakers uses intelligent technology to monitor and dynamically adjust the energy consumption of vacuum circuit breakers during operation in real time, optimizing their operating state and reducing unnecessary energy consumption. This technology integrates sensors, control algorithms, and communication modules to achieve precise control of the circuit breaker's operating electromagnet, heater, and auxiliary equipment, thereby improving the energy efficiency of the equipment and the overall economic efficiency and stability of the system.

[0003] The existing technology has the following shortcomings:

[0004] When using PWM (Pulse Width Modulation) algorithms to control the on / off power of permanent magnet actuator coils, electromagnetic resonance coupling between the PWM frequency and the coils or magnetic circuits can trigger nonlinear electromagnetic disturbances, leading to delayed or incomplete engagement or release, and even serious consequences such as localized coil overheating, control system misjudgment, or circuit breaker failure. Furthermore, control failures at high altitudes, low temperatures, or locations with complex electromagnetic interference can pose a significant threat to system stability due to their concealment and difficulty in troubleshooting. Summary of the Invention

[0005] The object of the present invention is to provide a method for intelligently controlling power consumption of a vacuum circuit breaker to solve the deficiencies in the background technology.

[0006] In order to achieve the above object, the present invention provides the following technical solution: a method for intelligently controlling power consumption of a vacuum circuit breaker, comprising:

[0007] Obtain the current working environment parameters of the circuit breaker and the historical operating data of the permanent magnetic operating mechanism, and establish an electromagnetic response model of the permanent magnetic operating mechanism;

[0008] The electromagnetic response model is used to determine whether the currently set PWM control signal frequency is close to the coil resonant frequency;

[0009] If it is close to the resonant frequency, the PWM frequency is adjusted to avoid the resonant region;

[0010] Before the circuit breaker is closed or released, a preset test pulse is sent to detect the current response and response time of the coil. If the response meets the set action conditions, the closing or releasing operation is performed;

[0011] During operation, the current and magnetic field response are monitored in real time and closed-loop control is performed;

[0012] After the operation is completed, the holding current of the control coil is automatically turned off and the system enters low-power standby mode.

[0013] Preferably, obtaining the current working environment parameters of the circuit breaker includes: installing an environmental sensor module in the circuit breaker body to collect parameters including ambient temperature, relative humidity, atmospheric pressure or altitude, external electromagnetic interference intensity and power supply voltage fluctuation in real time, and using the collected parameters as model input features.

[0014] Preferably, establishing the electromagnetic response model of the permanent magnet operating mechanism includes:

[0015] Extracting historical operation data from a data storage module of the controller, the data including action response time, current waveform, number of actions, peak current, holding current and coil temperature;

[0016] Extracting features and normalizing the data to form feature vectors that are input into a neural network model for training;

[0017] The neural network adopts a double-layer LSTM structure to extract time series characteristics and aging trends.

[0018] Preferably, the determining whether the PWM frequency is close to the resonant frequency includes:

[0019] Read the PWM frequency value currently output by the controller;

[0020] Calculate the estimated value of the resonant frequency under the current environmental parameters through the electromagnetic response model;

[0021] Calculate the offset Δf between the PWM frequency and the resonant frequency: Where, is the estimated value of the current resonant frequency, Indicates the frequency of the PWM signal currently set by the controller.

[0022] Preferably, set the offset safety threshold , if Δf ≤ , determine that the current PWM frequency is close to the resonant frequency; if Δf > , it is determined that the PWM frequency is in the safe working area and no adjustment is required.

[0023] Preferably, the adjusting the PWM frequency includes:

[0024] Obtain the resonant frequency and its bandwidth range, and generate the prohibited PWM frequency range;

[0025] Eliminate intervals from the available frequency ranges of the controller to form a candidate frequency set;

[0026] The response time, power consumption and stability of each candidate frequency are predicted using an electromagnetic response model;

[0027] Select the optimal frequency and write it into the controller to update the PWM control parameters.

[0028] Preferably, the sending of a preset test pulse and detecting a response includes:

[0029] Before the formal pull-in or release operation, a group of low-amplitude short-time test pulses are output to the coil;

[0030] Collect and analyze the coil current waveform to extract the current rising slope, peak current and response time;

[0031] The extracted parameters are compared with the action standard threshold. If the conditions are met, the main control action is allowed to be executed. If not, the operation is terminated and the exception is recorded.

[0032] Preferably, the closed-loop control includes:

[0033] During operation, the coil current waveform and magnetic flux response curve are collected simultaneously;

[0034] Extract the peak value of current change rate and magnetic flux hysteresis delay time;

[0035] The comprehensive electromagnetic consistency index EMCI is calculated through normalization processing;

[0036] The EMCI is compared with the set threshold. If it is lower than the threshold, pulse time extension, PWM frequency fine-tuning, duty cycle increase or repetitive excitation adjustment operations are performed.

[0037] Preferably, the peak value of the current change rate is obtained, specifically: at the first rising edge after the action pulse is started, the system records the current curve at a high sampling rate; performs first-order differentiation on the current signal in unit time to obtain the current change rate; records the maximum value in the current rising stage, that is, the peak value of the current change rate; obtains the flux lag delay time, specifically: records the curve of the magnetic induction intensity generated by the coil over time through the magnetic field sensor; synchronously records the moment when the current reaches the steady-state peak; compares the time correspondence between the rising waveforms of the two, and measures the time difference from the current peak to the magnetic induction peak; and defines the time difference as the flux lag delay time.

[0038] Preferably, the automatic shutdown of the maintenance current and entering the low-power standby mode includes: after the operation is completed, confirming through the position detector that the circuit breaker is in place and the control current enters a stable state; shutting down the PWM control output and the buffer loop, and the controller switches to a low-power operation mode; shutting down the high-speed sampling module, reducing the processing frequency, shielding non-critical interrupts, and retaining only the communication wake-up channel.

[0039] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0040] 1. This invention addresses existing issues such as abnormal operation, excessive energy consumption, and control failure caused by the coupling of PWM frequency and coil resonance by introducing electromagnetic response modeling and intelligent control mechanisms. By constructing a neural network model based on real-time acquisition of environmental parameters and historical operating data, and combining this model with predictions of resonance risks, it implements dynamic harmonic avoidance control of the PWM frequency. This effectively mitigates resonant interference caused by environmental changes or mechanism aging, improving the circuit breaker's operational reliability and safety under extreme operating conditions.

[0041] 2. This invention verifies operational feasibility in advance through preset test pulses. It also monitors the electromagnetic response during the pull-in / pull-out process by combining the current rate of change and magnetic flux lag time, establishing a comprehensive consistency evaluation mechanism and enabling closed-loop regulation and control throughout the entire process. Upon completion of the action, the system automatically enters a low-power standby state, significantly reducing energy consumption and extending equipment life. This overall solution integrates a "prediction + verification + monitoring + energy saving" strategy, enabling intelligent and efficient operation of vacuum circuit breakers in complex power environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0043] Figure 1 This is a mind map of the method of the present invention. DETAILED DESCRIPTION

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0045] For examples, see Figure 1 As shown, the intelligent control method for power consumption of a vacuum circuit breaker according to this embodiment includes:

[0046] Obtain the current working environment parameters of the circuit breaker and the historical operating data of the permanent magnetic operating mechanism, and establish an electromagnetic response model of the permanent magnetic operating mechanism;

[0047] The electromagnetic response model is used to determine whether the currently set PWM control signal frequency is close to the coil resonant frequency;

[0048] If it is close to the resonant frequency, the PWM frequency is adjusted to avoid the resonant region;

[0049] Before the circuit breaker is closed or released, a preset test pulse is sent to detect the current response and response time of the coil. If the response meets the set action conditions, the closing or releasing operation is performed;

[0050] During operation, the current and magnetic field response are monitored in real time and closed-loop control is performed;

[0051] After the operation is completed, the holding current of the control coil is automatically turned off and the system enters low-power standby mode.

[0052] Obtaining current operating environment parameters: Install an environmental sensor module to collect key factors affecting the circuit breaker's operating environment, including but not limited to ambient temperature (T), relative humidity (RH), atmospheric pressure (P) or altitude, external electromagnetic interference (EMI), and power supply voltage fluctuation (Vin_ripple).

[0053] Read historical records from the controller's data storage module, including: the time required for each pull-in / pull-out action (t_response), the current waveform corresponding to each action (I(t)), the cumulative number of actions (N_total), the peak current, average current, holding current, temperature rise data (such as coil temperature) during operation, and previous action anomaly (delay, failure, malfunction) event logs.

[0054] The goal of building an electromagnetic response model is to simulate and predict the action response of a permanent magnet mechanism under different control signals and different environments. This model can be implemented using the following methods:

[0055] Input historical data into the neural network for fitting modeling, for example:

[0056] Integrate temperature sensor, voltage sampling module, current transformer, electromagnetic interference detection module, and action time detection module into the vacuum circuit breaker control system;

[0057] After each pull-in or release action is completed, the following raw data corresponding to the operation is recorded:

[0058] PWM frequency output by the controller; ambient temperature during operation; current waveform sampling value; real-time voltage of the control power supply; response time of pull-in / release; whether the pull-in action is successful; current cumulative number of actions; temperature of the operating mechanism body.

[0059] Filter the collected current waveform data; calculate key parameters such as current peak value, current rise time, current average value, current maintenance time, etc.; calculate the time decay trend of parameters such as temperature, voltage, and current;

[0060] The above data are standardized and constructed into feature vectors in a unified format as input data for the neural network model.

[0061] Build a two-layer LSTM network and set the input dimension to be equal to the feature vector dimension;

[0062] The first layer of LSTM is used to extract the changing characteristics of operation behavior in time series;

[0063] The second layer of LSTM is used to memorize historical states and aging trends;

[0064] The LSTM output is connected to a fully connected neural network for mapping to multiple task outputs;

[0065] Configure the output structure as four parallel output nodes, corresponding to the following prediction targets:

[0066] Whether the action was successful (classification);

[0067] response time (regression);

[0068] Operating power consumption (regression);

[0069] Resonance risk level (multiple categories);

[0070] Set the loss function to a combination of cross entropy loss function and mean square error loss function;

[0071] Use stochastic gradient descent (SGD) or Adam optimizer for training configuration.

[0072] Import historical operation data into the model for initial training;

[0073] After each round of training, the model accuracy and average error are evaluated;

[0074] Based on the evaluation results, adjust the network hyperparameters, including the number of LSTM units, learning rate, dropout, etc.

[0075] When the model reaches the set error threshold on the validation set, export the final model file;

[0076] Quantize the model and compress it into a model format suitable for embedded deployment (such as TensorFlow Lite).

[0077] Embed the trained model into the vacuum circuit breaker controller;

[0078] Before each circuit breaker operation, the model reads the currently collected input features;

[0079] Input the feature vector into the model and run the model to make predictions;

[0080] Obtain prediction outputs, including the probability of successful engagement, estimated response time, estimated power consumption, and resonance risk level;

[0081] After the operation is completed, the actual response time, success, current waveform and power consumption data are recorded; the recorded results are compared with the model prediction value and the error is calculated; the action data is cached as a new sample in the feedback data set.

[0082] Every time a certain number of feedback samples are accumulated (such as 10 groups), online training is triggered, and the model parameters are slightly fine-tuned using micro-batch samples. If the prediction error continues to deviate from the set range, the full retraining mechanism is started, and the updated model is reloaded into the control system to overwrite the old model.

[0083] Determine whether the current PWM frequency is close to the coil resonant frequency, specifically including:

[0084] Step 1: Get the current PWM control frequency. The controller reads the PWM output frequency setting value (in kHz) to be used for the operating mechanism.

[0085] Step 2: Extract coil parameters and working environment information, and collect key physical state parameters of the current operating mechanism coil, including: real-time inductance value (obtained through dynamic testing or model prediction); current ambient temperature (obtained through temperature sensor); magnetic permeability corresponding to the coil material (which can be estimated from historical data models); current waveform characteristics (such as rise time and peak change rate);

[0086] The equivalent resonant frequency of the coil in its current state is calculated using an electromagnetic response model (neural network model), and the current resonant frequency estimate is extracted from the model output.

[0087] Step 3: Calculate the offset Δf between the PWM frequency and the resonant frequency: Where, is the estimated value of the current resonant frequency, Indicates the frequency of the PWM (Pulse Width Modulation) signal currently set by the controller, usually in Hertz (Hz) or kilohertz (kHz).

[0088] Setting the offset safety threshold (usually 2~5kHz, determined by the system resonance bandwidth); if Δf≤ , determine that the current PWM frequency is close to the resonant frequency; if Δf > , it is determined that the PWM frequency is in the safe working area and no adjustment is required.

[0089] Adjust the PWM frequency:

[0090] Step 4: Obtain the resonance influence bandwidth of the current system (e.g., ±3kHz) based on the model or experimental parameters; calculate the frequency avoidance range as: , δ is the safe bandwidth, marking this interval as the prohibited PWM frequency interval.

[0091] Step 5: Eliminate the resonant range from the available PWM frequency ranges of the controller and retain a set of feasible frequencies where frequency changes do not affect the control effect, such as:

[0092] [12kHz, 14kHz], [18kHz, 20kHz], [25kHz, 28kHz];

[0093] Sort the candidate frequencies and give priority to the frequencies closest to the original set frequency to reduce system disturbances.

[0094] Step 6: Use the electromagnetic response model to simulate and estimate each candidate frequency, and predict the following indicators: action response time; action power consumption; control current waveform stability;

[0095] The PWM frequency with the best control performance is selected as the new frequency value; if all candidate frequencies cannot meet the performance requirements, the soft start pulse + action segment backup strategy is triggered.

[0096] Step 7: Write the new PWM frequency setting value to the controller; the controller outputs the coil control signal at this frequency; monitor the current and response time in real time during the pull-in / pull-out operation and record the action effect; and feed the operation results of the new frequency back to the model for subsequent optimization of the frequency recommendation logic.

[0097] Preset test pulse detection and action judgment, including:

[0098] The controller receives the pull-in or release operation instruction from the host computer, dispatching system or local remote control; the controller enters the operation preparation state, but does not immediately start the main action pulse; the system reads the current power supply voltage, ambient temperature, PWM frequency, electromagnetic model estimation and other status data; determines whether the preset conditions are met and needs to perform the test pulse pre-action detection process; this process is mainly used to evaluate whether the coil or permanent magnet mechanism has the ability to operate stably and discover potential risks in advance.

[0099] The controller calls the internal parameter table and loads the currently matched test pulse configuration parameters: pulse voltage amplitude (usually lower than the main pull-in voltage, such as 70%~80%); pulse width (for example, 1~3 milliseconds); rising edge control mode (slow rise or instantaneous); PWM duty cycle and frequency setting value.

[0100] The controller applies a low-power, short-duration test pulse to the coil through the PWM signal output port; synchronously starts the sampling module to perform high-frequency sampling of the current changes at both ends of the coil and record the sampling timestamp.

[0101] During the test pulse, the coil current waveform data is recorded, including: initial current rise rate; peak current; steady-state holding time; back EMF reaction; response time (i.e., the time it takes for the current to reach the set threshold). The original current signal is filtered to remove power supply noise and environmental disturbances.

[0102] The following key features are extracted from the current waveform:

[0103] Current rise slope (dI / dt); deviation of peak current from the reference standard; comparison of response time and action threshold; whether there are abnormal phenomena such as spike jitter, waveform distortion, etc.

[0104] Determine whether the current response meets the preset action conditions, including: the current response speed is greater than the minimum dI / dt threshold; the peak current reaches the specified effective suction criterion; there is no abnormal oscillation or abnormal sound signal; the response time is less than the set maximum allowable value (such as ≤30ms); if all judgment conditions are met, the operating mechanism is deemed to be in a normal executable state; if any judgment item does not meet the standard, it is determined to be a potential action failure risk, and the controller will prevent the main action output.

[0105] If the response is determined to be satisfied, the controller enters the main action execution process, sends a high-energy pull-in / release control pulse, and starts a closed-loop feedback mechanism to monitor the entire action process.

[0106] If the response is determined to be abnormal, the controller does not execute the main operation and reports the action blocking status to the host or scheduling system; the current test pulse data is recorded for maintenance or subsequent algorithm correction.

[0107] Start the closed-loop monitoring process: the controller sends a main pulse signal for the pull-in or release action to start the permanent magnet operating mechanism; at the same time, the monitoring system is activated to collect coil current changes and magnetic field signal feedback in real time.

[0108] The following two types of sensor modules are installed in the controller or circuit breaker housing:

[0109] Current sensor module: used to collect the coil drive current waveform during the action process;

[0110] Magnetic field sensing module (Hall sensor or magnetoresistive sensor): used to sense the actual magnetic flux changes of permanent magnets or iron cores.

[0111] Get the peak value of the current change rate, specifically:

[0112] At the first rising edge after the action pulse is started, the system records the current curve at a high sampling rate;

[0113] Perform first-order differentiation on the current signal in unit time to obtain the current change rate;

[0114] Record the maximum value during the current rising phase, that is, the peak value of the current change rate (unit: A / ms);

[0115] The peak value of the current change rate reflects whether the operating coil is effectively excited in the first place, and can judge the power supply response and coil integrity in advance.

[0116] Get the flux hysteresis delay time, specifically:

[0117] The magnetic field sensor records the curve of the magnetic induction intensity (unit T or G) generated by the coil over time;

[0118] Synchronously record the moment when the current reaches the steady-state peak;

[0119] Compare the time correspondence of the two rising waveforms and measure the time difference from the current peak to the magnetic induction peak;

[0120] The time difference is defined as the flux lag delay time (unit: ms);

[0121] The magnetic flux hysteresis delay time is used to determine the matching degree between the magnetic circuit response speed and the mechanical part's attraction, and can detect mechanical hysteresis or magnetic saturation risks in advance.

[0122] The peak value of the current change rate and the magnetic flux hysteresis delay time are normalized so that they are both between [0,1]. The comprehensive electromagnetic consistency index EMCI is calculated based on the normalized peak value of the current change rate and the magnetic flux hysteresis delay time: ;in: is the normalized peak value of the current change rate, is the normalized flux hysteresis delay time; k is the empirical coefficient (calibrated according to different coil / permanent magnet types); The larger the value, the faster the excitation, the faster the magnetic circuit response, and the higher the pull-in efficiency;

[0123] The integrated electromagnetic consistency index (EMCI) is compared with a built-in preset threshold to determine whether the current motion quality meets the standard. If the integrated electromagnetic consistency index is greater than or equal to the preset threshold, the current motion process is determined to meet the design expectations. The control system maintains the current control strategy and completes normal closed-loop operation. The EMCI value and status are recorded for model feedback and optimization.

[0124] If the comprehensive electromagnetic consistency index is less than the preset threshold, it is determined that the current electromagnetic response is lagging or uncoordinated. The controller performs one or more of the following closed-loop adjustment operations:

[0125] Extend the pulse time by 1-2ms; increase the PWM duty cycle by 5-10%; modify the PWM frequency to deviate from the current setting by ±2kHz; start the emergency re-excitation mechanism and re-issue the short-time compensation pulse; at the same time, mark this operation as a partial abnormality and save detailed data.

[0126] The control coil maintains current off and low power standby mode, specifically:

[0127] The controller completes the output of the circuit breaker closing or releasing operation instruction; confirms that the circuit breaker has reached the expected mechanical position through the position detector (such as Hall switch, mechanical displacement sensor) or the closing feedback signal; synchronously reads that the coil current has entered a stable state and no excitation action is currently being executed; the system marks the action completion status and prepares to enter the post-processing link.

[0128] The controller determines that the current operation is a permanent magnet mechanism control structure and does not need to continuously maintain the pull-in current. It checks whether the following two safety conditions are met:

[0129] The energized state remains locked successfully; the system is not in remote manual test or special mode; when the conditions are met, a "maintain current off command" is issued.

[0130] The controller sends a pulse termination command to the PWM drive module; disconnects the power devices (such as MOSFET or IGBT) in the control power output circuit to stop powering the coil; if there is a freewheeling or buffer circuit, the controller simultaneously closes the buffer current path; the current sensor confirms that the coil current has dropped to zero.

[0131] The controller enters low-power mode and performs the following actions:

[0132] Turn off unnecessary high-speed ADC sampling modules; reduce the CPU or MCU main frequency to the standby frequency; keep only the minimum necessary communication and monitoring modules running; shield all interrupts except remote wake-up and alarm wake-up; reduce the overall system power consumption to an idle state, and only maintain online monitoring and remote wake-up response.

[0133] Record the timestamp, control parameters and power consumption data of the current closing or releasing end; set the standby state flag, and the system is ready to exit standby in the following events: receiving a new closing / opening control command; voltage fluctuation, current anomaly, temperature alarm and other events occur; the scheduled self-test cycle arrives, triggering background data update.

[0134] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0135] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0136] It should be understood that the term "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist at the same time, and B exists alone, where A and B may be singular or plural. In addition, the character " / " herein generally indicates that the objects associated with each other are in an "or" relationship, but it may also indicate an "and / or" relationship, which can be understood by referring to the context. A person of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0137] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. An intelligent control method for power consumption of a vacuum circuit breaker, characterized in that: include: Obtain the current working environment parameters of the circuit breaker and the historical operating data of the permanent magnetic operating mechanism, and establish an electromagnetic response model of the permanent magnetic operating mechanism; The electromagnetic response model is used to determine whether the currently set PWM control signal frequency is close to the coil resonant frequency; If it is close to the resonant frequency, the PWM frequency is adjusted to avoid the resonant region; Before the circuit breaker is closed or released, a preset test pulse is sent to detect the current response and response time of the coil. If the response meets the set action conditions, the closing or releasing operation is performed; During operation, the current and magnetic field response are monitored in real time and closed-loop control is performed; The closed-loop control includes: simultaneously collecting the coil current waveform and the magnetic flux response curve during operation; extracting the current change rate peak and the magnetic flux hysteresis delay time; calculating the comprehensive electromagnetic consistency index (EMCI) through normalization processing; comparing the EMCI with a set threshold value; and executing pulse time extension, PWM frequency fine-tuning, duty cycle increase, or repeated excitation adjustment operations if the EMCI is lower than the threshold; The peak value of the current change rate is obtained by: recording the current curve at a high sampling rate on the first rising edge after the action pulse is started; performing first-order differentiation on the current signal within a unit time to obtain the current change rate; recording the maximum value in the current rising phase, i.e., the peak value of the current change rate; obtaining the magnetic flux lag delay time, specifically: recording the time-varying curve of the magnetic induction intensity generated by the coil through a magnetic field sensor; synchronously recording the moment when the current reaches the steady-state peak; comparing the time correspondence between the rising waveforms of the two, and measuring the time difference from the current peak to the magnetic induction peak; defining the time difference as the magnetic flux lag delay time; After the operation is completed, the holding current of the control coil is automatically turned off and the system enters low-power standby mode.

2. The intelligent control method for power consumption of a vacuum circuit breaker according to claim 1, characterized in that: The method of obtaining the current working environment parameters of the circuit breaker includes: installing an environmental sensor module in the circuit breaker body to collect parameters including ambient temperature, relative humidity, atmospheric pressure or altitude, external electromagnetic interference intensity and power supply voltage fluctuation in real time, and using the collected parameters as model input features.

3. The intelligent control method for power consumption of a vacuum circuit breaker according to claim 2, characterized in that: The establishing of the electromagnetic response model of the permanent magnet operating mechanism includes: Extracting historical operation data from a data storage module of the controller, the data including action response time, current waveform, number of actions, peak current, holding current and coil temperature; Extracting features and normalizing the data to form feature vectors that are input into a neural network model for training; The neural network adopts a double-layer LSTM structure to extract time series characteristics and aging trends.

4. The intelligent control method for power consumption of a vacuum circuit breaker according to claim 3, characterized in that: Determining whether the PWM frequency is close to the resonant frequency includes: Read the PWM frequency value currently output by the controller; Calculate the estimated value of the resonant frequency under the current environmental parameters through the electromagnetic response model; Calculate the offset Δf between the PWM frequency and the resonant frequency: Where, is the estimated value of the current resonant frequency, Indicates the frequency of the PWM signal currently set by the controller.

5. The intelligent control method for power consumption of a vacuum circuit breaker according to claim 4, characterized in that: Setting the offset safety threshold , if Δf ≤ , determine that the current PWM frequency is close to the resonant frequency; if Δf > , it is determined that the PWM frequency is in the safe working area and no adjustment is required.

6. The intelligent control method for power consumption of a vacuum circuit breaker according to claim 5, characterized in that: The adjusting of the PWM frequency comprises: Obtain the resonant frequency and its bandwidth range, and generate the prohibited PWM frequency range; Eliminate intervals from the available frequency ranges of the controller to form a candidate frequency set; The response time, power consumption and stability of each candidate frequency are predicted using an electromagnetic response model; Select the optimal frequency and write it into the controller to update the PWM control parameters.

7. The intelligent control method for power consumption of a vacuum circuit breaker according to claim 6, characterized in that: The sending of a preset test pulse and detecting a response includes: Before the formal pull-in or release operation, a group of low-amplitude short-time test pulses are output to the coil; Collect and analyze the coil current waveform to extract the current rising slope, peak current and response time; The extracted parameters are compared with the action standard threshold. If the conditions are met, the main control action is allowed to be executed. If not, the operation is terminated and the exception is recorded.

8. The intelligent control method for power consumption of a vacuum circuit breaker according to claim 1, characterized in that: The automatic shutdown of the holding current and entry into the low-power standby mode includes: after the operation is completed, confirming through a position detector that the circuit breaker is in place and the control current is stable; shutting down the PWM control output and the buffer loop, and switching the controller to the low-power operation mode; shutting down the high-speed sampling module, reducing the processing frequency, shielding non-critical interrupts, and retaining only the communication wake-up channel.

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