Intelligent control method for power consumption of vacuum circuit breaker

Abstract

The invention discloses an intelligent power consumption control method for a vacuum circuit breaker, and particularly relates to the technical field of circuit breakers. An electromagnetic response model of a permanent magnetic mechanism is constructed by obtaining environment parameters and historical operation data of a circuit breaker, and the relation between PWM frequency and a resonance area is judged in real time and dynamically adjusted; a test pulse mechanism is introduced to verify action conditions, and action accuracy is ensured in combination with closed-loop monitoring of current and magnetic field response; according to the method, the operation reliability, the action accuracy and the energy efficiency level of the circuit breaker in a complex environment are effectively improved.

Description

Technical Field

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

[0002] Intelligent control of the power consumption of a vacuum circuit breaker refers to the real-time monitoring and dynamic adjustment of the energy consumption of the vacuum circuit breaker during operation through intelligent technologies, so as to optimize its working state and reduce unnecessary energy consumption. This technology comprehensively uses sensors, control algorithms, and communication modules to achieve precise control of the operating electromagnets, heaters, and auxiliary equipment of the circuit breaker, thereby improving the energy efficiency of the equipment operation and the overall economy and stability of the system.

[0003] The existing technologies have the following deficiencies: In the process of controlling the on-off of the coil of the permanent magnet operating mechanism by using the PWM pulse width modulation algorithm, when the PWM frequency is electromagnetically resonantly coupled with the coil or the magnetic circuit, it may cause non-linear electromagnetic disturbances, resulting in delayed or incomplete suction or release actions, and even serious consequences such as local overheating of the coil, misjudgment of the control system, or refusal of the circuit breaker to operate. In addition, when control fails in places with high altitude, low temperature, or complex electromagnetic interference, due to its strong concealment and difficulty in troubleshooting, it may pose a major threat to the system stability. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent control method for the power consumption of a vacuum circuit breaker to solve the deficiencies in the background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: An intelligent control method for the power consumption of a vacuum circuit breaker, including: Obtaining the current working environment parameters of the circuit breaker and the historical operation data of the permanent magnet operating mechanism, and establishing an electromagnetic response model of the permanent magnet operating mechanism; Judging whether the currently set PWM control signal frequency is close to the coil resonance frequency through the electromagnetic response model; If it is close to the resonance frequency, adjust the PWM frequency to avoid the resonance region; Before the circuit breaker is sucked or released, sending a preset test pulse and detecting the current response and response time of the coil, and if the response meets the set action conditions, execute the suction or release operation; During the operation, real-time monitoring the current and magnetic field response conditions and performing closed-loop control; After the operation is completed, automatically turn off the holding current of the control coil and enter the low-power standby mode.

[0006] Preferably, the obtaining of the current working environment parameters of the circuit breaker includes: installing an environmental sensor module inside the circuit breaker to collect in real time parameters including environmental temperature, relative humidity, atmospheric pressure or altitude, external electromagnetic interference intensity, and power supply voltage fluctuation, and using the collected parameters as model input features.

[0007] Preferably, the establishing of the electromagnetic response model of the permanent magnet operating mechanism includes: Extracting historical operation data from the data storage module of the controller, where the data includes action response time, current waveform, number of actions, peak current, holding current, and coil temperature; Performing feature extraction and normalization processing on the data, and forming a feature vector to be input into a neural network model for training; The neural network adopts a double-layer LSTM structure for extracting time series characteristics and aging trends.

[0008] Preferably, the judging whether the PWM frequency is close to the resonance frequency includes: Reading the PWM frequency value output by the current controller; Calculating an estimated value of the resonance frequency under the current environmental parameters through the electromagnetic response model; Calculating the offset Δf between the PWM frequency and the resonance frequency: ; where is the current estimated value of the resonance frequency, represents the frequency of the PWM signal currently set by the controller.

[0009] Preferably, set an offset safety threshold , if Δf ≤ , it is determined that the current PWM frequency is close to the resonance frequency; if Δf > , it is determined that the PWM frequency is in the safe operating area and no adjustment is required.

[0010] Preferably, the adjusting of the PWM frequency includes: Obtaining the resonance frequency and its bandwidth range, and generating a prohibited PWM frequency interval; Excluding the interval from the available frequency gears of the controller to form a candidate frequency set; Predicting the response time, power consumption, and stability of each candidate frequency through the electromagnetic response model; Selecting the optimal frequency and writing it into the controller to update the PWM control parameters.

[0011] Preferably, the sending of the preset test pulse and the detection of the response include: Before the formal closing or opening operation, output a group of low-amplitude short-time test pulses to the coil; Collect and analyze the coil current waveform, and extract the current rising slope, peak current, and response time; Compare the extracted parameters with the action standard threshold. If the conditions are met, the main control action is allowed to be executed. If not, the operation is aborted and the abnormality is recorded.

[0012] Preferably, the closed-loop control includes: During the operation, collect the coil current waveform and the magnetic flux response curve simultaneously; Extract the peak value of the current change rate and the magnetic flux lag delay time; Calculate the comprehensive electromagnetic consistency index EMCI through normalization processing; Compare EMCI with the set threshold. If it is lower than the threshold, perform operations such as pulse time extension, PWM frequency fine-tuning, duty cycle increase, or repeated excitation adjustment.

[0013] Preferably, to obtain the peak value of the current change rate, specifically: at the first rising edge after the action pulse is started, the system records the current curve at a high sampling rate; perform a first-order differential on the current signal within a unit time to obtain the current change rate; record the maximum value during the current rising stage, which is the peak value of the current change rate; to obtain the magnetic flux lag delay time, specifically: record the curve of the magnetic induction intensity generated by the coil over time through a magnetic field sensor; synchronously record the moment when the current reaches the steady-state peak value; compare the time correspondence relationship between the two rising waveforms, and measure the time difference between the current peak and the magnetic induction peak; define the time difference as the magnetic flux lag delay time.

[0014] Preferably, the automatic shutdown to maintain the current and enter the low-power standby mode includes: after the operation is completed, confirm that the circuit breaker is in place through the position detector, and control the current to enter a stable state; turn off the PWM control output and the buffer circuit, and the controller switches to the low-power operation mode; turn off the high-speed sampling module, reduce the processing frequency, and mask non-critical interrupts, only retaining the communication wake-up channel.

[0015] In the above technical solution, the technical effects and advantages provided by the present invention are: 1. By introducing the electromagnetic response modeling and intelligent control mechanism, the present invention solves the problems of abnormal actions, excessive energy consumption, and control failure caused by the PWM frequency and coil resonance coupling in the prior art. By obtaining the environmental parameters and historical operation data in real time to construct a neural network model, and combining the prediction of the resonance risk by the model, the dynamic resonance avoidance control of the PWM frequency is realized, effectively avoiding the resonance interference caused by environmental changes or mechanism aging, and improving the action reliability and safety of the circuit breaker under extreme working conditions.

[0016] 2. The present invention verifies the operation feasibility in advance through preset test pulses, monitors the electromagnetic response by combining the current change rate and the flux hysteresis time during the suction / release process, constructs a comprehensive consistency evaluation mechanism, and realizes the closed-loop regulation control of the whole process. After the operation is completed, the system automatically enters the low-power standby state, significantly reducing the energy consumption and extending the equipment life. The overall solution integrates the "prediction + verification + monitoring + energy-saving" strategy, realizing the intelligent and efficient operation of the vacuum circuit breaker in a complex power environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments recorded in the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings.

[0018] Figure 1 It is a method mind map of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0020] For the embodiments, please refer to Figure 1 As shown, the intelligent power consumption control method for the vacuum circuit breaker in this embodiment includes: Obtain the current working environment parameters of the circuit breaker and the historical operation data of the permanent magnet operating mechanism, and establish an electromagnetic response model of the permanent magnet operating mechanism; Judge whether the currently set PWM control signal frequency is close to the coil resonance frequency through the electromagnetic response model; If it is close to the resonance frequency, adjust the PWM frequency to avoid the resonance region; Before the circuit breaker is sucked or released, send a preset test pulse and detect the current response and response time of the coil. If the response meets the set action conditions, perform the suction or release operation; During the operation, monitor the current and magnetic field response in real time and perform closed-loop control; After the operation is completed, automatically turn off the holding current of the control coil and enter the low-power standby mode.

[0021] Obtain the parameters of the current working environment: Install an environmental sensor module to collect the key influencing factors of the operating environment where the circuit breaker is located, including but not limited to: environmental temperature (T), relative humidity (RH), atmospheric pressure (P) or altitude, external electromagnetic interference intensity (EMI), and the fluctuation of the working power supply voltage (Vin_ripple).

[0022] Read the historical records from the data storage module of the controller, including: the time required for each closing / releasing action (t_response), the current waveform (I(t)) corresponding to each action, the cumulative value of the number of actions (N_total), the peak current, average current, holding current, temperature rise data (such as coil temperature), and the event logs of previous action abnormalities (delay, failure, misoperation).

[0023] The goal of building an electromagnetic response model is to simulate and predict the action responses of the permanent magnet mechanism under different control signals and different environments. This model can be implemented by the following methods: Input the historical data into a neural network for fitting and modeling, for example: Integrate a temperature sensor, a voltage sampling module, a current transformer, an electromagnetic interference detection module, and an action time detection module in the vacuum circuit breaker control system; After each closing or releasing action is completed, record the following original data corresponding to this operation: The PWM frequency output by the controller; the environmental temperature during the operation; the sampled values of the current waveform; the real-time voltage of the control power supply; the response time of closing / releasing; whether the closing action is successful; the current cumulative number of actions; the temperature of the operating mechanism body.

[0024] Filter the collected current waveform data; calculate the key parameters such as the current peak value, current rising edge time, current average value, and current holding time; calculate the time decay trend of parameters such as temperature, voltage, and current; Normalize the above data and construct a feature vector in a unified format as the input data of the neural network model.

[0025] Build a two-layer LSTM network and set the input dimension equal to the dimension of the feature vector; The first layer of LSTM is used to extract the changing features of the operation behavior in the time series; The second layer of LSTM is used to remember the historical state and aging trend; The output of LSTM is connected to a fully connected neural network for mapping to multiple task outputs; Configure the output structure as four parallel output nodes, corresponding to the following prediction targets respectively: Whether the action is successful (classification); Response time (regression); Operating power consumption (regression); Resonance risk level (multi-classification); Set the loss function to be a combination type, including cross-entropy loss function and mean squared error loss function; Use Stochastic Gradient Descent (SGD) or Adam optimizer for training configuration.

[0026] Import historical operation data into the model for initial training; After each round of training, evaluate the model accuracy and average error; According to the evaluation results, adjust the network hyperparameters, including the number of LSTM units, learning rate, dropout, etc.; When the model reaches the set error threshold on the validation set, export the final model file; Quantize the model and compress it into a model format suitable for embedded deployment (such as TensorFlow Lite).

[0027] Embed the trained model into the vacuum circuit breaker controller; Before each circuit breaker operation, the model reads the currently collected input features; Input this feature vector into the model and run the model for prediction; Obtain the prediction output, including the probability of successful closing, expected response time, estimated power consumption, resonance risk level; After the operation is completed, record the actual response time, whether it is successful, current waveform and power consumption data of this time; compare the recorded results with the model prediction values and calculate the error; cache the action data of this time as a new sample into the feedback dataset.

[0028] Every time a certain number of feedback samples are accumulated (such as 10 groups), trigger an online training, use mini-batch samples to slightly fine-tune the model parameters. If the prediction error continuously deviates from the set range, start the full-scale retraining mechanism, reload the updated model into the control system to overwrite the old model.

[0029] Judge whether the current PWM frequency is close to the coil resonance frequency, specifically including: Step 1: Obtain the current PWM control frequency, and read the PWM output frequency setting value (unit: kHz) that will be used for the operating mechanism inside the controller.

[0030] Step 2: Extract the coil parameters and working environment information, and collect the 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 a temperature sensor); magnetic permeability corresponding to the coil material (can be estimated by the historical data model); current waveform characteristics (such as rise time, peak change rate); Calculate the equivalent resonant frequency of the coil in the current state through an electromagnetic response model (neural network model), and extract the estimated value of the current resonant frequency from the model output.

[0031] Step 3: Calculate the offset Δf between the PWM frequency and the resonant frequency: ; where is the estimated value of the current resonant frequency, represents the frequency of the PWM (pulse width modulation) signal currently set by the controller, and the unit is usually Hertz (Hz) or kilohertz (kHz).

[0032] Set the offset safety threshold (usually 2 - 5 kHz, specifically determined according to the system resonance bandwidth); if Δf ≤ , it is determined that the current PWM frequency is close to the resonant frequency; if Δf > , it is determined that the PWM frequency is in the safe operating area and no adjustment is required.

[0033] Adjust the PWM frequency: Step 4: According to the model or experimental parameters, obtain the resonance influence bandwidth of the current system (for example, ±3 kHz); calculate the frequency avoidance interval as: , where δ is the safety bandwidth, and mark this interval as the prohibited PWM frequency interval.

[0034] Step 5: From the available PWM frequency gears of the controller, eliminate the resonance interval; retain the set of feasible frequencies whose frequency changes do not affect the control effect, such as: [12 kHz, 14 kHz], [18 kHz, 20 kHz], [25 kHz, 28 kHz]; Sort the candidate frequencies, and give priority to the frequency closest to the original set frequency to reduce system disturbance.

[0035] Step 6: Call the electromagnetic response model to simulate and estimate each candidate frequency, and predict the following indicators: action response time; power consumption required for the action; stability of the control current waveform; Select the PWM frequency with the optimal control performance as the new frequency value; if all candidate frequencies cannot meet the performance requirements, trigger the soft start pulse + action segmentation backup strategy.

[0036] Step 7: Write the new PWM frequency setting value into the controller; the controller outputs the coil control signal at this frequency; during the suction / release operation, monitor the current and response time in real time, record the action effect; feedback the operation result of the new frequency to the model for subsequent optimization of the frequency recommendation logic.

[0037] Preset test pulse detection and action judgment, specifically including: The controller receives the closing or releasing operation instructions issued by the host computer, the 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; it determines whether it meets the preset conditions and needs to perform the test pulse pre-action detection process; this process is mainly used to evaluate whether the coil or the permanent magnet mechanism has the stable action ability and to detect potential risks in advance.

[0038] The controller calls the internal parameter table and loads the currently matched test pulse configuration parameters: pulse voltage amplitude (usually lower than the main closing 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 set values.

[0039] The controller applies a low-power short-time test pulse to the coil through the PWM signal output port; simultaneously starts the sampling module to perform high-frequency sampling on the current change at both ends of the coil and records the sampling timestamp.

[0040] During the test pulse, record the coil current waveform data, including: initial current rising speed; peak current; steady-state holding time; back electromotive force response; response time (i.e., the time taken for the current to reach the set threshold). Filter the original current signal to remove power supply noise and environmental disturbances; Extract the following key features from the current waveform: Current rising slope (dI / dt); deviation of the peak current from the reference standard; comparison of the response time with the action threshold; whether there are abnormal phenomena such as spike jitter and waveform distortion.

[0041] Judge 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, it is determined that the operating mechanism is in a normal executable state; if any judgment item does not meet the standard, it is determined as a potential action failure risk, and the controller will block the main action output.

[0042] If it is determined that the response is satisfied, the controller enters the main action execution process, issues a high-energy closing / releasing control pulse, and starts the closed-loop feedback mechanism to monitor the entire action process.

[0043] If it is determined that the response is abnormal, the controller does not perform the main operation, reports the action blocking status to the host or the dispatching system; records the current test pulse data for subsequent maintenance or algorithm correction.

[0044] Start the closed-loop monitoring process: The controller sends out the main pulse signal for the closing or releasing action to start the permanent magnet operating mechanism; at the same time, the monitoring system is activated to collect the coil current change and the magnetic field signal feedback in real time.

[0045] Install the following two types of sensor modules inside the controller or the circuit breaker housing: Current sensor module: used to collect the coil drive current waveform during the action process; Magnetic field induction module (Hall sensor or magnetoresistive sensor): used to sense the actual magnetic flux change of the permanent magnet or the iron core.

[0046] Obtain the peak value of the current change rate, specifically: At the first rising edge after the action pulse starts, the system records the current curve at a high sampling rate; Perform the first-order differentiation on the current signal within a unit time to obtain the current change rate; Record the maximum value during the current rising stage, that is, the peak value of the current change rate (unit: A / ms); The peak value of the current change rate reflects whether the operating coil obtains effective excitation in the first time, and can judge the power supply response and the coil integrity in advance.

[0047] Obtain the flux hysteresis delay time, specifically: Record the change curve of the magnetic induction intensity (unit: T or G) generated by the coil with time through the magnetic field sensor; Synchronously record the moment when the current reaches the steady-state peak value; Compare the time correspondence relationship of the rising waveforms of the two, and measure the time difference between the current peak and the magnetic induction peak; Define the time difference as the flux hysteresis delay time (unit: ms); The flux hysteresis delay time is used to judge the magnetic circuit response speed and the suction matching degree of the mechanical part, and can discover the potential hazards of mechanical hysteresis or magnetic saturation in advance.

[0048] Normalize the peak value of the current change rate and the flux hysteresis delay time so that they are both in the range of [0, 1]. Calculate the comprehensive electromagnetic consistency index EMCI according to the normalized peak value of the current change rate and the flux hysteresis delay time: ; where: is the normalized peak value of the current change rate, is the normalized flux hysteresis delay time; k is an empirical coefficient (calibrated according to different coil / permanent magnet types); The larger, the faster the excitation, the faster the magnetic circuit response, and the higher the suction efficiency; Compare the comprehensive electromagnetic consistency index with the built-in preset threshold to determine whether the current action quality meets the standard. If the comprehensive electromagnetic consistency index is greater than or equal to the preset threshold, it is determined that the current action process meets the design expectation; the control system maintains the current control strategy and completes the normal closed-loop operation; record the current EMCI value and status for model feedback and optimization.

[0049] If the comprehensive electromagnetic consistency index is less than the preset threshold: it is determined that there is a lag or incoordination in the current electromagnetic response; the controller performs one or more of the following closed-loop adjustment operations: Prolong the pulse time by 1 - 2 ms; increase the PWM duty cycle by 5 - 10%; modify the PWM frequency to deviate from the current setting by ±2 kHz; start the emergency repetitive excitation mechanism and reissue the short-time compensation pulse; at the same time, mark this operation as partially abnormal and save the detailed data.

[0050] Control the coil to maintain the current off and enter the low-power standby mode, specifically: The controller completes the output of the breaker closing or opening operation instruction; through the position detector (such as Hall switch, mechanical displacement sensor) or the closing feedback signal, confirm that the breaker has reached the expected mechanical position; synchronously read that the coil current has entered the stable state and there is no current excitation operation being executed; the system marks the action completion status and prepares to enter the post-processing link.

[0051] The controller determines that the current operation is a permanent magnet mechanism control structure and does not require continuous maintenance of the closing current; check whether the following two safety conditions are met: The closing state hold lock is successful; the system is not in the remote manual test or special mode; after the conditions are met, issue the "maintaining current off instruction".

[0052] The controller sends a termination pulse command to the PWM drive module; disconnect the power device (such as MOSFET or IGBT) in the control power output loop to stop power supply to the coil; if there is a freewheeling or buffer circuit, the controller synchronously closes the buffer current path; the current sensor confirms that the coil current has dropped to zero.

[0053] The controller enters the low-power working mode and performs the following actions: Turn off the unnecessary high-speed ADC sampling module; reduce the CPU or MCU main frequency to the standby frequency; keep only the minimum necessary communication and monitoring modules running; mask all interrupts except for remote wake-up and alarm wake-up; the overall system power consumption drops to the idle state, only maintaining online monitoring and remote wake-up response.

[0054] Record the timestamp, control parameters, and power consumption data at the end of the current closing or opening; set the standby status flag bit. The system is ready to exit the standby state in the following events: receiving a new closing / opening control instruction; events such as voltage fluctuations, current anomalies, and temperature alarms occur; the timed self-check cycle arrives, triggering background data update.

[0055] All the above formulas are dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0056] 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 programs are loaded or executed on the computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. 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 in a wired or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that contains one or more collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0057] It should be understood that the term "and / or" in this text is merely a description of the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. Additionally, the character " / " in this text generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be understood by referring to the context before and after. Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this text can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0058] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application.

Claims

1. An intelligent control method for the power consumption of a vacuum circuit breaker, characterized in that: Including: Obtain the current operating environment parameters of the circuit breaker and the historical operation data of the permanent magnet operating mechanism, and establish an electromagnetic response model of the permanent magnet operating mechanism; Judge whether the frequency of the currently set PWM control signal is close to the coil resonance frequency through the electromagnetic response model; If it is close to the resonance frequency, adjust the PWM frequency to avoid the resonance region; Before the circuit breaker is attracted or released, send a preset test pulse and detect the current response and response time of the coil. If the response meets the set action conditions, perform the attraction or release operation; During the operation, monitor the current and magnetic field response conditions in real time and perform closed-loop control; After the operation is completed, automatically turn off the holding current of the control coil and enter the low-power standby mode.

2. The intelligent control method for the power consumption of a vacuum circuit breaker according to claim 1, wherein: The obtaining of the current operating environment parameters of the circuit breaker includes: installing an environmental sensor module inside the circuit breaker to collect parameters including environmental 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 the power consumption of a vacuum circuit breaker according to claim 2, characterized in that: The establishment of the electromagnetic response model of the permanent magnet operating mechanism includes: Extract historical operation data from the data storage module of the controller. The data includes action response time, current waveform, number of actions, peak current, holding current, and coil temperature; Perform feature extraction and normalization processing on the data, and form a feature vector to be input into the neural network model for training; The neural network adopts a two-layer LSTM structure to extract time series characteristics and aging trends.

4. The intelligent control method for the power consumption of a vacuum circuit breaker according to claim 3, characterized in that: The judgment of whether the PWM frequency is close to the resonance frequency includes: Read the PWM frequency value output by the current controller; Calculate the estimated resonance frequency value 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, represents the frequency of the PWM signal currently set by the controller.

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

6. The intelligent control method for the power consumption of a vacuum circuit breaker according to claim 5, characterized in that: The adjustment of the PWM frequency includes: Obtain the resonance frequency and its bandwidth range, and generate a prohibited PWM frequency interval; Exclude the interval from the available frequency gears of the controller to form a candidate frequency set; Predict the response time, power consumption, and stability of each candidate frequency through the 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 the power consumption of a vacuum circuit breaker according to claim 6, characterized in that: The sending of the preset test pulse and the detection of the response include: Before the formal attraction or release operation, output a group of low-amplitude short-time test pulses to the coil; Collect and analyze the coil current waveform, and extract the current rise slope, peak current, and response time; Compare the extracted parameters with the action standard threshold. If the conditions are met, allow the execution of the main control action. If not, abort the operation and record the abnormality.

8. The intelligent control method for the power consumption of a vacuum circuit breaker according to claim 7, characterized in that: The closed-loop control includes: Collect the coil current waveform and the magnetic flux response curve simultaneously during the operation; Extract the peak value of the current change rate and the magnetic flux lag delay time; Calculate the comprehensive electromagnetic consistency index EMCI through normalization processing; Compare the EMCI with the set threshold. If it is lower than the threshold, perform operations such as pulse time extension, PWM frequency fine-tuning, duty cycle increase, or repeated excitation adjustment.

9. The intelligent control method for the power consumption of a vacuum circuit breaker according to claim 8, characterized in that: Obtain the peak value of the current change rate, specifically: after the action pulse is started, at the first rising edge, the system records the current curve at a high sampling rate; within a unit time, perform a first-order differentiation on the current signal to obtain the current change rate; record the maximum value during the current rising stage, that is, the peak value of the current change rate; obtain the flux lag delay time, specifically: record the curve of the magnetic induction intensity generated by the coil changing with time through a magnetic field sensor; synchronously record the moment when the current reaches the steady-state peak value; compare the time correspondence relationship of the rising waveforms of the two, and measure the time difference between the current peak value and the magnetic induction peak value; define the time difference as the flux lag delay time.

10. The intelligent control method for the power consumption of a vacuum circuit breaker according to claim 9, characterized in that: The automatic shutdown to maintain the current and enter the low-power standby mode includes: after the operation is completed, confirm that the circuit breaker is in place through a position detector, and control the current to enter a stable state; turn off the PWM control output and the buffer circuit, and the controller switches to the low-power operation mode; turn off the high-speed sampling module, reduce the processing frequency, mask non-critical interrupts, and only retain the communication wake-up channel.

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