Circuit breaker rigid regulation and control method and system based on load monitoring terminal

Abstract

The invention discloses a circuit breaker rigid regulation and control method and system based on a load monitoring terminal, and relates to the technical field of electric power automation, and the method comprises the following steps: S1, obtaining a unified nanosecond time base line, continuously collecting current signals of a plurality of loops, reconstructing a complete phase track of each loop current, generating a corresponding low-frequency lag fingerprint base line, and carrying out the collection of the low-frequency lag fingerprint base line; the reference basis is used for dynamic response correction; and S2, constructing a causal playback chain based on the low-frequency hysteresis fingerprint baseline, replaying a current transition behavior in the rigid regulation and control process of the circuit breaker, identifying a nonlinear hysteresis section, and extracting a threshold drift core parameter. According to the method, the current phase is reconstructed through the nanosecond-level time base, the lagging characteristics are extracted, the causal playback and energy coupling model is constructed, threshold double-track generation and time sequence correction are achieved, lagging energy is dissipated in combination with a phase conjugate instruction, the regulation and control precision and stability of a circuit breaker are improved, and the safety and the intelligent level of a power distribution network are enhanced.

Description

Technical Field

[0001] This invention relates to the field of power automation technology, and more specifically to a method and system for rigid control of circuit breakers based on load monitoring terminals. Background Technology

[0002] "Rigid Circuit Breaker Control Based on Load Monitoring Terminals" refers to a high-precision power control method in power distribution networks that uses load monitoring terminals as the core execution and sensing unit to monitor, remotely control, and manage the opening and closing status of circuit breakers in real time. Its "rigidity" is manifested in the fact that when critical states such as overload, short circuit, or abnormal power fluctuations occur, the system executes forced disconnection or closing actions through the terminal's built-in relays, achieving load disconnection and power isolation with a response time of seconds, ensuring system safety without relying on manual intervention. This control process relies on the terminal's high-precision current and voltage acquisition, control loop access detection, national cryptographic encryption communication, and event reporting mechanisms, enabling independent decision-making and execution for each branch load, forming a closed-loop rigid control chain from status perception and command issuance to action feedback. Through this architecture, the circuit breaker is transformed from a traditional passive protection element into an active control unit with intelligent identification and safe execution capabilities, thereby significantly improving the reliability, real-time performance, and safety protection level of the power distribution system.

[0003] The existing technology has the following shortcomings:

[0004] In existing technologies, when a load monitoring terminal performs continuous rigid control operations on multiple circuit breakers, the current sampling links of each circuit generally employ low-frequency filtering structures to suppress noise interference, which easily leads to dynamic response lag during high-frequency switching and high-power transitions. This low-frequency lag causes a time offset between the phase of the monitoring signal and the actual current change, thus forming a nonlinear hysteresis loop in the terminal feedback closed loop. As the hysteresis accumulates, the system's judgment of the circuit breaker's operating threshold becomes misaligned, and the control pulse output experiences cross-cycle delays, ultimately exceeding the safety control window of rigid control. This causes the circuit breaker actuator to remain in a semi-driven state for an extended period, triggering control lock-up or continuous high-temperature erosion of the contacts. In severe cases, it can lead to mechanical instability, localized overheating of the busbar, and control circuit failure, making it difficult to guarantee the reliability and safety of multi-circuit synchronous control.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for rigid control of circuit breakers based on load monitoring terminals, so as to solve the problems in the background art mentioned above.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a circuit breaker rigid control method based on a load monitoring terminal, comprising the following steps:

[0008] S1. Obtain a unified nanosecond-level time baseline, continuously acquire current signals from multiple loops, reconstruct the complete phase trajectory of the current in each loop, and generate the corresponding low-frequency hysteresis fingerprint baseline as a reference for dynamic response correction.

[0009] S2, based on the low-frequency hysteresis fingerprint baseline, constructs a causal replay chain to replay the current transition behavior during the rigid control process of the circuit breaker, identifies the nonlinear hysteresis section, and extracts the core parameters of threshold drift.

[0010] S3, using the drift core parameters to generate phase mapping relationship and residual spectrum, calculate the energy coupling strength between loops, construct threshold misalignment surface and determine the delay time window boundary of control response;

[0011] S4, under the constraint of the delay time window, construct a dual-track threshold structure combining fast track and slow track, and correct the timing of control pulses by real-time tracking of hysteresis rhythm by fast track and solidification of baseline characteristics by slow track, combined with feedforward control field.

[0012] S5 generates a phase conjugate control instruction set under stable feedforward control field conditions, implements time-frequency inverse diffusion suppression, amplitude limiting write-back and interference self-suppression operations, dissipates control energy accumulation online, realizes dynamic unlocking and temperature rise mitigation of the control chain, and constructs a closed-loop stable rigid control system.

[0013] Preferably, step S1 includes:

[0014] A unified nanosecond-level time baseline is obtained. A nanosecond-level time sequence signal is generated through a high-precision clock source, a temperature-compensated oscillator, and a phase-locked loop circuit. The signal is then distributed to multiple current sampling channels and configured with delay compensation to achieve time alignment.

[0015] Under the constraint of a unified nanosecond-level time baseline, the current signals of multiple current loops are continuously acquired. Each loop uses a high-resolution analog-to-digital converter chip and a bandpass filter circuit. The acquisition results are uploaded to the main control buffer through time tags and synchronized.

[0016] Based on the continuous sampling data after synchronization and processing, the complete phase trajectory of each current loop is reconstructed through sliding segment comparison and adjacent differential operation. The window length and weight distribution are adjusted for high-frequency disturbances to ensure the continuity of the phase trajectory.

[0017] Based on the reconstructed phase trajectory, by comparing the time offset between the actual rising edge and the theoretical transition point, hysteresis response features are extracted and a two-dimensional response mapping surface is established to generate a low-frequency hysteresis fingerprint trajectory with delay, distortion and drift properties.

[0018] Preferably, step S2 includes:

[0019] Based on the low-frequency hysteresis fingerprint baseline, a causal playback chain of multiple loops aligned with a unified nanosecond-level time baseline is constructed to obtain the time offset relationship between the current phase trajectory and the sampled data, and to establish a multi-time axis synchronization reference table.

[0020] In the causal replay chain, current transition events within the replay segment are extracted around the time point of the control command issuance, delayed response, frequency oscillation, amplitude rebound and waveform changes are identified, and behavioral dynamic modeling is performed.

[0021] Based on the transition behavior modeling results, an error accumulation trajectory analysis mechanism is introduced to construct error curves, identify key time segments of hysteresis in multiple channels where unidirectional cumulative offset occurs, and label key response feature information.

[0022] Within the critical time interval of hysteresis, periodic offset trend parameters, instantaneous amplitude disturbance parameters, and cross-channel coupling response parameters are extracted, and control path matching and multi-period statistical analysis are performed to form a core parameter set for threshold drift.

[0023] Preferably, the extraction of the threshold drift core parameter set further includes: performing trend fitting on the periodic offset trend parameters, performing amplitude fluctuation statistics on the instantaneous amplitude disturbance parameters, and determining the inter-channel phase offset synchronization of the cross-channel coupling response parameters, so as to improve the dynamic correction accuracy of the threshold judgment.

[0024] Preferably, step S3 includes:

[0025] Based on the threshold drift core parameters, a phase mapping relationship between multi-loop current signals is constructed. The phase response trajectory is compared by sliding through a multi-cycle translation window to form a phase response mapping surface with time coordinates and loop number as reference axes.

[0026] Based on the phase mapping relationship, a phase residual spectrum is constructed. By performing differential operations on the actual phase trajectory and the expected phase curve, a phase residual spectrum with time locality and frequency distribution characteristics is generated.

[0027] The energy coupling strength between current loops is calculated using phase mapping relationship and phase residual spectrum. By constructing a multidimensional time coupling matrix, abrupt points of coupling strength change are identified and representative coupling relationship pairs are extracted.

[0028] Based on the analysis results of energy coupling strength and phase residual, a threshold judgment misalignment surface is constructed. The control response delay time window boundary is determined by surface fitting and spectral amplitude deformation, which is used for subsequent action judgment constraints.

[0029] Preferably, the threshold judgment misaligned surface constructs an intermediate response surface by interpolation between adjacent loops, and performs local region fitting by combining the amplitude change of the corresponding frequency band in the phase residual spectrum, so that the misaligned surface is continuous and has dynamic response characteristics.

[0030] Preferably, step S4 includes:

[0031] Under the constraint of the delay time window boundary, a fast track threshold generation structure is constructed, and a fast response correction threshold is generated based on the current cycle current change rate, phase offset velocity and high frequency component density in the residual spectrum.

[0032] While the fast track is running, a slow track threshold generation structure is constructed. Based on the sampling window with the smallest cross-cycle error fluctuation, a baseline threshold curve is generated as a steady-state response trend reference, and a fast and slow track coordinated threshold output is formed.

[0033] Based on the dynamic threshold of dual-track coordinated output, combined with the time response model in the delay time window and the feedforward control field, the error between the current control point and the optimal trigger point is calculated, and the control pulse output correction timing is generated.

[0034] The desired response curve generated by the feedforward control field is matched with the dual-track output results. The timing of the control pulse trigger is determined based on the matching degree, and the correction parameters are fed back to update the subsequent response prediction template.

[0035] Preferably, the fast-track threshold generation structure further dynamically adjusts the sliding window length based on the density of high-frequency components in the residual spectrum to enhance the real-time tracking capability of the current transition response, and preferentially triggers fast threshold correction when the error exceeds the set threshold.

[0036] Preferably, step S5 includes:

[0037] Under stable operation conditions of the feedforward control field, a dynamic control instruction set containing phase conjugate commands is generated. The fast track and slow track threshold outputs are used as input signals. The control command generation space with time and phase dual references is constructed by combining the current phase response trajectory and residual spectrum distribution.

[0038] Based on the dynamic control instruction set, time-frequency inverse diffusion suppression operation is implemented. By injecting reverse phase suppression pulses into the interference frequency band and performing time-domain and frequency-domain boundary clipping, control signal energy convergence and disturbance suppression are achieved.

[0039] After inverse diffusion suppression, a limit value write-back process is performed. By identifying over-amplitude components and adjusting the control pulse amplitude to below the minimum effective threshold, the phase direction is consistent and the signal is continuous.

[0040] After the amplitude limiting write-back is completed, the interference self-suppression adjustment operation is performed. By injecting a low-amplitude wide-wave suppression signal, the hysteresis energy is released, and the control response threshold is dynamically adjusted to achieve energy dissipation and closed-loop stability of the control link.

[0041] The circuit breaker rigid control system based on load monitoring terminals includes a time base acquisition module, a playback identification module, a modeling and calculation module, a threshold correction module, and a dynamic control module.

[0042] The time base acquisition module acquires a unified nanosecond-level time baseline, continuously acquires current signals from multiple loops, reconstructs the complete phase trajectory of the current in each loop, and generates a corresponding low-frequency hysteresis fingerprint baseline as a reference for dynamic response correction.

[0043] The playback recognition module constructs a causal playback chain based on the low-frequency hysteresis fingerprint baseline, replays the current transition behavior during the rigid control process of the circuit breaker, identifies the nonlinear hysteresis section, and extracts the core parameters of threshold drift.

[0044] The modeling and calculation module uses drift core parameters to generate phase mapping relationships and residual spectra, calculates the energy coupling strength between loops, constructs threshold misalignment surfaces, and determines the delay time window boundaries of the control response.

[0045] The threshold correction module constructs a dual-track threshold structure combining fast and slow tracks under the constraint of the delay time window. It corrects the timing of control pulses by real-time tracking of hysteresis rhythm by fast track and solidifying baseline characteristics by slow track, combined with feedforward control field.

[0046] The dynamic control module generates a phase conjugate control instruction set under stable feedforward control field conditions, implements time-frequency inverse diffusion suppression, amplitude limiting write-back and interference self-suppression operations, and dissipates control energy accumulation online.

[0047] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0048] This invention, based on a unified nanosecond-level time baseline, comprehensively reconstructs the current phase trajectory and extracts low-frequency hysteresis features. On this basis, a causal playback chain is established to accurately identify nonlinear hysteresis regions and threshold drift patterns. Furthermore, a cross-loop energy coupling model and delay response boundary are constructed to achieve dual-track dynamic generation and precise correction of the control threshold. Combined with a phase conjugate instruction set constructed using a feedforward control field, it not only effectively suppresses high-frequency disturbances and response diffusion but also dissipates energy accumulation in the control chain through methods such as amplitude limiting write-back and interference self-suppression. This effectively avoids problems such as control mis-triggers, response hysteresis, and actuator half-drive, solving risks such as misjudgment, lock-up erosion, and bus overheating caused by filtering hysteresis in traditional control. Ultimately, a highly reliable rigid control system with closed-loop self-stabilization capability is constructed, significantly improving the safety, response speed, and intelligence level of multi-loop distribution networks. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0050] Figure 1 This is a flowchart of the circuit breaker rigid control method based on a load monitoring terminal according to the present invention.

[0051] Figure 2 This is a schematic diagram of the circuit breaker rigid control system based on a load monitoring terminal according to the present invention. Detailed Implementation

[0052] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0053] This invention provides, for example Figure 1 The circuit breaker rigid control method based on load monitoring terminal shown includes the following steps:

[0054] S1. Obtain a unified nanosecond-level time baseline. Under the constraint of this time baseline, continuously acquire the current signals of multiple loops, reconstruct the complete current phase trajectory of each loop, and generate a low-frequency hysteresis fingerprint baseline corresponding to the sampling hysteresis characteristics on this basis, which is used to establish the reference field required for subsequent dynamic response correction.

[0055] To achieve precise control of multiple current loops and address the dynamic lag issue caused by traditional low-frequency sampling structures, a unified nanosecond-level time baseline must first be established. Using this baseline as a constraint, continuous and precise acquisition and processing of the current signals from each loop are then performed to construct a reference data field for dynamic response correction. The entire process includes the following steps:

[0056] A unified nanosecond-level time baseline is established. This step involves embedding a high-precision clock source in the load monitoring terminal, combined with a temperature-compensated oscillator and a phase-locked loop circuit, to perform real-time self-calibration and frequency stabilization control of the local time signal. This clock source generates a time-series signal with nanosecond-level resolution and distributes it to the start-up trigger units of each current sampling channel via a high-fidelity differential signal link, ensuring that each channel starts data acquisition under the same time reference. To further eliminate microsecond-level offsets caused by differences in path length between channels, the system configures the drive signals of the sampling channels with delay compensation and adjusts the relative time offset based on measured feedback results, ultimately forming a sampling start-up mechanism with physical time alignment characteristics. The construction of this time baseline ensures that the current signal acquisition of all subsequent loops is performed within a unified clock framework, eliminating the phase aliasing and data misalignment problems caused by inconsistent sampling start points in traditional systems from the source.

[0057] Under a unified nanosecond-level time baseline constraint, continuous data acquisition is performed on multiple current loops. In this step, each current loop employs a high-speed precision sampling current transformer linked with a 24-bit high-resolution analog-to-digital converter chip. A parallel synchronous triggering mechanism enables parallel sampling at a unified time point. Each acquired signal is sampled at 5-microsecond intervals, continuously acquiring data for at least one complete power frequency cycle to ensure a complete record of the dynamic changes of the current signal across different time periods. Simultaneously, to ensure data accuracy, a bandpass filter circuit is introduced before analog-to-digital conversion. This circuit's passband covers the transition range from low frequencies to high frequencies, improving the response to rapidly changing components and reducing the suppression effect of conventional low-frequency filters on signal rising edges. After conversion, each sampled signal is immediately uploaded to the main control buffer and preliminarily synchronized based on its time tag for subsequent phase reconstruction processing.

[0058] Based on the completed data acquisition, the current phase trajectory of each loop is reconstructed. Using time tags obtained after unified time base calibration, combined with the aforementioned continuous sampling data, the system performs time-domain reconstruction and phase smoothing processing on each current signal. To ensure accurate representation of the phase trajectory, a sliding segment comparison mechanism is introduced during reconstruction. This involves extending a symmetrical segment of one cycle length forward and backward from each sampling point, and performing amplitude normalization and adjacent sampling difference operations on the data within this segment to construct a phase vector sequence representing the direction and velocity of current change. This vector sequence accurately reflects the relative displacement trend of the current waveform at each sampling point, and, combined with the amplitude change trend, further reconstructs the complete current phase trajectory. For loops with short-term fluctuations or high-frequency disturbances, increasing the window length and adjusting the weight distribution strategy effectively avoids phase jumps caused by local distortion, ensuring the continuity and traceability of the overall phase trajectory. The reconstructed phase trajectory will serve as the base dataset for subsequent hysteresis feature identification.

[0059] Based on the reconstructed phase trajectory, the response difference between each loop and its original sampled data is extracted, and a fingerprint baseline corresponding to the low-frequency hysteresis characteristics is constructed. This process extracts the fixed characteristic segment of the hysteresis response by comparing the time deviation between the original rising edge of each sampled data and its theoretical transition point exhibited in the reconstructed phase trajectory. To avoid systematic errors masking the hysteresis characteristics, each data point is compared over multiple periods, and its average offset value is taken as the basic offset vector. The hysteresis boundary region of the loop is constructed by combining the maximum and minimum offset values ​​in different periods. Subsequently, the system performs unified projection processing on the hysteresis boundaries of all sampled loops to establish a two-dimensional response mapping surface with time offset as the horizontal axis and loop identification as the vertical axis. Based on this, a representative low-frequency hysteresis fingerprint trajectory is extracted. This fingerprint trajectory has a comprehensive descriptive capability of three attributes: time-domain delay, amplitude response distortion, and phase drift. It can fully characterize the differences in dynamic response capabilities of different loops under a unified time base, and finally construct a reference field for subsequent current transition correction and response regulation.

[0060] S2, a causal replay chain is constructed based on the low-frequency hysteresis fingerprint baseline. This causal replay chain is used to replay the current transition behavior during the rigid control process of the circuit breaker, identify the key time segment that forms the nonlinear hysteresis loop, and extract the core threshold drift parameter that affects the accuracy of the circuit breaker action judgment.

[0061] Building upon the established low-frequency hysteresis fingerprint baseline, to accurately reproduce and trace the source of response deviations during the rigid control process of circuit breakers, a causal playback chain needs to be established. This chain will then be used to identify nonlinear hysteresis characteristic segments and extract the core threshold drift parameters that affect the accuracy of circuit breaker control judgments. The entire process includes the following steps:

[0062] A causal playback chain is constructed based on the acquired low-frequency hysteresis fingerprint baseline. This step uses sampled data aligned to a unified nanosecond-level time baseline from multiple loops as a foundation. The reconstructed current phase trajectory is compared one-to-one with the original sampled data to obtain the time offset between the actual and theoretical response timings of each loop in different control cycles. Based on this, a multi-time-axis synchronization comparison table is constructed. To ensure the accuracy of causal relationship reproduction, a periodic window slicing strategy is adopted during the construction process. Each current data segment is divided according to a complete power frequency cycle, and key feature positions such as transition points, waveform inflection points, and rise rate change points in each cycle are marked and mapped to the time axis. Based on the time axis mapping, a point-by-point alignment operation is performed by combining the issuance and execution time sequences of the control signal. Using a unified time base as a reference, the sampled data from multiple loops are organized into a behavioral chain sequence with sequential causal logic. This sequence can completely reproduce the entire process from control command triggering to response feedback, providing full-scale time-domain data support for subsequent backtracking of current transition behavior.

[0063] In the constructed causal playback chain, the current transition behavior during the rigid control process of the circuit breaker is retrospectively replayed. This step starts from the time point when the control command is issued and unfolds a playback segment of no less than two complete power frequency cycles, extracting all current transition events within this segment. Each transition event includes detailed information such as the transition start time, duration, waveform change amplitude, phase shift direction and amplitude, and the corresponding control command number and channel number. During the playback process, by comparing the differences between the actual waveform change path and the ideal control response model cycle by cycle, various response characteristics in the actual response, such as delayed response, high-frequency oscillation, amplitude rebound, and slow slope change, are identified, further modeling the complete dynamic process of transition behavior formation. To ensure the coherence and authenticity of the playback, after the transition event of each circuit is identified, its waveform behavior in the same time window needs to be cross-compared with that of adjacent circuits to determine whether there is cross-channel interference or energy coupling relationship, thus adding cross-influence factors to the behavior playback to make it closer to the actual operation process.

[0064] Based on the transition behavior sequence obtained from backtracking replay, the key time segments forming nonlinear hysteresis loops are identified. Due to non-ideal factors such as asynchrony, disturbances, and boundary triggering during multi-loop control, certain current waveforms may exhibit hysteresis offsets and phase distortions during transitions, leading to dynamic hysteresis behavior in the sampling-judgment-execution closed-loop control. To identify these behaviors, this step introduces an error accumulation trajectory analysis mechanism during replay. By superimposing the error offsets between the judgment threshold and the actual trigger point in each transition event, a time continuity error curve is constructed, and the start and end segments where each judgment offset exceeds a preset tolerance threshold are marked. When the error offsets of multiple consecutive sampling points within a segment show a consistent cumulative trend, and this trend occurs synchronously in three or more channels, the time segment can be identified as a key area for hysteresis loop formation. For the identified key segments, their starting response point, hysteresis peak value, response time, and peak-valley amplitude need to be further marked, and a causal logic mapping of the hysteresis formation process is established by combining this with the corresponding control command sequence in the replay chain.

[0065] Within the identified critical time intervals of nonlinear hysteresis, core threshold drift parameters affecting the accuracy of circuit breaker action judgment are extracted. This step involves detailed modeling of the offset trajectory between the actual trigger point and the target threshold position within the hysteresis interval, extracting three types of key parameters: first, periodic offset trend parameters, used to describe the periodic pattern of continuous trigger point offset under multiple similar control scenarios; second, instantaneous amplitude disturbance parameters, used to measure the probability of instantaneous misjudgment caused by high-frequency fluctuations; and third, cross-channel coupling response parameters, used to identify the synchronicity and coupling strength of response offsets between different channels. During the extraction process, each type of parameter needs to be matched one-to-one with the original sampled data and the actual control path in the playback chain, and multi-cycle statistical analysis is performed to eliminate deviations caused by occasional disturbances. The final set of core parameters will serve as the basic input for subsequent threshold judgment optimization, control timing correction, and control stability enhancement, providing data support and logical basis for the entire rigid control strategy.

[0066] S3. Generate multi-loop phase mapping relationship and phase residual spectrum based on the extracted threshold drift core parameters, calculate the energy coupling strength of current signal between loops, construct threshold judgment misalignment surface on this basis, and determine the time window boundary of control response delay.

[0067] To further improve the judgment accuracy and response consistency during the rigid control process of circuit breakers, it is necessary to construct the phase mapping relationship and residual spectrum between multiple circuits based on the extracted core parameters of threshold drift, and to perform quantitative analysis on the coupling energy between current signals. Finally, a threshold judgment misalignment surface and time window boundary are established to form accurate and stable response domain constraints. This process includes the following implementation steps:

[0068] Based on the extracted threshold drift core parameters, a phase mapping relationship between multi-loop current signals is constructed. This step uses the phase trajectory data of each loop in the hysteresis section as the basic input, and performs curve fitting and normalization on the phase evolution process of each current in each key control cycle to ensure that all data have the same reference benchmark. On this basis, a dual-loop pairing mapping table is constructed to correspond the phase change trends of any two loops in the same time period, forming a preliminary mapping comparison relationship. To enhance the dynamic stability of this mapping relationship, this step introduces a multi-cycle translation window method to perform a lateral sliding comparison of the phase response trajectories in adjacent cycles and calculate their synchronization offset value and phase fitting overlap, thereby identifying the relative response synchronization characteristics between loops in different time periods. Finally, by integrating and consolidating the mapping results of all loop combinations, a three-dimensional phase response mapping surface is formed with the time coordinate and loop number as the reference axis and the phase synchronization coefficient as the value range. This mapping surface will serve as the basic reference structure for subsequent energy analysis.

[0069] Based on the phase mapping relationship of multiple loops, a phase residual spectrum is constructed. This step aims to further characterize the fine-grained phase error characteristics between each loop to identify high-frequency residual responses and control error concentration points in current transition events. Specifically, point-to-point differencing is first performed on the actual phase trajectory of each loop within the control period and the expected phase curve in the mapping surface to obtain a complete residual time series. To extract high-frequency components and periodic disturbance characteristics from the residual, the rapid amplitude change rate and peak position change rate within the sliding segment are used as evaluation indicators. The residual series is segmented into spectral lines and marked with fluctuation frequencies. The amplitude deviation of all identifiable frequency bands is classified according to their corresponding frequency intervals, generating a phase residual spectrum with temporal locality and frequency distribution characteristics. This spectrum clearly characterizes the non-ideal phase behavior of each loop and the loops themselves during the response process, and can serve as an input indicator set for energy coupling analysis.

[0070] The energy coupling strength between current loops is calculated using phase mapping relationships and phase residual spectra. In this step, the phase synchronization coefficient, residual amplitude density, and current transition duration of each loop pair within the control window are used as the core dimensions for energy coupling calculation. A multi-dimensional time coupling matrix is ​​constructed to quantify the energy transfer probability on each coupling path. During the calculation, to eliminate occasional interference caused by instantaneous fluctuations, this method uses the minimum period continuous response segment as the calculation window to ensure that each coupling strength is based on stable current transition behavior. Subsequently, by performing regional clustering on the coupling matrix, abrupt coupling strength change points and stable channel regions are identified, and representative coupling pairs are extracted to construct the boundary constraints of the subsequent threshold judgment misalignment model. This coupling strength data not only reveals the fundamental path of mutual interference between loops but also provides a key data foundation for channel-specific coordination in control strategies.

[0071] Based on the analysis results of energy coupling strength and phase residuals, a threshold judgment misalignment surface is constructed, and the delay time window boundary of the control response is determined accordingly. This step uses the previously obtained coupling strength matrix as the coordinate basis, and the hysteresis response point of each loop as the height variable to construct a complete misalignment surface structure in three-dimensional space. To enhance the resolution of the misalignment surface, this method interpolates between adjacent loops to construct intermediate response surfaces, and uses the amplitude change of the corresponding frequency band in the phase residual spectrum as the surface deformation factor to fine-tune the fitting of local areas, thereby generating a continuous surface graphic that can truly reflect the judgment delay trend and error concentration area. On this misalignment surface, based on the contour distribution and the location of peaks and troughs, the dynamic boundary of the judgment area is set, and the optimal judgment interval for each loop in different time stages is extracted. This is then used as the basis to calibrate the time window of the allowable range of the control response. Finally, this time window boundary will be used as a dynamic constraint condition in the subsequent control decision-making process to ensure that the control pulse trigger point is within the high-confidence response area, improving the accuracy and consistency of the circuit breaker action judgment.

[0072] S4. Under the constraint of the delay time window boundary, a dual-track threshold generation structure containing fast track and slow track is constructed. The fast track is used to track the hysteresis rhythm in real time and quickly correct the threshold. The slow track is used to extract and solidify the sampling baseline features. Based on the control value output by the dual track, the output timing of the control pulse is precisely corrected by combining the feedforward control field.

[0073] Based on the previously constructed threshold judgment misalignment surface and control response delay time window boundary, in order to achieve dynamic adaptation and precise correction of the control pulse output timing, a dual-track threshold generation structure consisting of a fast track and a slow track needs to be constructed, and output adjustment is performed in conjunction with a feedforward control field. This implementation process includes the following steps:

[0074] Under the established time delay window boundary constraints, a fast-track threshold generation structure is constructed. This step extracts key decision nodes in the high-error gradient region based on the misaligned surface formed in the previous stage, and establishes a fast-response decision framework around these nodes. Specifically, the fast-track threshold structure uses the current change rate, current phase shift velocity, and the density of high-frequency components in the residual spectrum within the current sampling period as input variables to perform rapid dynamic analysis of the current signal in the current period. Based on this, by constructing a continuous time-series sliding window, leading factors reflecting hysteresis trend changes are extracted in real time, and these factors are quickly matched with the actual error change curves in historical periods, thereby generating a corrected threshold suitable for the current response conditions within microseconds. The core of the fast-track generation structure lies in capturing the dynamic fluctuations of the hysteresis rhythm, enabling real-time judgment and adjustment of response drift caused by sudden phase transitions, current fluctuations, or external disturbances, allowing the threshold in each control period to respond and correct rapidly according to real-time changes in the current state.

[0075] While the fast track is running, a slow track threshold generation structure is constructed. This step selects multiple continuous sampling windows with minimal cross-cycle error fluctuations from the stable hysteresis response segment extracted in the previous stage as the basis for slow track baseline generation. By performing multi-cycle superposition analysis on the phase response curves within these windows, representative steady-state response patterns are extracted, and a normalized baseline threshold curve is formed based on this. This baseline curve can be used to indicate the natural response trend of the loop current signal under conditions without high-frequency disturbances. To ensure the slow track output has long-term reference value, its baseline data needs to be updated periodically, and its deviation compared with the sampling data of the current cycle. When a long-term continuous offset or trend drift occurs, the slow track baseline is readjusted. In the dual-track structure, the slow track provides stability threshold support, ensuring a reliable fallback benchmark for the fast track during high-frequency adjustments and preventing system oscillations caused by excessive fast track adjustments. The outputs of the fast and slow tracks will participate in the final threshold generation in a collaborative manner, with the fast track playing a dominant role and the slow track providing constraint boundaries and long-term trend control.

[0076] Based on the dynamic threshold generated by the dual-track structure of fast and slow tracks, an output timing correction mechanism for control pulses is constructed. This step uses the time window boundary established in the previous stage as the reference boundary range for control timing adjustment, and performs precise correction within this range based on the time difference between the current control point and the optimal trigger point on the misaligned surface. Specifically, the dual-track fusion threshold is first used as the judgment standard to compare the current current state against the threshold to determine if the action conditions are met. If met, the control pulse is not triggered immediately. Instead, based on the preset time response model in the feedforward control field, the error between the current time point and the ideal trigger point is used as the correction amount to generate an adaptive delay compensation duration. This compensation duration guides the specific trigger time of the control pulse, preventing it from triggering in the error concentration area and shifting it to the optimal response area. To avoid action lag caused by delay compensation, this step sets a minimum action response window. When the expected correction value exceeds this window tolerance, the compensation cycle is automatically shortened, prioritizing the timeliness and reliability of the circuit breaker's action response.

[0077] After the output timing correction is completed, the feedforward control field is linked and matched with the dual-track fusion threshold to complete the final output adjustment of the control pulse. The feedforward control field in this step originates from the control command and response feedback of the previous cycle, as well as the high-frequency disturbance distribution of the current signal in the current cycle, and generates a desired response curve for a future time period through a weighted superposition mechanism. In the final output stage, this desired response curve is compared with the correction result generated by the dual-track fusion threshold to calculate the time offset and phase matching degree between the two. When the matching degree reaches the set threshold, a control pulse is immediately issued to complete the rigid action of the circuit breaker; if the matching degree is insufficient, a fine calibration mode is entered, continuously adjusting the trigger point position within a limited period until the action threshold condition is reached. After the action output is completed, the correction parameters of the current cycle are injected back into the feedforward control field to update the response prediction template for the next cycle, thereby achieving closed-loop linkage between the dual-track structure, the feedforward mechanism, and the pulse output. This ensures a dynamic balance between real-time performance and stability in circuit breaker control, minimizing the impact of lag.

[0078] S5, under the stable operation of the feedforward control field, generates a dynamic control instruction set containing phase conjugate instructions. Through the control instruction set, time-frequency inverse diffusion suppression, amplitude limit write-back and interference self-suppression adjustment operations are implemented to dissipate the control energy accumulation caused by lag online, realize the dynamic unlocking of the control link and the relief of contact temperature rise, and construct a stable closed-loop circuit breaker rigid control system.

[0079] Building upon the stable operation of the completed dual-track threshold generation structure and feedforward control field, to achieve dynamic release of accumulated energy in the control link and effective suppression of contact thermal stress, a dynamic control instruction set incorporating phase conjugation characteristics needs to be constructed. This instruction set will then be used to perform multiple interference suppression in the frequency and time domains, control signal limiting and callback, and energy dissipation adjustment operations, ultimately achieving closed-loop stability of the circuit breaker's rigid control system. This implementation process includes the following steps:

[0080] Under the condition that the feedforward control field is in a stable operating state, a dynamic control command set containing phase conjugate commands is generated. This step uses the correction results of the dual threshold outputs of the fast and slow tracks from the previous step as input signals, and combines them with the current phase response trajectory and residual spectrum distribution of the current cycle to construct a control command generation space with dual reference dimensions of time and phase axes. In this space, starting from the action trigger point within the current cycle, the angle between the current phase direction and the control signal vector in its adjacent sampling segments is analyzed point by point. Based on the angle direction, a set of phase-symmetric command sequences is constructed in reverse, ensuring that it forms a precise phase conjugate relationship with the original action signal in future cycles. To improve the convergence rate and response consistency of this phase conjugate command, the command set needs to be dynamically adjusted based on the predicted disturbance boundaries in the feedforward control field. Its amplitude is set to the minimum effective range that just drives the actuator to complete the action, preventing excessive energy injection that leads to energy accumulation in the control chain.

[0081] Based on the generated phase conjugate dynamic control command set, a time-frequency back-diffusion suppression operation is implemented. This step focuses on the frequency domain disturbance characteristics within the current cycle of the circuit breaker. The current signal is divided into equally spaced segments on the frequency axis, and the energy peak position, duration, and energy accumulation rate in each frequency band are statistically analyzed to identify high energy density regions and the main disturbance frequency band. After identification, the phase conjugate command set is weighted and modulated according to the frequency distribution, injecting a suppressive pulse with the opposite phase into the interference frequency band, forming a back-diffusion effect in the frequency domain, thereby achieving the purpose of interference cancellation. In this process, to ensure that the phase control command does not accidentally damage the main signal path, each control pulse needs to be trimmed in both the time and frequency domains simultaneously, so that its response frequency is within the control frequency band and its time domain duration is controlled within the safe threshold of the response period. This operation ensures the energy convergence and interference suppression capability of the control signal during execution, significantly reducing the instability factors in the control chain caused by hysteresis diffusion.

[0082] After completing the anti-diffusion suppression, the amplitude output of the control signal is subjected to amplitude limiting and write-back processing to suppress the over-excited response behavior in the hysteresis section. In this step, through the linkage analysis of the feedforward control field and the phase residual spectrum, the over-amplitude component of the control pulse within the response period is identified, and the amplitude change curve is differentiated to extract the energy change trend of the fast rise segment and the overshoot segment. Subsequently, based on each pulse unit in the dynamic control instruction set, its actual energy transfer efficiency on the response path is calculated, and the part exceeding the set energy upper limit is subjected to amplitude write-back processing, that is, the amplitude of the control pulse is adjusted to below the minimum effective threshold upper limit without affecting the completion of the action. During the write-back process, the rising edge characteristics and phase direction of the pulse must be preserved to prevent phase shift distortion caused by amplitude reduction. At the same time, a linear decreasing edge processing method is adopted to alleviate the discontinuity effect caused by amplitude adjustment, ensuring the continuity of the output signal in the time domain and the response stability of the actuator, thereby further avoiding the accumulation of thermal stress at the contacts caused by frequent high-energy drives.

[0083] After the amplitude limit adjustment is completed, an interference self-suppression adjustment operation is performed to achieve online dissipation of hysteresis energy in the control link and dynamic unlocking of the closed loop. In this step, the current response behavior of each loop is continuously monitored within the subsequent cycle, and its timing, amplitude, and direction are dynamically correlated with the control pulse of the previous cycle to construct an energy accumulation trend graph. When a segment in the graph shows a continuous upward trend and fails to fall back to the steady-state threshold, it is identified as an interference energy accumulation region. For such regions, this step uses a short-cycle, wide-wave, low-amplitude suppressive signal for gradual intervention. This signal has the characteristics of opposite direction, longer duration, and lower frequency compared to the original control pulse, which can effectively guide the actuator to slowly release from the high-excitation state, reducing mechanical load and electromagnetic stress. During the interference self-suppression process, the control response threshold within each cycle is also dynamically adjusted, with the threshold adjusted in real time according to the energy release progress to prevent malfunctions caused by the control chain still being in a semi-locked state. In this way, the energy caused by hysteresis no longer accumulates in the execution chain, but is gradually released and dissipated in the stable channel, ultimately unlocking the entire control link and reducing the thermal load on the contacts, forming a stable closed-loop rigid control state.

[0084] This invention, based on a unified nanosecond-level time baseline, comprehensively reconstructs the current phase trajectory and extracts low-frequency hysteresis features. On this basis, a causal playback chain is established to accurately identify nonlinear hysteresis regions and threshold drift patterns. Furthermore, a cross-loop energy coupling model and delay response boundary are constructed to achieve dual-track dynamic generation and precise correction of the control threshold. Combined with a phase conjugate instruction set constructed using a feedforward control field, it not only effectively suppresses high-frequency disturbances and response diffusion but also dissipates energy accumulation in the control chain through methods such as amplitude limiting write-back and interference self-suppression. This effectively avoids problems such as control mis-triggers, response hysteresis, and actuator half-drive, solving risks such as misjudgment, lock-up erosion, and bus overheating caused by filtering hysteresis in traditional control. Ultimately, a highly reliable rigid control system with closed-loop self-stabilization capability is constructed, significantly improving the safety, response speed, and intelligence level of multi-loop distribution networks.

[0085] This invention provides, for example Figure 2 The circuit breaker rigid control system based on a load monitoring terminal shown includes a time base acquisition module, a playback identification module, a modeling and calculation module, a threshold correction module, and a dynamic control module.

[0086] The time base acquisition module acquires a unified nanosecond-level time baseline, continuously acquires current signals from multiple loops, reconstructs the complete phase trajectory of the current in each loop, and generates a corresponding low-frequency hysteresis fingerprint baseline as a reference for dynamic response correction.

[0087] The playback recognition module constructs a causal playback chain based on the low-frequency hysteresis fingerprint baseline, replays the current transition behavior during the rigid control process of the circuit breaker, identifies the nonlinear hysteresis section, and extracts the core parameters of threshold drift.

[0088] The modeling and calculation module uses drift core parameters to generate phase mapping relationships and residual spectra, calculates the energy coupling strength between loops, constructs threshold misalignment surfaces, and determines the delay time window boundaries of the control response.

[0089] The threshold correction module constructs a dual-track threshold structure combining fast and slow tracks under the constraint of the delay time window. It corrects the timing of control pulses by real-time tracking of hysteresis rhythm by fast track and solidifying baseline characteristics by slow track, combined with feedforward control field.

[0090] The dynamic control module generates a phase conjugate control instruction set under stable feedforward control field conditions, implements time-frequency inverse diffusion suppression, amplitude limiting write-back and interference self-suppression operations, dissipates control energy accumulation online, realizes dynamic unlocking and temperature rise mitigation of the control chain, and constructs a closed-loop stable rigid control system.

[0091] The circuit breaker rigid control method based on load monitoring terminal provided in this embodiment of the invention is implemented through the above-mentioned circuit breaker rigid control system based on load monitoring terminal. For details of the specific method and process of the circuit breaker rigid control system based on load monitoring terminal, please refer to the embodiment of the circuit breaker rigid control method based on load monitoring terminal, which will not be repeated here.

[0092] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for rigid control of circuit breakers based on load monitoring terminals, characterized in that, Includes the following steps: S1. Obtain a unified nanosecond-level time baseline, continuously acquire current signals from multiple loops, reconstruct the complete phase trajectory of the current in each loop, and generate the corresponding low-frequency hysteresis fingerprint baseline as a reference for dynamic response correction. S2, based on the low-frequency hysteresis fingerprint baseline, constructs a causal replay chain to replay the current transition behavior during the rigid control process of the circuit breaker, identifies the nonlinear hysteresis section, and extracts the core parameters of threshold drift. S3, using the drift core parameters to generate phase mapping relationship and residual spectrum, calculate the energy coupling strength between loops, construct threshold misalignment surface and determine the delay time window boundary of control response; S4, under the constraint of the delay time window, construct a dual-track threshold structure combining fast track and slow track, and correct the timing of control pulses by real-time tracking of hysteresis rhythm by fast track and solidification of baseline characteristics by slow track, combined with feedforward control field. S5 generates a phase conjugate control instruction set under stable feedforward control field conditions, implements time-frequency inverse diffusion suppression, amplitude limiting write-back and interference self-suppression operations, and dissipates control energy accumulation online.

2. The circuit breaker rigid control method based on a load monitoring terminal according to claim 1, characterized in that, Step S1 includes: A unified nanosecond-level time baseline is obtained. A nanosecond-level time sequence signal is generated through a high-precision clock source, a temperature-compensated oscillator, and a phase-locked loop circuit. The signal is then distributed to multiple current sampling channels and configured with delay compensation to achieve time alignment. Under the constraint of a unified nanosecond-level time baseline, the current signals of multiple current loops are continuously acquired. Each loop uses a high-resolution analog-to-digital converter chip and a bandpass filter circuit. The acquisition results are uploaded to the main control buffer through time tags and synchronized. Based on the continuous sampling data after synchronization and processing, the complete phase trajectory of each current loop is reconstructed through sliding segment comparison and adjacent differential operation. The window length and weight distribution are adjusted for high-frequency disturbances to ensure the continuity of the phase trajectory. Based on the reconstructed phase trajectory, by comparing the time offset between the actual rising edge and the theoretical transition point, hysteresis response features are extracted and a two-dimensional response mapping surface is established to generate a low-frequency hysteresis fingerprint trajectory.

3. The circuit breaker rigid control method based on a load monitoring terminal according to claim 1, characterized in that, Step S2 includes: Based on the low-frequency hysteresis fingerprint baseline, a causal playback chain of multiple loops aligned with a unified nanosecond-level time baseline is constructed to obtain the time offset relationship between the current phase trajectory and the sampled data, and to establish a multi-time axis synchronization reference table. In the causal replay chain, current transition events within the replay segment are extracted around the time point of the control command issuance, delayed response, frequency oscillation, amplitude rebound and waveform changes are identified, and behavioral dynamic modeling is performed. Based on the transition behavior modeling results, an error accumulation trajectory analysis mechanism is introduced to construct error curves, identify key time segments of hysteresis in multiple channels where unidirectional cumulative offset occurs, and label key response feature information. Within the critical time interval of hysteresis, periodic offset trend parameters, instantaneous amplitude disturbance parameters, and cross-channel coupling response parameters are extracted, and control path matching and multi-period statistical analysis are performed to form a core parameter set for threshold drift.

4. The circuit breaker rigid control method based on a load monitoring terminal according to claim 3, characterized in that, The extraction of the core parameter set for threshold drift further includes: performing trend fitting on periodic offset trend parameters, performing amplitude fluctuation statistics on instantaneous amplitude disturbance parameters, and determining the inter-channel phase offset synchronization of cross-channel coupling response parameters, so as to improve the dynamic correction accuracy of threshold judgment.

5. The circuit breaker rigid control method based on a load monitoring terminal according to claim 1, characterized in that, Step S3 includes: Based on the threshold drift core parameters, a phase mapping relationship between multi-loop current signals is constructed. The phase response trajectory is compared by sliding through a multi-cycle translation window to form a phase response mapping surface with time coordinates and loop number as reference axes. Based on the phase mapping relationship, a phase residual spectrum is constructed. By performing differential operations on the actual phase trajectory and the expected phase curve, a phase residual spectrum with time locality and frequency distribution characteristics is generated. The energy coupling strength between current loops is calculated using phase mapping relationship and phase residual spectrum. By constructing a multidimensional time coupling matrix, abrupt points of coupling strength change are identified and representative coupling relationship pairs are extracted. Based on the analysis results of energy coupling strength and phase residual, a threshold judgment misalignment surface is constructed. The control response delay time window boundary is determined by surface fitting and spectral amplitude deformation, which is used for subsequent action judgment constraints.

6. The circuit breaker rigid control method based on a load monitoring terminal according to claim 5, characterized in that, The threshold judgment misaligned surface constructs an intermediate response surface by interpolating between adjacent loops, and performs local region fitting by combining the amplitude changes of the corresponding frequency band in the phase residual spectrum, so that the misaligned surface is continuous and has dynamic response characteristics.

7. The circuit breaker rigid control method based on a load monitoring terminal according to claim 1, characterized in that, Step S4 includes: Under the constraint of the delay time window boundary, a fast track threshold generation structure is constructed, and a fast response correction threshold is generated based on the current cycle current change rate, phase offset velocity and high frequency component density in the residual spectrum. While the fast track is running, a slow track threshold generation structure is constructed. Based on the sampling window with the smallest cross-cycle error fluctuation, a baseline threshold curve is generated as a steady-state response trend reference, and a fast and slow track coordinated threshold output is formed. Based on the dynamic threshold of dual-track coordinated output, combined with the time response model in the delay time window and the feedforward control field, the error between the current control point and the optimal trigger point is calculated, and the control pulse output correction timing is generated. The desired response curve generated by the feedforward control field is matched with the dual-track output results. The timing of the control pulse trigger is determined based on the matching degree, and the correction parameters are fed back to update the subsequent response prediction template.

8. The circuit breaker rigid control method based on a load monitoring terminal according to claim 7, characterized in that, The fast-track threshold generation structure further dynamically adjusts the sliding window length based on the density of high-frequency components in the residual spectrum to enhance the real-time tracking capability of current transition response, and prioritizes fast threshold correction when the error exceeds the set threshold.

9. The circuit breaker rigid control method based on a load monitoring terminal according to claim 1, characterized in that, Step S5 includes: Under stable operation conditions of the feedforward control field, a dynamic control instruction set containing phase conjugate commands is generated. The fast track and slow track threshold outputs are used as input signals. The control command generation space with time and phase dual references is constructed by combining the current phase response trajectory and residual spectrum distribution. Based on the dynamic control instruction set, time-frequency inverse diffusion suppression operation is performed by injecting reverse phase suppression pulses into the interference frequency band and clipping the time and frequency domain boundaries. After inverse diffusion suppression, a limit value write-back process is performed. By identifying over-amplitude components and adjusting the control pulse amplitude to below the minimum effective threshold, the phase direction is consistent and the signal is continuous. After the amplitude limiting write-back is completed, an interference self-suppression adjustment operation is performed. By injecting a low-amplitude wide-wave suppression signal, the hysteresis energy is released, and the control response threshold is dynamically adjusted.

10. A circuit breaker rigid control system based on a load monitoring terminal, used to implement the circuit breaker rigid control method based on a load monitoring terminal as described in any one of claims 1-9, characterized in that, It includes a time-base acquisition module, a playback recognition module, a modeling and calculation module, a threshold correction module, and a dynamic control module: The time base acquisition module acquires a unified nanosecond-level time baseline, continuously acquires current signals from multiple loops, reconstructs the complete phase trajectory of the current in each loop, and generates a corresponding low-frequency hysteresis fingerprint baseline as a reference for dynamic response correction. The playback recognition module constructs a causal playback chain based on the low-frequency hysteresis fingerprint baseline, replays the current transition behavior during the rigid control process of the circuit breaker, identifies the nonlinear hysteresis section, and extracts the core parameters of threshold drift. The modeling and calculation module uses drift core parameters to generate phase mapping relationships and residual spectra, calculates the energy coupling strength between loops, constructs threshold misalignment surfaces, and determines the delay time window boundaries of the control response. The threshold correction module constructs a dual-track threshold structure combining fast and slow tracks under the constraint of the delay time window. It corrects the timing of control pulses by real-time tracking of hysteresis rhythm by fast track and solidifying baseline characteristics by slow track, combined with feedforward control field. The dynamic control module generates a phase conjugate control instruction set under stable feedforward control field conditions, implements time-frequency inverse diffusion suppression, amplitude limiting write-back and interference self-suppression operations, and dissipates control energy accumulation online.

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