Electrical digital data processing system in pole switching task planning

Abstract

This invention relates to the field of electrical digital data processing technology and discloses an electrical digital data processing system for pole-switching task planning, comprising: a transient response acquisition module for capturing real-time current response waveform data of a nonlinear time-varying load after receiving a power pulse injection; a complex impedance damping decoupling module for locking the zero-input response time window after the power pulse injection ends based on the data and extracting time-domain attenuation characteristics to calculate the attenuation slope index; and a power spectrum scheduling module for constructing a load dynamic impedance model based on the attenuation slope index and generating power modulation control commands accordingly. This invention decouples the complex impedance damping characteristics of the load by identifying the transient attenuation slope, achieving accurate prediction and frequency compensation for overdamped high-energy-consumption states under nonlinear time-varying load conditions, effectively avoiding power deadlock in the execution loop, and improving the system's energy scheduling efficiency and dynamic response stability.

Description

Technical Field

[0001] This invention relates to the field of electrical digital data processing technology, and more specifically, to an electrical digital data processing system for pole switching task planning. Background Technology

[0002] In current high-energy-consuming industrial production processes such as aluminum electrolysis, electrode switching is a crucial step in maintaining the thermal balance and electrochemical stability of the electrolytic cell. Essentially, it involves an electro-digital control system driving an actuator to apply pulse energy to the electrolyte crust—a specific load—to achieve physical breakage. Existing electro-digital data processing systems typically employ linear control logic based on a steady-state feedback mechanism when planning such tasks. The system collects the amplitude of the current or pressure signal fed back by the actuator in real time. The logic unit compares this amplitude with a preset impedance threshold, thereby adjusting the intensity or duration of the pulse output from the power module. This feedback control mode, based on a single scalar characteristic, can effectively overcome load impedance and ensure operational continuity when the electrolyte is in a homogeneous and brittle state by increasing pulse energy. However, with increasing demands for energy efficiency control and refined equipment management in industrial settings, the limitations of existing technologies in handling complex, non-steady-state conditions are becoming increasingly apparent. This is especially true when the electrolyte exhibits rheological characteristics due to temperature fluctuations or uneven alumina concentration distribution, where traditional control logic faces a severe challenge of missing dimensions.

[0003] In practical applications, when the electrolyte crust is in a highly viscoelastic state, its transient response to external impacts often exhibits a high degree of similarity in signal amplitude to that of a high-hardness brittle crust. This makes peak-detection-based data processing models unable to effectively distinguish between these two distinct physical properties on a single energy dimension. Under such aliased conditions, if the system adopts a conventional linear gain strategy and continuously increases the pulse intensity command value based solely on the high impedance characteristics of the feedback signal, it will not only fail to utilize the brittle fracture mechanism to break the load, but will also absorb a large amount of pulse energy due to the viscous damping effect of the medium. This will cause the output power of the power module to be converted into ineffective heat dissipation. This mismatch between parameters and operating conditions can lead to the actuator falling into a logic deadlock, failing to complete the intended task even under high energy consumption output conditions, and consequently causing systemic risks such as power supply unit overload or bus communication congestion. Research and analysis indicate that existing technologies attempting to increase the physical channel of the feedback signal to optimize the control logic have not yet broken through the limitations of discrete logic. The system suffers from several limitations. For example, Chinese invention patent CN105543897B discloses a method for controlling the shell breaking of electrolytic aluminum. Although this solution introduces a dual feedback mechanism of voltage and pneumatic pressure sensors, using the electrolyte voltage feedback signal to determine whether the hammer head is in contact with the liquid surface and the exhaust pressure feedback signal to monitor the cylinder's action status, and thus executes the secondary strike logic, an analysis of this technical solution reveals that the core logic is still based on fixed threshold switching control. The method can only determine the degree of action completion based on whether the voltage is normal or whether the air pressure is present, and cannot deeply analyze the dynamic waveform at the moment of load contact. When facing highly viscoelastic rheological media, even if the sensor feedback voltage signal is within the normal range, the internal damping characteristics of the load, such as the viscosity coefficient, may be changing rapidly. This type of steady-state threshold control logic cannot perceive the microscopic physical fact that energy is absorbed by the medium, making it difficult to generate a targeted frequency conversion compensation strategy. As a result, the system still faces the dilemma of low execution efficiency and energy waste when facing nonlinear loads.

[0004] Therefore, the technical problem to be solved by this invention is how to construct an electrical digital data processing mechanism with multi-dimensional feature analysis capability, accurately decouple the viscoelastic properties of the load by extracting the time-domain damping features in the feedback signal, and thereby realize the adaptive orthogonal switching of control parameters in the pulse intensity and frequency dimensions to avoid ineffective energy delivery and resource deadlock. Summary of the Invention

[0005] This invention provides an electrical digital data processing system for pole-switching task planning, the system comprising:

[0006] The transient response acquisition module, coupled to the feedback end of the pulse power execution loop, is used to capture the real-time current response waveform data of the nonlinear time-varying load after receiving a power pulse injection at a high-frequency sampling rate.

[0007] The complex impedance damping decoupling module is connected to the transient response acquisition module. Based on the real-time current response waveform data, it locks the zero-input response time window after the power pulse injection ends, and extracts the time-domain attenuation characteristics of the signal envelope within the time window. Then, it calculates the attenuation slope index that characterizes the complex impedance damping characteristics of the nonlinear time-varying load.

[0008] The power spectrum scheduling module, connected to the complex impedance damping decoupling module, constructs a dynamic impedance model of the nonlinear time-varying load based on the attenuation slope index, and generates a power modulation control command for the next operating cycle of the pulse power execution circuit accordingly. The complex impedance damping decoupling module defines the starting boundary of the zero-input response time window by identifying the zero-crossing moments of the real-time current response waveform data, and performs a first-order differential operation on the signal amplitude within this time window to quantify the attenuation slope index. When the power spectrum scheduling module detects that the attenuation slope index is lower than a preset critical damping threshold, it determines that the current load circuit is in an overdamped, high-energy-consumption state, and generates a power modulation control command containing frequency conversion drive parameters to drive the power supply unit to dynamically adjust the frequency characteristics of the output energy, thereby preventing power delivery deadlock in the pulse power execution circuit under high-damping load environments.

[0009] Preferably, the complex impedance damping decoupling module includes: an instantaneous envelope calculation unit, configured to receive a discrete current sequence within a zero-input response time window, and extract the analytical signal magnitude of the discrete current sequence using a Hilbert transform algorithm to construct an instantaneous amplitude envelope; a differential evolution calculation unit, connected to the instantaneous envelope calculation unit, configured to perform a discrete-time first-order differential operation on the instantaneous amplitude envelope to obtain an instantaneous attenuation rate sequence reflecting the energy dissipation rate of the load circuit; and a feature weighted aggregation unit, connected to the differential evolution calculation unit, configured to perform an average processing on the instantaneous attenuation rate sequence based on time window weights, and output a single numerical attenuation slope index as a normalized quantization basis characterizing the rheological impedance properties of the load medium.

[0010] Preferably, the power spectrum scheduling module includes: an impedance spectrum mapping unit, which stores a preset load impedance characteristic lookup table to map the attenuation slope index to the corresponding load equivalent stiffness level and load equivalent viscosity level; and a modulation command synthesis unit, which is connected to the impedance spectrum mapping unit and is configured to determine the pulse amplitude modulation parameters based on the load equivalent stiffness level, determine the pulse frequency modulation parameters based on the load equivalent viscosity level, and perform time-domain superposition of the pulse amplitude modulation parameters and the pulse frequency modulation parameters to generate a power modulation control command.

[0011] Preferably, the modulation instruction synthesis unit incorporates a mathematical formula for quantizing and calculating the pulse frequency compensation amount: Where Δf is the frequency compensation amount to be superimposed on the base power pulse frequency, and K is the preset frequency response gain coefficient. This is a preset reference attenuation slope corresponding to the base underdamped load. The measured attenuation slope index is the output of the feature-weighted aggregation unit; in actual control loop operation, the mathematical formula... The difference term precisely defines the deviation of the energy dissipation rate between the current measured operating condition and the ideal reference underdamped state; when the system detects that the load medium has entered an overdamped high-energy-dissipation state, due to the large amount of energy absorbed by the internal dissipation of the medium, the measured attenuation slope index... The value of decreases significantly, which in turn leads to the difference term The corresponding increase drives the calculated frequency compensation amount. It exhibits a linear increasing trend and is ultimately superimposed on the base pulse frequency to increase the output frequency; at the parameter linkage level, in order to meet the nonlinear control requirement of nonlinearly increasing the pulse frequency based on the reciprocal relationship of the attenuation slope as stated in the specification, the frequency response gain coefficient... The control chip is dynamically configured to match the measured attenuation slope index. The function related to the current value, i.e. ,in As a constant gain reference; by using the coefficients of variables containing reciprocal relationships. Substituting into the linear formula, the final frequency compensation amount is... In terms of overall control logic, it exhibits a dramatic increase in nonlinearity as the attenuation slope decreases, thus achieving complete self-consistency in the description of the nonlinear abrupt change characteristics of the mathematical model and physical properties; the modulation instruction synthesis unit superimposes the calculated Δf onto the preset base power pulse frequency to generate the final pulse frequency modulation parameters.

[0012] Preferably, the system further includes: a multi-loop power entropy management module, connected between the power spectrum scheduling module and the external power distribution bus, used to calculate the impedance entropy value of each power request task based on the attenuation slope index fed back by each load branch when receiving concurrent power requests from multiple load branches; the multi-loop power entropy management module dynamically sorts the concurrent power request queue according to the impedance entropy value, prioritizes responding to power requests with impedance entropy values ​​in the nonlinear change range, and implements a power degradation strategy for low-entropy steady-state loads, so as to maintain the energy supply stability of critical load branches under the boundary conditions of limited total power system capacity.

[0013] Preferably, when the multi-loop power entropy tube module detects that the load rate of the power distribution bus exceeds the preset safety redundancy threshold, it forcibly starts the time-domain slicing reuse logic. The time-domain slicing reuse logic interleaves high-power-density pulse tasks and low-power-density detection tasks on the time axis to ensure that the number of high-energy-consuming load branches connected to the power supply unit at the same time does not exceed the physical upper limit of the system's power supply capacity.

[0014] Preferably, the transient response acquisition module includes: an oversampling front-end unit configured to capture real-time current response waveform data at a sampling rate not less than 10 times the inherent resonant frequency of the load circuit; and a fundamental frequency extraction and filtering unit connected after the oversampling front-end unit, used to filter out high-frequency switching noise caused by the operation of power semiconductor switching, and retain the fundamental frequency component and its low-order harmonic components that reflect the load damping characteristics.

[0015] Preferably, the power modulation control command includes: a PWM duty cycle signal for directly controlling the switching ratio of the power inverter to adjust the average power density output to the pulse power execution circuit; and a dead-time timing parameter for setting the minimum off interval between two adjacent power pulses, which is a function mapping that is negatively correlated with the attenuation slope index to ensure sufficient energy dissipation rebound time in high-damped load environments.

[0016] Preferably, the system further includes: a reference impedance database module, which stores reference attenuation slope data of different batches of load media at different ambient temperatures; when calculating the attenuation slope index, the complex impedance damping decoupling module obtains the current ambient temperature data through an external interface and retrieves the corresponding reference data in the reference impedance database module as a normalization factor to eliminate systematic measurement errors caused by ambient temperature thermal drift.

[0017] Preferably, the pulse power execution circuit includes a pneumatic-hydraulic actuator or an electromagnetic linear motor, with a drive coil or piezoelectric transducer connected to its feedback end; the system is integrated as an embedded edge computing node in the electrical control cabinet of the distributed power management node, and interacts with the central energy management system through industrial real-time Ethernet to achieve centralized optimization management of the energy consumption of distributed load nodes.

[0018] The embodiments of the present invention have at least the following beneficial effects:

[0019] 1. In the pole-switching task planning, the logic operation module performs time-domain differentiation on the free oscillation time window of the actuator feedback signal after the pulse action ends, extracting the time-domain attenuation slope of the signal amplitude as an independent discrimination dimension. Utilizing the physical response difference between the high-frequency fast attenuation of brittle media and the low-frequency slow attenuation of viscoelastic media, a second characteristic coordinate orthogonal to the pulse amplitude is constructed at the electrical digital logic level. This enables the system to effectively distinguish between high-hardness brittle crusts and high-viscoelastic gelatinous crusts. Even if the two show high consistency in the current peak value fed back by the sensor, the data processing system can still identify the rheological properties of the medium by analyzing the damping characteristics at the end of the signal. This logic design eliminates the misjudgment of operating conditions caused by feature aliasing under a single scalar mapping mode, ensuring that subsequent control commands are generated based on the real physical impedance properties rather than a single electrical value. This avoids ineffective energy dissipation and mechanical jamming of the actuator caused by erroneous output of high-intensity impact commands under viscous operating conditions.

[0020] 2. The parameter mapping module incorporates frequency compensation logic based on damping attenuation rate, establishing an energy application mode switching path driven by the rheological characteristics of the medium. When the system determines through data calculation that the work object is in a high-viscosity state, the parameter generation logic automatically executes the dimensionality reduction reconstruction of the control strategy, reduces the pulse intensity command value, and nonlinearly increases the pulse frequency command value according to the inverse relationship of the attenuation slope. This dynamic mapping mechanism based on data characteristics enables the execution end to smoothly switch from a single impact crushing mode to a high-frequency vibration shearing mode. This mechanism changes the energy distribution density in the time domain and uses high-frequency vibration to cut off the connection force of the viscous medium, solving the problem of work failure caused by the absorption of energy by the deformation of the medium when facing viscoelastic loads by traditional fixed-frequency control logic, and realizing impedance matching between the pulse energy waveform and the physical characteristics of the load.

[0021] 3. The instruction generation module introduces task entropy as an arbitration weight for resource scheduling. This weight represents the acceleration of the change of the crust hardness characterization factor in a continuous time series. When the estimated total energy consumption demand exceeds the system bus threshold due to multiple concurrent requests, the system dynamically sorts the concurrent queue according to the task entropy value, selects low-entropy tasks with slowing state evolution, and forcibly calls the degradation mapping rule, temporarily outputting low-energy maintenance instructions to release power quotas. This mechanism transforms the static first-in-first-out queuing logic into a dynamic resource allocation logic based on the urgency of deteriorating operating conditions. Under the boundary conditions of limited physical resources, it ensures that high-entropy tasks in the rapid hardening stage can obtain sufficient computing power and energy support. This yielding strategy based on second-order data characteristics eliminates the instantaneous overload of the power supply unit or the congestion of the communication bus caused by multiple tasks simultaneously requesting high-energy-consuming instructions at the logical level, ensuring the continuous operation stability of the electronic digital data processing system under high load conditions. Attached Figure Description

[0022] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings, in which several embodiments of the invention are illustrated by way of example and not limitation, wherein:

[0023] Figure 1 This is a closed-loop energy scheduling logic architecture diagram of the pole-switching task planning system of the present invention;

[0024] Figure 2 This is a diagram showing the current decay characteristics and damping state division within the zero-input response time window of the present invention. Detailed Implementation

[0025] The principles and spirit of the present invention will now be described with reference to several exemplary embodiments in conjunction with the accompanying drawings. It should be understood that these embodiments are provided merely to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0026] An electrical digital data processing system for pole-switching task planning, the system comprising:

[0027] The transient response acquisition module, coupled to the feedback end of the pulse power execution loop, is used to capture the real-time current response waveform data of the nonlinear time-varying load after receiving a power pulse injection at a high-frequency sampling rate.

[0028] The complex impedance damping decoupling module is connected to the transient response acquisition module. Based on the real-time current response waveform data, it locks the zero-input response time window after the power pulse injection ends, and extracts the time-domain attenuation characteristics of the signal envelope within the time window. Then, it calculates the attenuation slope index that characterizes the complex impedance damping characteristics of the nonlinear time-varying load.

[0029] The power spectrum scheduling module, connected to the complex impedance damping decoupling module, constructs a dynamic impedance model of the nonlinear time-varying load based on the attenuation slope index, and generates a power modulation control command for the next operating cycle of the pulse power execution circuit accordingly. The complex impedance damping decoupling module defines the starting boundary of the zero-input response time window by identifying the zero-crossing moments of the real-time current response waveform data, and performs a first-order differential operation on the signal amplitude within this time window to quantify the attenuation slope index. When the power spectrum scheduling module detects that the attenuation slope index is lower than a preset critical damping threshold, it determines that the current load circuit is in an overdamped, high-energy-consumption state, and generates a power modulation control command containing frequency conversion drive parameters to drive the power supply unit to dynamically adjust the frequency characteristics of the output energy, thereby preventing power delivery deadlock in the pulse power execution circuit under high-damping load environments.

[0030] Preferably, the complex impedance damping decoupling module includes: an instantaneous envelope calculation unit, configured to receive a discrete current sequence within a zero-input response time window, and extract the analytical signal magnitude of the discrete current sequence using a Hilbert transform algorithm to construct an instantaneous amplitude envelope; a differential evolution calculation unit, connected to the instantaneous envelope calculation unit, configured to perform a discrete-time first-order differential operation on the instantaneous amplitude envelope to obtain an instantaneous attenuation rate sequence reflecting the energy dissipation rate of the load circuit; and a feature weighted aggregation unit, connected to the differential evolution calculation unit, configured to perform an average processing on the instantaneous attenuation rate sequence based on time window weights, and output a single numerical attenuation slope index as a normalized quantization basis characterizing the rheological impedance properties of the load medium.

[0031] Preferably, the power spectrum scheduling module includes: an impedance spectrum mapping unit, which stores a preset load impedance characteristic lookup table to map the attenuation slope index to the corresponding load equivalent stiffness level and load equivalent viscosity level; the preset load impedance characteristic lookup table is a two-dimensional double monotonic mapping matrix constructed from multiple sets of experimental calibration data in a digital memory; the input to the lookup table is the attenuation slope index; as a one-dimensional single-valued quantity, its numerical range is discretized into multiple stepped ranges; wherein, when the attenuation slope index is in the range of 0.0V / ms to 0.2V / ms, the output port of the impedance spectrum mapping unit directly outputs a digital code indicating that the mapped load equivalent stiffness level is high stiffness and the load equivalent viscosity level is high viscosity; when the attenuation slope index is... When the load is in the range of 0.2V / ms to 0.4V / ms, the output is mapped to a digital code with a load equivalent stiffness level of medium stiffness and a load equivalent viscosity level of medium viscosity. The equivalent stiffness level and the equivalent viscosity level are both 2-bit digital logic features, which are used to characterize the brittle fracture tendency and rheological damping properties of the load medium, respectively, thereby providing a definite digital interface for efficient table lookup and hardware state matching of subsequent modulation commands. The modulation command synthesis unit is connected to the impedance spectrum mapping unit and is configured to determine the pulse amplitude modulation parameters based on the load equivalent stiffness level, determine the pulse frequency modulation parameters based on the load equivalent viscosity level, and perform time-domain superposition of the pulse amplitude modulation parameters and the pulse frequency modulation parameters to generate a power modulation control command.

[0032] Preferably, the modulation instruction synthesis unit incorporates a mathematical formula for quantizing and calculating the pulse frequency compensation amount: Where Δf is the frequency compensation amount to be superimposed on the base power pulse frequency, and K is the preset frequency response gain coefficient. This is a preset reference attenuation slope corresponding to the base underdamped load. The measured attenuation slope index is output by the feature weighting aggregation unit; the modulation command synthesis unit superimposes the calculated Δf onto the preset base power pulse frequency to generate the final pulse frequency modulation parameters.

[0033] Preferably, the system further includes: a multi-loop power entropy management module, connected between the power spectrum scheduling module and the external power distribution bus, used to calculate the impedance entropy value of each power request task based on the attenuation slope index fed back by each load branch when receiving concurrent power requests from multiple load branches; the multi-loop power entropy management module dynamically sorts the concurrent power request queue according to the impedance entropy value, prioritizes responding to power requests with impedance entropy values ​​in the nonlinear change range, and implements a power degradation strategy for low-entropy steady-state loads, so as to maintain the energy supply stability of critical load branches under the boundary conditions of limited total power system capacity.

[0034] Preferably, when the multi-loop power entropy tube module detects that the load rate of the power distribution bus exceeds the preset safety redundancy threshold, it forcibly starts the time-domain slicing reuse logic. The time-domain slicing reuse logic interleaves high-power-density pulse tasks and low-power-density detection tasks on the time axis to ensure that the number of high-energy-consuming load branches connected to the power supply unit at the same time does not exceed the physical upper limit of the system's power supply capacity.

[0035] Preferably, the transient response acquisition module includes: an oversampling front-end unit configured to capture real-time current response waveform data at a sampling rate not less than 10 times the inherent resonant frequency of the load circuit; and a fundamental frequency extraction and filtering unit connected after the oversampling front-end unit, used to filter out high-frequency switching noise caused by the operation of power semiconductor switching, and retain the fundamental frequency component and its low-order harmonic components that reflect the load damping characteristics.

[0036] Preferably, the power modulation control command includes: a PWM duty cycle signal for directly controlling the switching ratio of the power inverter to adjust the average power density output to the pulse power execution circuit; and a dead-time timing parameter for setting the minimum off interval between two adjacent power pulses, which is a function mapping that is negatively correlated with the attenuation slope index to ensure sufficient energy dissipation rebound time in high-damped load environments.

[0037] Preferably, the system further includes: a reference impedance database module, which stores reference attenuation slope data of different batches of load media at different ambient temperatures; when calculating the attenuation slope index, the complex impedance damping decoupling module obtains the current ambient temperature data through an external interface and retrieves the corresponding reference data in the reference impedance database module as a normalization factor to eliminate systematic measurement errors caused by ambient temperature thermal drift.

[0038] Preferably, the pulse power execution circuit includes a pneumatic-hydraulic actuator or an electromagnetic linear motor, with a drive coil or piezoelectric transducer connected to its feedback end; the system is integrated as an embedded edge computing node in the electrical control cabinet of the distributed power management node, and interacts with the central energy management system through industrial real-time Ethernet to achieve centralized optimization management of the energy consumption of distributed load nodes.

[0039] Example 1: When the electro-digital data processing system is applied to the planning of electrolytic aluminum electrode switching tasks, and the load medium exhibits nonlinear time-varying high viscoelastic rheological properties, the data acquisition module receives the electrolyte concentration data sequence and liquid level height data sequence after analog-to-digital conversion via an industrial real-time Ethernet bus. The logic operation module calls a preset nonlinear feature mapping algorithm. A weighted operation is performed on the current state feature vector to calculate the crust hardness characterization factor Γ, using a nonlinear mapping algorithm. In practical applications, a Sigmoid-type nonlinear activation function is used to simulate the nonlinear abrupt change in the crust from elastic deformation to plastic failure. The specific form of the algorithm is as follows: ,in The weighting coefficients are the preset phase transition bias constants. , , It is derived from a historical sample database of the factory through least squares fitting. Under the electrode switching conditions of electrolytic aluminum, it is usually set as follows: The value ranges from 0.45 to 0.55. The value ranges from 0.2 to 0.3. The value is set to 0.25 to 0.35 to ensure that the concentration characteristics dominate when assessing the rheology of the crust. This weighting configuration enables the system to maintain high sensitivity to the damping evolution caused by changes in the internal composition of the electrolyte.

[0040] Where C represents the concentration characteristic value and H represents the liquid level characteristic value. Represents the characteristic value of the feedback current. , , The weighting coefficients, calibrated based on historical data, yield a calculated Γ value of 0.85 within the current sampling period. This value is mapped to a high-intensity pulse amplitude request in a preset lookup table, eliminating the dimensionless scalar hardness characterization factor calculated through a nonlinear activation function. Compared with the measured attenuation slope index in V / ms To address the dimensional mismatch, the system introduces a cross-dimensional bridging mapping rule in the comparison stage of the control algorithm; specifically, the system utilizes the linear transformation coefficients calibrated by offline regression. The unit is V / ms, and the calculated dimensionless hardness characterization factor is... Converted into a static reference adjustment factor with the same voltage-time rate of change dimension. Before the actual frequency compensation calculation, the converted... Compared with the dimensional measured attenuation slope index, which is extracted in real time through Hilbert transform and first-order difference operation and represents the dynamic feedback quantity, Both are connected to the input of the subtraction operator, thus collaboratively determining the direction and magnitude of subsequent frequency correction while ensuring complete equivalence and alignment of physical dimensions. The transient response acquisition module simultaneously captures real-time current response waveform data after the power pulse injection ends in high-frequency mode. The complex impedance damping decoupling module identifies the zero-crossing point of the current waveform or the moment when the current amplitude drops to 5% of the peak value (for overdamped conditions where the current does not cross zero), defining a zero-input response time window of 50ms. The length of this time window is set by the hardware firmware to be 4 times the electrical time constant of the load circuit (inductance value L divided by resistance value R) to ensure that the complete energy dissipation process is covered. Within this time window, the module performs Hilbert transform on the acquired discrete current sequence to extract the analytical signal magnitude, and performs discrete-time first-order difference operation on the constructed instantaneous amplitude envelope to quantify the attenuation slope index characterizing the damping characteristics of the load complex impedance.

[0041] The measured attenuation slope was 0.15V / ms, which is lower than the system's preset critical damping threshold of 0.4V / ms. This indicates that the load is in an overdamped, high-energy-consumption state. In response to this low attenuation rate characteristic, the power spectrum scheduling module triggers a frequency compensation mechanism to replace the single amplitude gain logic. The modulation instruction synthesis unit calls the frequency compensation formula. Calculate the frequency compensation amount, where K is the frequency response gain coefficient. The preset reference attenuation slope for the underdamped load is used. To ensure consistency of parameter attributes in the control loop, the measured attenuation slope index must be used as the reference value before the system calls the frequency compensation formula. The properties are aligned with the hardness characterization factor calculated by a nonlinear algorithm. Specifically, in the frequency compensation logic here... Maintaining its physical meaning as the rate of change of a time-domain signal, reflecting the real-time dissipation rate of pulse energy by the load, the system uses the calculated hardness factor as a static reference adjustment factor. As dynamic feedback quantities, the two together determine the direction of frequency correction in the compensation formula. Since the attenuation slope and hardness level have a monotonic correlation in physical mechanism, the system unifies the characterization quantities of different dimensions into the gain space of frequency response through preset conversion coefficients, ensuring that the components participating in the difference calculation are completely matched in terms of dimensions and physical connotation.

[0042] The calculated frequency compensation amount Δf is 12Hz. The system superimposes this compensation amount onto the preset base pulse frequency of 2Hz to generate a power modulation control command with a frequency command value of 14Hz. It also shortens the dead time sequence parameters between adjacent pulses. This control message containing the frequency conversion drive parameters drives the power supply unit to output high-frequency shear energy, establishes a matching energy dissipation path inside the viscoelastic medium, and avoids power delivery deadlock in the execution loop.

[0043] Example 2: To verify the damping decoupling and power dispatching capabilities of the present invention under nonlinear time-varying load conditions, a hardware-in-the-loop (HIL) test platform was built, comprising an industrial-grade pulse power supply, a simulated electrolytic cell load network, and a real-time data acquisition and analysis unit. This platform was configured to reproduce the rheological physical properties of a real electrolyte crust, specifically covering the brittle state of pure resistivity and the thixotropic state with viscoelasticity. To construct an electromagnetic interference environment consistent with engineering realities, broadband Gaussian white noise with a signal-to-noise ratio of 20 dB was actively injected into the sensor feedback loop to test the system's feature extraction accuracy under noise masking. The experiment was conducted on a comparative sample group (control group A) using existing technology, which was configured only based on stable... The threshold judgment logic for the steady-state current amplitude is as follows: When the simulated load is set to a high viscoelastic soft shell state, although the load has extremely high physical viscosity, due to the lack of a rigid fracture interface, the steady-state amplitude of the feedback current does not reach the high hardness impact threshold preset by the system. Based on a single amplitude dimension, control group A incorrectly identifies the current working condition as a low impedance state and continuously outputs low-frequency, high-amplitude reference pulses. During the continuous operation cycle of up to 120 seconds, the real-time monitoring data shows that the equivalent impedance curve at the load end remains in the high plateau region without an effective downward inflection point, indicating that the injected pulse energy is dissipated by the viscous damping inside the medium and fails to trigger structural physical shear, and the system falls into a power transmission deadlock state.

[0044] For the test group (sample group B of this invention) using the technical solution of this invention, the test was started under the same viscoelastic load and noise interference conditions. After the system was powered on, the transient response acquisition module captured the current waveform after the pulse injection, and used zero-crossing detection logic to lock a zero-input response time window with a duration of 50ms in a strong noise background. Within this time window, the complex impedance damping decoupling module performs Hilbert transform and first-order difference operations on the discrete current sequence, and applies weighted aggregation logic based on a trapezoidal window function: the data weights in the first 2ms of the time window are forcibly set to 0 to shield the high-frequency oscillation noise at the moment the power switch turns off; the data weights in the 2ms to 40ms interval are set to 1.0 as the core feature region; the data weights in the 40ms to 50ms interval are linearly decreased from 1.0 to 0 to suppress the quantization noise at the end of the signal. The module accumulates the weighted difference values ​​and divides them by the sum of the effective weights to extract the measured attenuation slope index characterizing the load damping characteristics. Data shows that although the original signal was contaminated by noise, after processing... The values ​​are stably distributed in the range of 0.12V / ms to 0.18V / ms, which is lower than the system's preset critical damping threshold of 0.4V / ms, clearly indicating that the load is in an overdamped rheological state.

[0045] Based on the above feature recognition, the power spectrum scheduling module triggers the frequency compensation mechanism, and the modulation instruction synthesis unit calls the frequency compensation formula. Calculate the frequency compensation amount and set the reference attenuation slope. The frequency response gain coefficient K is 25Hz / (V / ms), and the reference attenuation slope is 0.6V / ms. The value is determined based on the average of multiple discharge experiments with a standard underdamped load at an ambient temperature of 20°C, representing the system's desired ideal energy rebound rate, while the frequency response gain coefficient... The frequency response gain coefficient is derived from the minimum controlled frequency step of the actuator and the oscillation acceleration required for the target shear force. The calibration process and physical boundary determination process are as follows: First, the physical limit frequency response step of the piezoelectric transducer component of the actuator is measured to be 0.5Hz. Under the known extreme boundary of electrolyte viscous damping, the minimum high-frequency shear force oscillation acceleration required to induce thixotropic softening of the medium is... Based on the electromechanical coupling constant, it can be deduced that a unit frequency increase can bring... The attenuation slope recovery increment is used to calculate the optimal gain coefficient so that the system can adjust the overdamped condition to the critical damping range within no more than 3 operating cycles. The system will use this to preset The baseline value is fixed at 25Hz / (V / ms); the safety redundancy threshold is calculated based on the rated thermal dissipation and fuse boundary of the external power distribution bus. When the continuous load rate of the bus reaches 90%, the bus temperature rise gradient approaches the safety critical point. Based on this, the system forcibly limits the load rate to 90% as the hard safety threshold for starting the time-domain sharding reuse logic. By pre-testing the yield stress of the actuator in different viscosity media, the energy penetration increment brought by the unit frequency increase is calculated, thereby calibrating the... Value, to ensure frequency compensation amount It can adjust the load state to the critical damping range in the shortest possible time.

[0046] The calculated frequency compensation Δf is approximately 11Hz. The system then generates a frequency command control message with a value of 13Hz for the frequency converter drive. Within 15 seconds of applying this frequency pulse, the equivalent impedance data fed back from the load side begins to increase at a rate of 0.5... The rate of decrease was linear, confirming that the high-frequency shear force effectively excited the thixotropic softening effect of the medium. By the 25th second, the attenuation slope index was monitored. The rebound and breakthrough of the 0.4V / ms threshold indicates that the medium has changed from a viscoelastic state to a brittle state, and the switching channel is open. Compared with the control group A, the effective working time of sample group B of this invention is shortened by 79%, and the total energy consumption is reduced by 45%. Finally, in order to verify the rationality of the value of the key control parameter K, an out-of-range control group (control group C) was set. When the K value is set to 5Hz / (V / ms) lower than the lower limit of the preferred range, the calculated frequency compensation is insufficient to overcome the yield stress of the medium, the impedance decrease rate slows down, and the working time is extended to more than 90s. When the K value is set to 50Hz / (V / ms) higher than the upper limit of the preferred range, the excessive frequency step causes obvious overshoot and oscillation in the power supply output waveform, increasing the risk of thermal runaway of the system.

[0047] Example 3: This example combines Figures 1 to 2 The description of the electrical digital data processing system in the pole-switching task planning is as follows: Figure 1 As shown, the logic architecture mainly consists of a transient response acquisition module, a complex impedance damping decoupling module, a power spectrum scheduling module, and a power supply unit. The transient response acquisition module is coupled to the feedback end of a pulsed power execution loop containing a nonlinear time-varying load. It captures real-time current response waveform data and transmits this waveform data to the complex impedance damping decoupling module. The complex impedance damping decoupling module locks a zero-input response time window based on the received data, calculates the attenuation slope index by extracting time-domain attenuation characteristics, and transmits this index to the power spectrum scheduling module. The power spectrum scheduling module constructs a dynamic impedance model based on this attenuation slope index and generates a power modulation control command after identifying an overdamped high-energy-dissipation state. Time-domain superposition refers to… In the waveform synthesis stage of the control signal generation, in actual operation, the modulation command synthesis unit first uses the pulse frequency modulation parameter as the reference clock signal to determine the trigger period and turn-off interval of the pulse sequence. Then, within the pulse width of each trigger, the pulse amplitude modulation parameter is assigned as the command value of the target voltage or current to the duty cycle register of the PWM controller. By applying the frequency parameter to the division of the time axis and the amplitude parameter to the intensity setting of the energy axis, a composite control sequence with discrete distribution in time and variable intensity is synthesized. This sequence is sent to the power supply unit to adjust the frequency characteristics of the output energy, thereby driving the next action cycle, thus forming a closed-loop energy dispatch control loop for nonlinear time-varying loads.

[0048] like Figure 2As shown in the figure, with time as the horizontal axis and current amplitude as the vertical axis, the zero-input response time window after the pulse power execution circuit's working phase and the pulse cutoff time t0 is defined. Within this time window, the system distinguishes three typical damping states based on the trajectory of current amplitude changes: State I (overdamped state), characterized by high energy consumption and a small attenuation slope; State II (critically damped state), serving as a reference and exhibiting rapid reset characteristics; and State III (underdamped state), characterized by oscillation attenuation. The complex impedance damping decoupling module quantifies the attenuation slope index based on the evolution of the aforementioned waveform characteristics after time t0, using this as the physical basis for the system's frequency compensation and power scheduling.

[0049] Example 4: To address the resource competition between energy supply stability and load abrupt change response in pole-switching task planning, this example constructs a dynamic power entropy tube mechanism based on a multi-loop power entropy tube module. Its core technology is to introduce impedance entropy as a quantitative indicator characterizing the nonlinear complexity and urgency of the load, and to execute differentiated power scheduling accordingly. For each concurrently connected load branch i, the complex impedance damping decoupling module calculates its attenuation slope in real time. To capture the dynamic evolution of the load in the time domain, the multi-loop power entropy transistor module is configured with a sliding time window of length N to buffer the decay slope data sequence of N consecutive sampling periods. , length is The sliding time window, its total number of samples The deterministic configuration is set to a fixed constant of 200; since the transient response acquisition module samples discrete data at a serial clock rate of 2kHz within each zero-input response time window, the total number of samples... This precisely covers a complete 100ms dynamic response evaluation period. The boundary setting of this discrete time window ensures that there are enough sample points distributed within 40 equally wide statistical intervals during histogram discretization to output Shannon entropy calculation results with statistical confidence, while avoiding impedance entropy values ​​caused by excessive data backlog in the window. In microsecond-level time-domain slice scheduling, a response lag is generated, achieving system self-consistency between statistical accuracy and control immediacy; the module calculates the impedance entropy value of the sequence based on information entropy theory. The specific calculation process is as follows: The decay slope sequence within the time window is normalized, and the histogram is discretized. Within the effective measurement range of 0.0 V / ms to 2.0 V / ms, the system divides the data into 40 equally wide statistical intervals, each with a width of 0.05 V / ms. The system iterates through N data points within the window, counts the number of data points falling into each interval, and divides the count value of each interval by the total number of data points N to generate a probability distribution. Applying the Shannon entropy formula The impedance entropy value is calculated, and this index... This objectively reflects the degree of time-varying disorder in the load impedance characteristics: lower The value corresponds to the steady-state or linearly gradual stage of the load characteristics, while a higher value... The value precisely maps the load to the region of drastic nonlinear abrupt change or phase transition, i.e., the nonlinear abrupt change region. The high entropy value mapping logic is based on the discrete statistical distribution of the attenuation slope sequence. When the load is in a steady state, the continuously sampled attenuation slope index is concentrated in a very narrow numerical range, the probability distribution is highly concentrated, and the calculated Shannon entropy is close to zero. However, when the load enters the nonlinear abrupt change region, the feedback signal exhibits drastic multi-steady-state jumps, and the attenuation slope index is distributed in multiple different statistical intervals within the sliding window, causing the probability distribution to tend to be discrete and uniform, thus significantly increasing the calculated entropy value. By monitoring this statistically significant increase in disorder, the system can predict the unstable state of the medium's physical properties and thus prioritize the allocation of scheduling resources. This is achieved by obtaining the impedance entropy value set of all concurrent tasks. Then, the system executes a dynamic sorting strategy prioritizing maximum entropy, assigning impedance entropy values... Greater than the preset entropy threshold The load tasks are defined as high-entropy tasks and set as the highest priority in the power allocation logic. The physical basis of this strategy is that high-entropy states are usually accompanied by critical physical processes such as the rupture, collapse, or rheological changes of the electrolyte crust. If the energy supply is interrupted or degraded at this time, it will lead to irreversible failure of the process. Conversely, for Less than For low-entropy tasks, the system treats them as steady-state maintenance tasks. Under the boundary condition of limited total power capacity, the system implements a power degradation strategy for low-entropy tasks, temporarily reducing their pulse frequency or amplitude to release power margin to meet the instantaneous peak demand of high-entropy tasks. Furthermore, to cope with extreme high-load concurrency scenarios, when the total power demand of all tasks exceeds the rated capacity of the power distribution bus and the bus load rate exceeds the preset safety redundancy threshold, such as 90%, the multi-loop power entropy tube module forcibly starts the time-domain slicing reuse logic, dividing the control cycle into microsecond-level time slices and performing staggered scheduling according to task attributes. Specifically, the system outputs full power to high-entropy tasks in odd-numbered time slices to ensure their energy surge demand; in even-numbered time slices, it switches to low-entropy tasks for low-power maintenance or state detection. This orthogonal reuse mechanism in the time domain ensures that the number of high-energy-consuming loads connected to the power unit at the same time is always within a safe range, achieving global optimal scheduling under the constraint of limited power resources, and effectively avoiding the risk of system shutdown or voltage drop due to overload.

[0050] Example 5: Before the electro-digital data processing system was officially put into operation for the pole-switching task, in order to eliminate the parameter uncertainty in the core nonlinear feature mapping algorithm and ensure the accurate correspondence between the crust hardness characterization factor Γ and the actual physical conditions, an offline calibration and data filling procedure was executed. A standard sample library containing different temperatures, electrolyte ratios, and mechanical strengths was constructed on the offline testing platform, covering the full spectrum of physical states from brittle hard shells to viscoelastic soft shells. For each sample in the sample library, an in-situ puncture test was performed using a high-precision mechanical probe to obtain its true physical hardness value as the baseline. The electrolyte concentration, liquid level, and feedback current original state characteristic data corresponding to the sample were collected through the system's data acquisition module. A multivariate nonlinear regression algorithm was used to minimize the mean square error between the predicted hardness and the baseline, and the weighting coefficients in the mapping algorithm were adjusted accordingly. , , Iterative optimization is performed to construct and populate a parameter lookup table with deterministic mapping relationships.

[0051] Furthermore, considering the differences in cell structure, busbar layout, and electromagnetic environment among different aluminum plant production lines, to avoid judgment bias caused by environmental baseline drift, the system enforces a pre-calibration and commissioning procedure during the on-site deployment phase. This requires a pre-set silent learning period of approximately 24 hours after the system is first connected to the target electrolytic cell group. During this period, the system does not issue control commands but operates in passive listening mode, continuously collecting background noise data and current response waveforms under normal operation for each load branch. Based on the statistical distribution of the collected data, the system automatically calculates and updates the reference attenuation slope for each branch. And critical damping threshold, to achieve adaptive baseline calibration for specific physical environments, ensuring that the system can maintain the robustness of control logic and the accuracy of judgment when facing parameter drift caused by different factory environments and equipment aging.

[0052] Example 6: To ensure the absolute executability of the frequency modulation commands generated by the power spectrum scheduling module at the physical execution level and to prevent system oscillations caused by the mechanical response lag of the actuator, this example establishes and implements a standardized electromechanical response boundary calibration procedure. Its core lies in quantitatively measuring the dynamic response capability of the pulse power execution loop through active frequency scanning testing, thereby setting hard physical constraints for subsequent frequency compensation algorithms. After the calibration procedure is initiated, the system main control unit drives the pulse power execution loop to output a set of frequencies linearly scanning from 0.1Hz to the no-load or standard dummy load. The system uses a sine wave or square wave test signal up to 50Hz. Simultaneously, a high-frequency displacement sensor or embedded current transformer installed at the end of the actuator is used to synchronously acquire displacement response data or output current waveform data of the mechanical vibration at a sampling rate of no less than 1kHz. The data processing unit performs real-time comparative analysis of the acquired input electrical signal frequency and the output physical response (displacement or current), focusing on calculating the phase difference and amplitude attenuation ratio between the two. Based on Bode plot analysis, the system automatically identifies and locks the frequency point where the phase difference reaches -3dB or the amplitude attenuation exceeds 30%, defining this as the system's cutoff frequency. The system performs threshold determination for both phase and amplitude characteristics. For amplitude-frequency characteristics, the system searches for the output amplitude to decrease relative to the reference amplitude to a certain level. The frequency is multiple times that of the input excitation. For the phase frequency characteristics, the system synchronously monitors the gradient of phase lag as the frequency increases. According to the dynamic response principle of linear systems, the phase angle after the input excitation reaches a specific delay angle value is taken as the phase boundary. Here, the frequency response limit of the system is comprehensively determined by parallel monitoring of the amplitude gain attenuation in decibels and the phase lag angle value.

[0053] Simultaneously, the maximum slew rate of the system is determined by calculating the maximum rate of change of the output response per unit time. After completing the above tests and calculations, the system will and These two key physical limit parameters are permanently written into the constraint register of the logic operation module. Subsequently, during the real-time operation of the multi-loop power entropy transistor module, any parameters determined by the frequency compensation formula... The calculated dynamic frequency compensation amount Both the calculated value and its rate of change are verified by this constraint register. If the calculated value exceeds... or Within the defined linear response range, the system will force the output command to be limited or slowed down to ensure that the control signal is always within the physical capability range of the actuator, thereby avoiding the risk of system instability caused by the command exceeding the execution capability.

[0054] During the real-time operation of the multi-loop power entropy transistor module, to avoid falsely triggering of high-priority power preemption logic due to artificially high impedance entropy values ​​caused by occasional spike noise from sensors, the system embeds entropy confidence verification logic based on time-domain gradients. This logic calculates the current impedance entropy value in real time during each calculation cycle. Compared to the previous cycle rate of change And compare this rate with a preset physical entropy change limit threshold. Comparison, among which It is a constant derived from the fastest theoretical rate of electrolyte physical phase transition, and is determined in practice. The system references the crack propagation rate and viscous relaxation time of the electrolyte under strong impact load. Since the phase change of the crust hardness at the microscale is limited by the molecular chain rearrangement rate, the rate of change of its impedance entropy has a physical upper limit. In the specific derivation process, the thermochemical reaction rate under a specific current density is calculated by the Arrhenius equation, and the maximum value of the entropy increment per unit time is obtained by combining material dynamics simulation. This value is set as the safety boundary for fault tolerance judgment, thereby effectively filtering out millisecond-level spike noise caused by poor sensor contact or strong magnetic field interference.

[0055] If the calculation yields Exceed The system determines that the current high-entropy characteristic is a spurious signal, blocks the priority upgrade request of this channel, and maintains the control state of the previous moment until the entropy change rate of three consecutive cycles returns to the physically permissible range. This builds a logical firewall against data noise on a microsecond-level timescale. When the system detects continuous data anomalies or when the actual current waveform fed back by the execution loop produces a phase loss of more than 15% with the expected control command, the main control unit forcibly triggers a deterministic degradation fault-tolerant procedure. This procedure immediately bypasses all nonlinear feature mapping algorithms and entropy scheduling logic, and switches the control mode to a pre-stored minimum safety maintenance table, which contains a set of low-energy-density trapezoidal wave drive parameters. Offline verification ensures that it will not cause current overload or arc extinction under any high-viscosity or hardened shell conditions. The system maintains this degradation mode until a manual reset command is received or the sensor data stream is confirmed to have returned to its statistical stability through a self-test program, thereby ensuring the intrinsic safety of the industrial site in extreme data failure scenarios.

[0056] The above description is only a few preferred embodiments of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present invention is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, technical solutions formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in the embodiments of the present invention.

Claims

1. An electrical digital data processing system for pole-switching task planning, characterized in that, The system includes: The transient response acquisition module, coupled to the feedback end of the pulse power execution loop, is used to capture the real-time current response waveform data of the nonlinear time-varying load after receiving a power pulse injection at a high-frequency sampling rate. The complex impedance damping decoupling module is connected to the transient response acquisition module. Based on the real-time current response waveform data, it locks the zero-input response time window after the power pulse injection ends, and extracts the time-domain attenuation characteristics of the signal envelope within the time window. Then, it calculates the attenuation slope index that characterizes the complex impedance damping characteristics of the nonlinear time-varying load. The power spectrum scheduling module, connected to the complex impedance damping decoupling module, constructs a dynamic impedance model of the nonlinear time-varying load based on the attenuation slope index, and generates power modulation control commands for the next operating cycle of the pulse power execution loop accordingly. The complex impedance damping decoupling module defines the starting boundary of the zero-input response time window by identifying the zero-crossing moments of the real-time current response waveform data, and performs first-order differential operations on the signal amplitude within this time window to quantify the attenuation slope index. The complex impedance damping decoupling module embeds dual-track boundary discrimination logic to adaptively accommodate different damping conditions. Specifically, this module simultaneously inputs the high-frequency acquired real-time current response waveform data to both the zero-crossing monitoring channel and the amplitude attenuation monitoring channel. When the load is in an underdamped state, the current waveform oscillates periodically and at the pulse cutoff moment... A zero-crossing point is quickly generated, and the zero-crossing point monitoring channel captures the first zero-crossing point trigger signal as the starting boundary of the zero-input response time window. When the load is in a nonlinear overdamped condition, the current signal cannot generate a zero-crossing point because the medium viscosity damping is too large, resulting in an exponential monotonic decay. At this time, the amplitude decay monitoring channel is activated, and the logic operation unit latches the current peak value at the end of the working stage of the pulse power execution circuit in real time, and uses this peak value as a reference to perform continuous voltage division ratio calculation. When the amplitude of the acquired current sequence drops to 5% of the current peak value, the amplitude decay monitoring channel outputs a step level signal as the starting boundary of the zero-input response time window under the nonlinear overdamped condition, thereby completing the smooth switching of the time window locking path under different conditions at the electrical digital logic level. When the power spectrum scheduling module detects that the attenuation slope index is lower than the preset critical damping threshold, it determines that the current load circuit is in an overdamped high-energy-consumption state and generates a power modulation control command containing frequency conversion drive parameters to drive the power supply unit to dynamically adjust the frequency characteristics of the output energy.

2. The electrical digital data processing system for pole-switching task planning according to claim 1, characterized in that, The complex impedance damping decoupling module includes: an instantaneous envelope calculation unit, configured to receive a discrete current sequence within a zero-input response time window, and extract the analytical signal magnitude of the discrete current sequence using the Hilbert transform algorithm to construct an instantaneous amplitude envelope; a differential evolution calculation unit, connected to the instantaneous envelope calculation unit, configured to perform a discrete-time first-order differential operation on the instantaneous amplitude envelope to obtain an instantaneous attenuation rate sequence reflecting the energy dissipation rate of the load loop; and a feature weighted aggregation unit, connected to the differential evolution calculation unit, configured to perform an average processing of the instantaneous attenuation rate sequence based on time window weights, and output a single numerical attenuation slope index as a normalized quantization basis for characterizing the rheological impedance properties of the load medium.

3. The electrical digital data processing system for pole-switching task planning according to claim 2, characterized in that, The power spectrum scheduling module includes: an impedance map mapping unit, which stores a preset load impedance characteristic lookup table to map the attenuation slope index to the corresponding load equivalent stiffness level and load equivalent viscosity level; and a modulation command synthesis unit, which is connected to the impedance map mapping unit and is configured to determine the pulse amplitude modulation parameters based on the load equivalent stiffness level, determine the pulse frequency modulation parameters based on the load equivalent viscosity level, and perform time-domain superposition of the pulse amplitude modulation parameters and the pulse frequency modulation parameters to generate a power modulation control command.

4. The electrical digital data processing system for pole-switching task planning according to claim 3, characterized in that, The modulation instruction synthesis unit introduces a mathematical formula for quantizing and calculating the pulse frequency compensation amount: Where Δf is the frequency compensation amount to be superimposed on the base power pulse frequency, and K is the preset frequency response gain coefficient. This is a preset reference attenuation slope corresponding to the base underdamped load. The measured attenuation slope index is output by the feature weighting aggregation unit; the modulation command synthesis unit superimposes the calculated Δf onto the preset base power pulse frequency to generate the final pulse frequency modulation parameters.

5. The electrical digital data processing system for pole-switching task planning according to claim 1, characterized in that, The system also includes a multi-loop power entropy management module, which is connected between the power spectrum scheduling module and the external power distribution bus. When multiple concurrent power requests are received from multiple load branches, the module calculates the impedance entropy value of each power request task based on the attenuation slope index fed back by each load branch. The multi-loop power entropy management module dynamically sorts the concurrent power request queue according to the impedance entropy value, prioritizes responding to power requests with impedance entropy values ​​in the nonlinear abrupt change range, and implements a power degradation strategy for low-entropy steady-state loads to maintain the energy supply stability of critical load branches under the boundary conditions of limited total power system capacity.

6. The electrical digital data processing system for pole-switching task planning according to claim 5, characterized in that, When the multi-loop power entropy tube module detects that the load rate of the power distribution bus exceeds the preset safety redundancy threshold, it forcibly starts the time-domain slicing reuse logic. The time-domain slicing reuse logic interleaves high-power-density pulse tasks and low-power-density detection tasks on the time axis to ensure that the number of high-energy-consuming load branches connected to the power supply unit at the same time does not exceed the physical upper limit of the system's power supply capacity.

7. The electrical digital data processing system for pole-switching task planning according to claim 1, characterized in that, The transient response acquisition module includes: an oversampling front-end unit configured to capture real-time current response waveform data at a sampling rate of not less than 10 times the inherent resonant frequency of the load circuit; and a fundamental frequency extraction and filtering unit connected after the oversampling front-end unit, used to filter out high-frequency switching noise caused by the operation of power semiconductor switching, and retain the fundamental frequency component and its low-order harmonic components that reflect the load damping characteristics.

8. The electrical digital data processing system for pole-switching task planning according to claim 1, characterized in that, The power modulation control command includes: a PWM duty cycle signal, used to directly control the switching ratio of the power inverter to adjust the average power density output to the pulse power execution circuit; and a dead-time timing parameter, used to set the minimum off interval between two adjacent power pulses, which is a function mapping that is negatively correlated with the attenuation slope index to ensure sufficient energy dissipation rebound time in high-damped load environments.

9. The electrical digital data processing system for pole-switching task planning according to claim 1, characterized in that, The system also includes: a reference impedance database module, which stores reference attenuation slope data of different batches of load media at different ambient temperatures; and a complex impedance damping decoupling module, which obtains the current ambient temperature data through an external interface when calculating the attenuation slope index, and retrieves the corresponding reference data in the reference impedance database module as a normalization factor to eliminate systematic measurement errors caused by ambient temperature thermal drift.

10. The electrical digital data processing system for pole-switching task planning according to claim 1, characterized in that, The pulse power execution circuit includes a pneumatic-hydraulic actuator or an electromagnetic linear motor, with a drive coil or piezoelectric transducer connected to its feedback end. When the pulse power execution circuit uses a pneumatic-hydraulic actuator as a large-inertia macroscopic actuator, to overcome the physical response lag of the fluid dynamic machinery at the millisecond level, the drive coil or piezoelectric transducer connected to the feedback end serves as a micro-adjustment mechanism, forming a series electromechanical two-stage drive architecture with the pneumatic-hydraulic actuator. The frequency conversion drive parameters in the power modulation control command generated by the power spectrum scheduling module are delivered in a hierarchical and decoupled manner at the physical execution level: the low-frequency amplitude energy component directly acts on the electromagnetic directional valve of the pneumatic-hydraulic actuator to control... The macroscopic impact kinetic energy, and the pulse frequency modulation parameters, which include high-frequency vibration shear energy, calculated by the frequency compensation formula, are directly applied to the piezoelectric transducer or the embedded high-frequency drive coil; the piezoelectric transducer utilizes the inverse piezoelectric effect to generate micro-amplitude high-frequency mechanical jitter within microseconds, and superimposes it on the macroscopic output curve of the pneumatic-hydraulic actuator, so that the final energy waveform of the injected load medium is superimposed with high-frequency micro-amplitude vibration on the basis of macroscopic large impact, thereby physically ensuring that the large inertial mechanical system can fully track and execute frequency modulation commands above 14Hz; the system is integrated as an embedded edge computing node in the electrical control cabinet of the distributed power management node.

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