Ultra-low frequency polarity adaptive circuit structure and operation method thereof

Abstract

The application discloses an ultra-low frequency polarity adaptive circuit structure and an operation method thereof. The ultra-low frequency polarity adaptive circuit structure comprises: an ultra-low frequency signal module, which is provided with a topology structure of a polarity circuit, and circuit elements of the ultra-low frequency signal module have a nanometer order characteristic size; a core structure module, which comprises a bipolar transistor array and a quantum effect compensation unit, and the bipolar transistor array and the quantum effect compensation unit are respectively used for signal compensation and stability control; a simulation experiment module, which is used for constructing a circuit simulation model and testing circuit performance in a 0.1-10 Hz frequency band; and an improved Gilbert module, wherein input impedance of the improved Gilbert module is not less than 10 12 Ω, an equivalent noise voltage of the improved Gilbert module is not greater than 5 nV / √Hz at a 1 Hz frequency, and a temperature drift coefficient of the improved Gilbert module is less than 0.1 μV / ℃.

Description

Technical Field

[0001] This application relates to the technical field of circuit structures, and in particular to ultra-low frequency polarity adaptive circuit structures and their operation methods. Background Technology

[0002] A circuit is the path through which electric current flows, also known as an electronic circuit. It consists of electrical devices and components (appliances) connected in a specific way. Examples include networks composed of resistors, capacitors, inductors, diodes, transistors, power supplies, and switches. Circuit sizes can vary greatly, from small integrated circuits on a silicon chip to large high- and low-voltage power transmission networks. Based on the different signals they process, electronic circuits can be divided into analog circuits and digital circuits.

[0003] However, existing fixed compensation capacitors cannot adapt to dynamic loads (error > 30%), and digital correction delays (> 100 ms) are difficult to track abrupt changes in geological signals. Summary of the Invention

[0004] This application proposes an ultra-low frequency polarity adaptive circuit structure and its operation method to overcome the deficiencies of the prior art.

[0005] According to a first aspect of the embodiments of this application, an ultra-low frequency polarity adaptive circuit structure is provided, comprising: An ultra-low frequency signal module has a polarized circuit topology, and the feature size of the circuit elements of the ultra-low frequency signal module is on the nanometer scale. The core structural module includes a bipolar transistor array and a quantum effect compensation unit, wherein the bipolar transistor array and the quantum effect compensation unit are used for signal compensation and stability control, respectively. The simulation experiment module is used to build circuit simulation models and test circuit performance in the 0.1 Hz to 10 Hz frequency band; An improved Gilbert module, wherein the input impedance of the improved Gilbert module is not less than 10Ω. 12 The equivalent noise voltage of the improved Gilbert module is no greater than 5nV / √Hz at a frequency of 1Hz, and the temperature drift coefficient of the improved Gilbert module is less than 0.1μV / ℃.

[0006] In some embodiments, the core structural module includes a hafnium oxide interface layer with a thickness of 2 nanometers, the hafnium oxide interface layer being configured to suppress the gate leakage current to 0.3 picoamperes per square micrometer.

[0007] In some embodiments, the ultra-low frequency polarity adaptive circuit structure includes a thyristor-switched capacitor in dynamic compensation scenarios, and the response time of the thyristor-switched capacitor is less than 20 milliseconds; the ultra-low frequency polarity adaptive circuit structure includes a dry capacitor or an oil-immersed capacitor in static compensation scenarios, and is configured with a filter reactor with a reactance of 7%.

[0008] In some implementations, the improved Gilbert module is used for four-quadrant product transformation, and the relationship between the output current and the input current of the improved Gilbert module is expressed as follows:

[0009] in, Indicates the output current; Indicates the cutoff frequency; Indicates a thermal compensation capacitor; Indicates the amount of electron charge; Represents the Boltzmann constant; Represents thermodynamic temperature; Represents the elementary charge; Both represent input current.

[0010] In some implementations, the compensation capacity of the quantum effect compensation unit satisfies the following relationship:

[0011] in, This indicates the reactive power that needs to be compensated; P represents the active power of the circuit or system. This represents the power factor angle before compensation; This represents the target power factor angle after compensation.

[0012] According to a second aspect of this application, an operating method is provided, implemented based on the aforementioned ultra-low frequency polarity adaptive circuit structure, comprising: Step S1: Initiate a self-calibration cycle every 60 seconds to compensate for voltage drift caused by electrode polarization; Step S2: Adjust the compensation parameters in real time according to load changes; Step S3: Monitor circuit performance parameters in real time through the simulation experiment module.

[0013] In some embodiments, step S1 further includes: Emergency calibration mode is activated when an electrode polarization voltage drift exceeding ±300mV is detected.

[0014] In some embodiments, S2 further includes: The quantum effect compensation unit monitors the tunneling current change in real time. When the gate leakage current exceeds 0.3 picoamperes per square micrometer, the bias voltage of the bipolar transistor array is automatically adjusted.

[0015] In some embodiments, S3 further includes: The system calculates the power factor change before and after compensation in real time. When the power factor increases from 0.75 to 0.95, it automatically records the operating parameters that reduce line loss by 12% and establishes an optimization parameter library.

[0016] In some embodiments, the method further includes: The circuit temperature changes are monitored in real time by using a thermal compensation capacitor. When the temperature drift coefficient exceeds 0.1 microvolts per degree Celsius, a temperature compensation mechanism is activated to ensure the accuracy of the four-quadrant product conversion.

[0017] The beneficial effects of the ultra-low frequency polarity adaptive circuit structure and its operation method in the embodiments of this application include at least the following: This application's embodiments effectively achieve circuit miniaturization and high integration by employing an ultra-low frequency signal module with a polarized circuit topology and a feature size on the nanometer scale, making it easy to deploy in modern precision chip systems. In the core structural module, a bipolar transistor array is responsible for signal compensation, while a quantum effect compensation unit is specifically designed to suppress non-ideal effects such as quantum tunneling at the nanometer scale. The two work together to significantly improve the long-term accuracy and extreme stability of signal processing. The simulation experiment module builds and tests circuit models in the target frequency band from 0.1 Hz to 10 Hz, greatly reducing R&D trial-and-error costs and accelerating product optimization cycles. The improved Gilbert module, with an input impedance of no less than 10¹²Ω, an equivalent noise voltage of no more than 5nV / √Hz at 1Hz, and a temperature drift coefficient of less than 0.1μV / ℃, ensures high-fidelity acquisition of weak ultra-low frequency signals and extremely low noise interference at the front end. At the same time, its excellent temperature characteristics ensure measurement consistency across the entire operating temperature range. Attached Figure Description

[0018] Figure 1 This is a schematic diagram illustrating an ultra-low frequency polarity adaptive circuit structure according to an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the sulfur-containing polymer electrolyte and its preparation method will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of this application. Obviously, the described embodiments are only some embodiments of the embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed embodiments of the present application, but merely to illustrate selected embodiments of the present application. Other embodiments obtained by those skilled in the art based on the embodiments of the present application without inventive effort are all within the scope of protection of the embodiments of the present application.

[0021] It can be noted that similar reference numerals and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it will not be further defined and explained in subsequent figures according to the embodiments of this application.

[0022] This application discloses an ultra-low frequency polarity adaptive circuit structure and its operation method. The operation method is implemented based on the ultra-low frequency polarity adaptive circuit structure system. The purpose is to solve the problems in the prior art where fixed compensation capacitors cannot adapt to dynamic loads (error > 30%) and digital correction delay (> 100 ms) is difficult to track geological signal changes.

[0023] See attached document Figure 1 As shown, this ultra-low frequency polarity adaptive circuit structure, refer to the attached diagram. Figure 1 As shown, it includes: an ultra-low frequency signal module, a core structure module, a simulation experiment module, and an improved Gilbert module.

[0024] The ultra-low frequency signal module is the core of this circuit structure for signal input and preprocessing. Its core function is to receive and process extremely low-frequency raw input signals, providing a stable and reliable signal foundation for subsequent compensation, calculation, and control. This module is configured to operate effectively within a specific ultra-low frequency band of 0.1 Hz to 10 Hz to meet the special requirements of ultra-low frequency signal processing in applications such as biomedical sensing and precision geological monitoring.

[0025] In some implementations, the ultra-low frequency signal module has a polarized circuit topology, and the circuit element feature size of the ultra-low frequency signal module is on the nanometer scale.

[0026] Specifically, to achieve the above functions, this module employs a dedicated topology architecture based on polarity circuits. This topology has been specially optimized to effectively maintain the integrity and accuracy of ultra-low frequency signals and possesses excellent anti-drift characteristics. Simultaneously, the module's circuit design fully considers compatibility with advanced integrated circuit manufacturing processes. Its specific structure and component parameters support manufacturing and integration using nanometer-level process nodes (e.g., but not limited to 5-nanometer processes), thereby achieving high performance, miniaturization, and low power consumption at the chip level.

[0027] In the circuit structure, the ultra-low frequency signal module works in conjunction with the "core structure module" (including bipolar transistor arrays, quantum effect compensation units, etc.), the "simulation experiment module," and the "improved Gilbert module." Specifically, its output signal is sent to the "core structure module" for further compensation and stabilization. Its design parameters and performance indicators (such as frequency response and noise characteristics) are modeled (e.g., by establishing a SPICE model) and verified within the 0.1Hz-10Hz frequency band through the "simulation experiment module." The processed signal can then be used as input for subsequent operations such as multiplication and conversion by the "improved Gilbert module."

[0028] In other words, the ultra-low frequency signal module of this application adopts a specific polarity circuit topology and is optimized for nanoscale processes and the 0.1Hz-10Hz ultra-low frequency band. It provides high-precision and high-stability front-end signal processing capabilities for the entire adaptive circuit structure. It also works in deep collaboration with system-level compensation algorithms, control logic and other functional modules to achieve the technical effect of accurate signal processing and adaptive compensation under extremely low frequency conditions.

[0029] In some implementations, the core structural module includes a bipolar transistor array and a quantum effect compensation unit, which are used for signal compensation and stability control, respectively.

[0030] The core structural module is the execution and compensation core of this application embodiment. Its main function is to receive the pre-processed signal from the "ultra-low frequency signal module" and perform substantial processing, compensation, and stabilization control on it to ultimately achieve the circuit's adaptability and high precision. The module is integrated and mainly includes two core technical units: a bipolar transistor array, which constitutes the module's basic amplification and signal conditioning body and is responsible for the core analog signal processing; and a quantum effect compensation unit, which is integrated with or works in conjunction with the bipolar transistor array to suppress and compensate for non-ideal characteristics such as quantum tunneling effects that may occur at the nanoscale, ensuring the module's extreme stability in the ultra-low frequency band.

[0031] To achieve the aforementioned functions, particularly quantum effect compensation, this module employs specific materials and structures in its physical implementation. In a preferred embodiment, a hafnium oxide (HfO2) interface layer is used at the interface or critical region of the bipolar transistor array. The typical thickness of this hafnium oxide interface layer is approximately 2 nanometers. By introducing this material layer, the gate leakage current of the transistor can be effectively suppressed to 0.3 picoamperes per square micrometer (0.3 pA / μm). 2 This material characteristic reduces the unwanted tunneling probability by approximately 47% and is a crucial material basis for achieving "quantum effect compensation" and ensuring the module's reliable operation even with nanoscale processes.

[0032] The working principle of this module, particularly its logic in compensation control, is tightly coupled with the overall adaptive strategy of the system. One of its core algorithmic foundations is the classical formula for calculating the required reactive power compensation capacity. For example, the compensation capacity of this quantum effect compensation unit satisfies the following relationship:

[0033] in, This indicates the reactive power that needs to be compensated; P represents the active power of the circuit or system. This represents the power factor angle before compensation; This represents the target power factor angle after compensation.

[0034] In some implementations, depending on different application scenarios and performance requirements, this core structural module supports and drives two main compensation implementation methods. Its specific execution components can be regarded as functional extensions or controlled objects of the module: dynamic compensation scenario, in which the core structural module drives thyristor switching capacitors for instantaneous compensation through fast control logic. The response time of the thyristor switching capacitors is less than 20 milliseconds, which is suitable for situations with rapid load fluctuations; static compensation scenario, in which the core structural module controls dry capacitors or oil-immersed capacitor banks for fixed or step compensation. In order to suppress harmonics and ensure stable operation, a filter reactor with a reactance of 7% is usually configured in the compensation circuit.

[0035] It is worth noting that this core structural module occupies a central position in the overall circuit structure. For example, the input terminal is used to receive the signal that has been preliminarily processed by the "ultra-low frequency signal module"; the internal processing is based on the simulation calculations (such as four-quadrant multiplication) performed by components such as the "improved Gilbert module"; and the output and verification process is based on the output signal and overall performance modeled and tested by the "simulation experiment module" in the 0.1Hz-10Hz frequency band.

[0036] In other words, the core structural module of this application embodiment is an integrated structure that combines a specific material (such as hafnium oxide), a specific architecture (bipolar transistor array and quantum effect compensation unit), and a specific control algorithm (such as based on...). It is a high-performance signal processing and compensation core (computational logic). Through two optional compensation implementation methods, it transforms the calculated compensation strategy into actual electrical actions, thereby working in conjunction with other modules of the system to achieve highly stable adaptive polarity control and compensation for ultra-low frequency signals.

[0037] In some implementations, the simulation experiment module is used to build circuit simulation models and test circuit performance in the 0.1 Hz to 10 Hz frequency band.

[0038] The simulation experiment module is the core of the circuit structure's design verification and performance evaluation. Its main purpose is to verify, optimize, and ensure that the overall circuit structure, composed of the "ultra-low frequency signal module" and the "core structure module," achieves the expected performance indicators by establishing an accurate simulation model and conducting systematic testing within a specified ultra-low frequency band before the circuit is put into actual manufacturing and application. This module is not an essential component of the final product circuit, but rather a key technical means for early design and performance assurance.

[0039] The simulation experiment module mainly consists of two core components: the construction of the circuit simulation model and performance testing within a specified frequency band. The construction of the circuit simulation model includes establishing a computer simulation model of the ultra-low frequency polarity adaptive circuit structure. In one specific implementation, SPICE (Simulation Program with Integrated Circuit Emphasis) or similar industry-standard circuit simulation software is used to create a corresponding simulation netlist based on the specific topology of the circuit and device parameters (such as the model of the bipolar transistor array, the capacitance characteristics of the hafnium oxide interface layer, and the parameters of the improved Gilbert module). This model aims to simulate the physical behavior of the circuit in actual operation as realistically as possible. The performance testing within the specified frequency band includes: after the SPICE model is established, the module performs systematic simulation tests on the circuit model within a specific ultra-low frequency band from 0.1 Hz to 10 Hz. This frequency band is the target operating frequency band of this application embodiment, and the test aims to verify the key performance of the circuit within this frequency band, such as the correctness of the polarity adaptive function, the accuracy of signal processing, the effectiveness of compensation actions, and overall stability. This process can replace or significantly reduce the high cost and difficulty of testing physical circuits in the ultra-low frequency band.

[0040] This simulation module, together with other functional modules of the circuit, forms a closed loop for design and verification. Its simulation and testing object is a complete circuit design scheme consisting of an "ultra-low frequency signal module," a "core structure module," and an "improved Gilbert module." Based on design specifications, this simulation module verifies whether the functions, performance, and collaborative working states of the aforementioned modules meet the invention requirements, such as verifying the compensation algorithm (based on...). The simulation tests demonstrate the performance of the computations in the simulation environment. Performance bottlenecks or design flaws discovered through simulation testing can be fed back to adjust and optimize the design parameters of the modules mentioned above (e.g., adjusting the thickness of the hafnium oxide interface layer, optimizing filter parameters, etc.), forming an iterative design process.

[0041] To ensure the accuracy and reliability of simulation experiments, in one specific implementation, the module's operation requires support from specific technical conditions. This includes using high-precision testing equipment (in the simulation environment, this refers to high-precision simulator settings; in subsequent physical verification, it corresponds to high-precision measuring instruments) to cross-validate key parameters of the simulation results or physical prototypes (such as equivalent noise voltage, temperature drift coefficient, etc.) to ensure the performance consistency of the final circuit and the deliverability of the design. Furthermore, the module's workflow can collaborate with supporting software systems to improve the efficiency of design verification through automated test scripts, data analysis tools, and other means.

[0042] In other words, the simulation experiment module of this application provides a crucial virtual verification environment for the design of the core circuit structure by constructing an accurate SPICE simulation model and conducting system testing within the target frequency band of 0.1Hz-10Hz. This makes performance prediction and optimization of circuit design under nanoscale processes and ultra-low frequency conditions possible, and is a necessary technical guarantee to ensure that the entire invention can be transformed from a design concept into a feasible, high-performance circuit product.

[0043] In some implementations, the input impedance of this improved Gilbert module is not less than 10Ω. 12 The equivalent noise voltage of this improved Gilbert module is no greater than 5nV / √Hz at a frequency of 1Hz, and the temperature drift coefficient of this improved Gilbert module is less than 0.1μV / ℃.

[0044] The improved Gilbert module is the core analog signal processing and arithmetic unit in this embodiment. It is a circuit module based on the classic Gilbert multiplier unit structure, specifically optimized and improved for ultra-low frequency, high-precision applications. Its main function is to perform high-precision analog multiplication operations, particularly implementing four-quadrant product conversion in this circuit. It multiplies or performs cross-conductor linear operations on input signals (such as voltage or current signals processed by the aforementioned modules) according to specific mathematical relationships, outputting accurate processing results for subsequent compensation and control logic.

[0045] For example, the module's "improved" features are specifically reflected in its superior static and dynamic performance indicators, which form the basis for its high-precision processing in ultra-low frequency (0.1Hz-10Hz) applications: extremely high input impedance, with an input impedance of not less than 10 Ω. 12Ohms (Ω). This characteristic minimizes the module's impact on the preceding circuitry, drawing almost no current from it, thus ensuring signal integrity, especially for ultra-low frequency weak signals, during transmission. Extremely low equivalent input noise: At 1 Hz, its equivalent input noise voltage density is no higher than 5 nanovolts per square hertz (nV / √Hz). This low noise characteristic is crucial for processing near-DC ultra-low frequency signals, effectively suppressing the overwhelming effect of circuit noise on the useful signal and ensuring a high signal-to-noise ratio. Extremely low thermal drift coefficient, with a temperature drift coefficient less than 0.1 microvolts per degree Celsius (μV / ℃). This characteristic ensures that the module's output stability is extremely insensitive to temperature changes, thus adapting to ambient temperature fluctuations and enabling long-term, stable, high-precision measurement and processing.

[0046] For example, the physical and mathematical principles underlying the module's core computational functions are as follows. In a preferred embodiment, the module's output current... With input current The functional relationship between them is expressed as follows:

[0047] in, Indicates the output current; This indicates the cutoff frequency, typically 0.01 Hz. This refers to the thermal compensation capacitor, a key component inside the module used to achieve low temperature drift characteristics; Indicates the amount of electron charge; Represents the Boltzmann constant; Represents thermodynamic temperature; Represents the elementary charge; Both represent input current; Thermovoltage, representing the thermal voltage, is a fundamental parameter in semiconductor physics. This relationship shows that the output current is proportional to the logarithm of the ratio of the two input currents, and introduces the cutoff frequency and thermal compensation mechanism. It is the core of the mathematical model that enables this module to achieve "adaptive" and "high stability" characteristics.

[0048] It is worth noting that the improved Gilbert module does not operate independently, but is deeply integrated as a key computational subunit within the "core structural module." Its high input impedance, low noise, and low temperature drift directly support the overall performance of the core structural module. Its precise four-quadrant product transformation function enables the core structural module to implement complex compensation algorithms (such as those based on...). The calculations rely on fundamental mathematical units. Its excellent temperature stability also benefits from the synergistic design with structural features such as the hafnium oxide interface layer.

[0049] In other words, the improved Gilbert module of this application embodiment is a high-performance analog multiplier deeply optimized for ultra-low frequency applications. Through specific circuit design, it achieves extremely high input impedance, extremely low noise and temperature drift, and strictly follows a specific transconductance linear function with thermal compensation capacitor and cutoff frequency as key parameters. These improvements enable it to serve as the core computing unit in the ultra-low frequency polarity adaptive circuit structure of this application embodiment, stably and accurately processing ultra-low frequency signals, and providing crucial analog signal computation guarantees for the adaptive compensation function of the entire system.

[0050] This application's embodiments effectively achieve circuit miniaturization and high integration by employing an ultra-low frequency signal module with a polarized circuit topology and a feature size on the nanometer scale, making it easy to deploy in modern precision chip systems. In the core structural module, a bipolar transistor array is responsible for signal compensation, while a quantum effect compensation unit is specifically designed to suppress non-ideal effects such as quantum tunneling at the nanometer scale. The two work together to significantly improve the long-term accuracy and extreme stability of signal processing. The simulation experiment module builds and tests circuit models in the target frequency band from 0.1 Hz to 10 Hz, greatly reducing R&D trial-and-error costs and accelerating product optimization cycles. The improved Gilbert module, with an input impedance of no less than 10¹²Ω, an equivalent noise voltage of no more than 5nV / √Hz at 1Hz, and a temperature drift coefficient of less than 0.1μV / ℃, ensures high-fidelity acquisition of weak ultra-low frequency signals and extremely low noise interference at the front end. At the same time, its excellent temperature characteristics ensure measurement consistency across the entire operating temperature range.

[0051] This application also discloses an operating method based on the aforementioned ultra-low frequency polarity adaptive circuit structure. This method is a control flow for operating the ultra-low frequency polarity adaptive circuit structure. Its core lies in ensuring high accuracy and stability of the circuit under ultra-low frequency (0.1Hz-10Hz) operating conditions through periodic self-calibration, dynamic parameter adjustment, and continuous performance monitoring. The method consists of three main steps forming a closed-loop control, and can trigger more refined optimization and compensation sub-steps based on real-time monitoring data. The method includes the following steps S1-S3.

[0052] Step S1: Initiate a self-calibration cycle every 60 seconds to compensate for voltage drift caused by electrode polarization.

[0053] Step S1 aims to periodically eliminate the DC voltage offset (i.e., voltage drift) introduced by electrode polarization in the circuit, which is crucial for maintaining the long-term accuracy of the ultra-low frequency signal measurement reference. Specifically, the circuit's control system (such as a microcontroller) is configured to automatically initiate a self-calibration cycle every 60 seconds. During this cycle, the circuit enters a calibration state, measuring and compensating for the voltage drift caused by electrode polarization through an internal reference and feedback mechanism, resetting the signal path to near zero bias.

[0054] In some implementations, step S1 further includes: activating an emergency calibration mode when an electrode polarization voltage drift exceeding ±300mV is detected.

[0055] In a preferred embodiment, step S1 further includes an emergency calibration mechanism: the control system continuously monitors the drift of the electrode polarization voltage. When the drift exceeds a preset threshold of ±300 millivolts (mV) in real time, the system immediately interrupts the normal cycle and activates the emergency calibration mode. This mode compensates for the voltage drift with a higher priority or faster convergence algorithm to prevent circuit malfunction or measurement errors caused by excessive drift under abnormal conditions.

[0056] Step S2: Adjust the compensation parameters in real time according to load changes.

[0057] Step S2 aims to dynamically adjust the compensation parameters of the circuit based on real-time changes in the load connected to the circuit, in order to maintain the best compensation effect. Specifically, the core structural module of the circuit uses its built-in algorithm to adjust the control parameters of the output to the compensation network (such as thyristor-switched capacitors) in real time according to feedback signals (such as load current and voltage phase) to adapt to load changes.

[0058] In some implementations, S2 further includes: monitoring tunneling current changes in real time through the quantum effect compensation unit, and automatically adjusting the bias voltage of the bipolar transistor array when the gate leakage current exceeds 0.3 picoamperes per square micrometer.

[0059] In a further optimized implementation, the adjustment process in step S2 incorporates microscopic physical state information from the "quantum effect compensation unit." Specifically, this unit monitors in real-time changes in tunneling current caused by the nanoscale structure. When the gate leakage current exceeds a set threshold of 0.3 picoamperes per square micrometer (pA / μm²), it indicates that the quantum tunneling effect may begin to affect the device linearity. At this point, the system automatically adjusts the bias voltage of the bipolar transistor array, shifting its operating point away from the sensitive region susceptible to quantum effects. This proactively maintains the linearity and stability of the circuit at the device physical level, serving as a microscopic supplement to macroscopic load compensation.

[0060] Step S3: Monitor circuit performance parameters in real time through the simulation experiment module.

[0061] Step S3 aims to track and record the performance of the entire circuit system in real time through a simulation experiment module or an equivalent monitoring circuit, providing data support for state assessment and long-term optimization. Specifically, the simulation experiment module (or its hardware-based monitoring unit) is used to monitor key circuit performance parameters in real time, such as the operating point voltage / current of each module, overall gain, noise spectral density, and temperature, ensuring that the system operates within the designed parameter range.

[0062] In some implementations, S3 further includes: calculating the power factor change before and after compensation in real time; automatically recording the operating parameters when the power factor increases from 0.75 to 0.95, indicating a 12% reduction in line loss; and establishing an optimization parameter library.

[0063] In a preferred embodiment, step S3 further includes an energy efficiency assessment and learning function: the system calculates and compares the power factor changes before and after compensation in real time. When the power factor is successfully improved from 0.75 before compensation to 0.95 after compensation, it indicates that the compensation effect is significant. At this time, the system automatically records the complete set of operating parameters (such as load conditions, compensation capacity, operating points of each module, etc.) corresponding to achieving this effect, and stores the successful parameter combination in an optimized parameter library. A typical technical effect recorded in this process is a corresponding reduction of approximately 12% in line loss. This optimized parameter library can be used for rapid parameter recall when encountering similar operating conditions in the future, realizing experience learning and continuous performance optimization.

[0064] In some implementations, to ensure the accuracy of the core computing unit (improved Gilbert module) is unaffected by temperature, the method also includes a parallel thermal stability maintenance step. For example, the method further includes: monitoring circuit temperature changes in real time using a thermal compensation capacitor, and activating a temperature compensation mechanism when the temperature drift coefficient exceeds 0.1 microvolts per degree Celsius to ensure the accuracy of the four-quadrant product conversion. Specifically, for example, the temperature changes of the circuit are monitored in real time using the integrated thermal compensation capacitor and its associated sensing circuitry. When the circuit temperature drift coefficient calculated based on the real-time monitoring data exceeds a threshold of 0.1 microvolts per degree Celsius (μV / ℃), it indicates that the temperature change has begun to have a non-negligible impact on accuracy. At this point, the system activates the temperature compensation mechanism, which may include adjusting the reference voltage, correcting temperature-related terms in the algorithm, etc., to ensure that the output accuracy of the four-quadrant product conversion module remains within a specified range.

[0065] This operating method achieves intelligent operation and maintenance of this ultra-low frequency polarity adaptive circuit structure through a closed-loop process including periodic reference calibration (S1), load follow-up compensation (S2), and system performance learning (S3), combined with possible emergency calibration, quantum effect feedforward adjustment, and thermal compensation mechanisms. This method not only solves long-term stability issues such as electrode polarization and temperature drift, but also enables the circuit to adapt to load changes and accumulate optimized operating experience through real-time monitoring and parameter learning, thereby comprehensively ensuring the reliability, accuracy, and energy efficiency of the circuit in demanding ultra-low frequency applications.

[0066] In summary, the ultra-low frequency polarity adaptive circuit structure of this application is innovative in technology, widely applicable, easy to maintain, and forward-looking in terms of environmental protection. It not only brings new technological breakthroughs to the field of ultra-low frequency signal processing but also provides efficient, reliable, and environmentally friendly solutions for related industries, possessing significant practical value and broad market prospects. In future research and development, the circuit structure of this application is expected to further integrate advanced digital signal processing technologies to achieve more advanced signal analysis and processing capabilities. By introducing machine learning algorithms, the circuit will be able to automatically adjust parameters to adapt to different signal characteristics and environmental changes, thereby achieving intelligent signal processing. Furthermore, with the rapid development of IoT technology, the circuit structure of this application is also expected to be combined with IoT devices to achieve remote monitoring and control. This will bring revolutionary changes to fields such as telemedicine, smart homes, and industrial automation, making devices more intelligent, networked, and automated. In terms of education and training, the circuit structure of this application can serve as a teaching tool to help students and engineers better understand the principles and applications of ultra-low frequency signal processing. Through practical operation and experiments, learners can deeply master key skills such as circuit design, signal analysis, and system integration. Finally, the circuit structure of this application embodiment has enormous potential for commercial applications. Its high efficiency, low power consumption, and high stability make it an ideal choice for electronic equipment manufacturers and system integrators. With continuous technological advancements and growing market demand, the circuit structure of this application embodiment is expected to be applied in a wider range of fields, creating greater value for users. In terms of promotion and marketing strategies, the circuit structure of this application embodiment will collaborate with industry leaders to jointly develop customized solutions to meet the needs of specific industries. Establishing strategic partnerships can accelerate product market penetration and continuously optimize the circuit structure through collaborative development to adapt to ever-changing market demands. To ensure continued technological leadership, the circuit structure of this application embodiment will invest continuous R&D resources to track the latest technological trends and scientific discoveries. Through continuous technological innovation, the circuit structure will maintain its leading position in the field of ultra-low frequency signal processing and bring continuous technological progress and performance improvements to users. Regarding social responsibility, the circuit structure of this application embodiment will be committed to promoting sustainable development and environmental protection. By reducing energy consumption and waste generation, the circuit structure will help reduce its environmental impact and promote the development of green technologies.

[0067] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of this application, and this application is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this application, and these modifications and improvements are also considered to represent the scope of protection of this application.

Claims

1. A low-frequency polarity adaptive circuit structure, characterized in that, include: An ultra-low frequency signal module has a polarized circuit topology, and the feature size of the circuit elements of the ultra-low frequency signal module is on the nanometer scale. The core structural module includes a bipolar transistor array and a quantum effect compensation unit, wherein the bipolar transistor array and the quantum effect compensation unit are used for signal compensation and stability control, respectively. The simulation experiment module is used to build circuit simulation models and test circuit performance in the 0.1 Hz to 10 Hz frequency band; An improved Gilbert module, wherein the input impedance of the improved Gilbert module is not less than 10Ω. 12 The equivalent noise voltage of the improved Gilbert module is no greater than 5nV / √Hz at a frequency of 1Hz, and the temperature drift coefficient of the improved Gilbert module is less than 0.1μV / ℃.

2. The ultra-low frequency polarity adaptive circuit structure according to claim 1, characterized in that, The core structural module includes a hafnium oxide interface layer with a thickness of 2 nanometers, which is configured to suppress the gate leakage current to 0.3 picoamperes per square micrometer.

3. The ultra-low frequency polarity adaptive circuit structure according to claim 1, characterized in that, The ultra-low frequency polarity adaptive circuit structure includes a thyristor-switched capacitor in the dynamic compensation scenario, and the response time of the thyristor-switched capacitor is less than 20 milliseconds; the ultra-low frequency polarity adaptive circuit structure includes a dry capacitor or an oil-immersed capacitor in the static compensation scenario, and is configured with a filter reactor with a reactance of 7%.

4. The ultra-low frequency polarity adaptive circuit structure according to claim 1, characterized in that, The improved Gilbert module is used for four-quadrant product transformation, and the relationship between the output current and the input current of the improved Gilbert module is shown in the following expression: in, Indicates the output current; Indicates the cutoff frequency; Indicates a thermal compensation capacitor; Indicates the amount of electron charge; Represents the Boltzmann constant; Represents thermodynamic temperature; Represents the elementary charge; Both represent input current.

5. The ultra-low frequency polarity adaptive circuit structure according to claim 1, characterized in that, The compensation capacity of the quantum effect compensation unit satisfies the following relationship: in, This indicates the reactive power that needs to be compensated; P represents the active power of the circuit or system. This represents the power factor angle before compensation; This represents the target power factor angle after compensation.

6. An operating method, implemented based on the ultra-low frequency polarity adaptive circuit structure according to any one of claims 1 to 5, characterized in that, include: Step S1: Initiate a self-calibration cycle every 60 seconds to compensate for voltage drift caused by electrode polarization; Step S2: Adjust the compensation parameters in real time according to load changes; Step S3: Monitor circuit performance parameters in real time through the simulation experiment module.

7. The operating method according to claim 6, characterized in that, Step S1 further includes: Emergency calibration mode is activated when an electrode polarization voltage drift exceeding ±300mV is detected.

8. The operating method according to claim 6, characterized in that, S2 further includes: The quantum effect compensation unit monitors the tunneling current change in real time. When the gate leakage current exceeds 0.3 picoamperes per square micrometer, the bias voltage of the bipolar transistor array is automatically adjusted.

9. The operating method according to claim 6, characterized in that, S3 further includes: The system calculates the power factor change before and after compensation in real time. When the power factor increases from 0.75 to 0.95, it automatically records the operating parameters that reduce line loss by 12% and establishes an optimization parameter library.

10. The operating method according to claim 6, characterized in that, The method further includes: The circuit temperature changes are monitored in real time by using a thermal compensation capacitor. When the temperature drift coefficient exceeds 0.1 microvolts per degree Celsius, a temperature compensation mechanism is activated to ensure the accuracy of the four-quadrant product conversion.

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