Intelligent regulation and control method and system for multi-stage digital processing high-voltage feedback signal

Abstract

The invention relates to the technical field of electric power systems, in particular to an intelligent regulation and control method and system for high-voltage feedback signals of multistage digital processing. A high-sensitivity sensor is used for collecting signals generated by high-voltage equipment, and collected analog signals are converted into digital signals through an analog-to-digital converter; filtering the digital signal through a digital signal processor, and transmitting the filtered signal to a microprocessor for analysis; and according to an analysis result of the microprocessor, a control instruction is generated through the decision algorithm module, and a feedback control signal is output after the control instruction is converted by the digital-to-analog converter. A multi-stage filtering strategy is adopted, including combined application of Kalman filtering and an adaptive filtering algorithm, and accurate processing is carried out on signals in a complex noise environment; intelligent closed-loop control is realized through cooperation of a multi-level decision-making mechanism constructed by an expert system and fuzzy logic and a self-learning optimization function; a modular design and a standardized interface are adopted, and a high-speed bus architecture is combined, so that high integration of the system is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method and system for intelligently controlling high-voltage feedback signals using multi-level digital processing. Background Art

[0002] With the continuous improvement of the intelligent level of power systems, high-voltage feedback signal processing technology plays an increasingly important role in the monitoring, diagnosis and protection of power equipment. At present, this technology has been widely used in the status monitoring and fault warning of high-voltage equipment such as transformers and circuit breakers, and its signal processing performance directly affects the reliability and safety of the entire system.

[0003] In the prior art, high-voltage feedback signal processing mainly uses analog signal processing technology. This technical solution collects and processes the signals generated by high-voltage equipment through analog circuits. Although the structure is relatively simple, it has several significant defects. First, analog signals are easily interfered by environmental noise, resulting in a significant decrease in the stability and accuracy of signal processing; second, due to the lack of effective digital processing methods, the long-term stability of the signal is poor, and it is difficult to adapt to the complex and changing conditions in the high-voltage environment.

[0004] In terms of system integration, traditional analog signal processing technology also has obvious shortcomings. On the one hand, analog signal processing components are usually large in size and have low system integration, which is not conducive to the miniaturization design of equipment; on the other hand, the system has high maintenance costs, and its reliability will gradually decrease with the increase of operating time, which poses a challenge to the long-term stable operation of the system.

[0005] In addition, the existing analog signal processing technology also faces bottlenecks in terms of upgrade scalability and intelligence. Due to the inherent limitations of analog technology, it is difficult for the system to achieve flexible functional upgrades and expansions. At the same time, when processing high-speed or high-frequency signals, it is often difficult to achieve the required accuracy and response speed, which seriously restricts the demand for the power system to develop to a higher level of intelligence.

[0006] The existence of the above problems makes it difficult for traditional analog signal processing technology to meet the requirements of modern power systems for high-performance and high-reliability signal processing, and it is urgent to develop new digital processing solutions. Summary of the invention

[0007] In view of the problems existing in the prior art, the present invention is proposed.

[0008] Therefore, the problem to be solved by the present invention is how to solve the problem that the existing analog signal processing technology is difficult to overcome the interference of environmental noise and lacks an effective anti-interference mechanism, resulting in low signal processing accuracy. At the same time, due to the inherent instability of analog signals, the performance of the system will gradually degrade after long-term operation, affecting the overall signal processing reliability.

[0009] The existing technology has the problems of low system integration and high power consumption. Since analog processing circuits are generally large in size and have high power consumption, it is not conducive to the miniaturization and energy-saving design of the system. In addition, the maintenance cost of the system increases with the increase of operating time, which brings great challenges to the long-term operation and maintenance of the equipment.

[0010] Existing technologies have obvious deficiencies in intelligence and scalability. The analog signal processing system lacks a flexible upgrade path and is difficult to adapt to the evolving needs of the power system. At the same time, when processing high-speed or high-frequency signals, the system's response speed and processing accuracy often cannot meet actual application needs, limiting the system's scope of application.

[0011] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0012] In a first aspect, an embodiment of the present invention provides a multi-stage digitally processed high-voltage feedback signal intelligent control method, which includes using a highly sensitive sensor to collect signals generated by high-voltage equipment, and converting the collected analog signals into digital signals via an analog-to-digital converter;

[0013] Filtering the digital signal by a digital signal processor, and transmitting the filtered signal to a microprocessor for analysis;

[0014] According to the analysis results of the microprocessor, the control instructions are generated by the decision algorithm module, and the feedback control signals are output after conversion by the digital-to-analog converter.

[0015] As a preferred solution of the multi-stage digital processing high-voltage feedback signal intelligent control method described in the present invention, the filtering processing includes: using the Kalman filtering algorithm to perform preliminary noise removal on the digital signal; using an adaptive filtering algorithm to further optimize the signal; and dynamically adjusting the filtering parameters according to the signal characteristics.

[0016] As a preferred solution of the multi-level digital processing high-voltage feedback signal intelligent control method described in the present invention, the analysis performed by the microprocessor includes: extracting features from the filtered digital signal; demodulating and analyzing the signal based on the extracted features; and generating a state evaluation result.

[0017] As a preferred solution of the multi-level digital processing high-voltage feedback signal intelligent control method described in the present invention, the decision algorithm module includes: performing multi-level judgment based on state evaluation results; selecting corresponding control strategies according to the judgment results; and generating corresponding control instructions.

[0018] As a preferred solution of the multi-level digital processing high-voltage feedback signal intelligent control method described in the present invention, it also includes a real-time monitoring step: real-time monitoring of the operating status of each module of the system; recording key data and abnormal information; triggering an alarm mechanism when an abnormality is detected.

[0019] As a preferred solution of the multi-level digital processing high-voltage feedback signal intelligent control method described in the present invention, wherein: the modules are integrated into a single control unit, and the single control unit includes: a signal acquisition unit, a digital processing unit, a decision control unit and a monitoring unit; the units are interconnected through an internal bus to achieve rapid data interaction.

[0020] As a preferred solution of the multi-level digital processing high-voltage feedback signal intelligent control method described in the present invention, it also includes a user interaction step: providing a parameter configuration interface; displaying system operating status and alarm information; and receiving control instructions from operators.

[0021] In a second aspect, an embodiment of the present invention provides a multi-level digitally processed high-voltage feedback signal intelligent control system, which includes a signal acquisition module, which uses a highly sensitive sensor to collect signals generated by high-voltage equipment, and converts the collected analog signals into digital signals through an analog-to-digital converter;

[0022] A processing and analysis module filters the digital signal through a digital signal processor and transmits the filtered signal to a microprocessor for analysis;

[0023] The decision execution module generates control instructions through the decision algorithm module according to the analysis results of the microprocessor, and outputs feedback control signals after conversion by the digital-to-analog converter.

[0024] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the multi-level digital processing high-voltage feedback signal intelligent control method as described in the first aspect of the present invention are implemented.

[0025] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the multi-stage digital processing high-voltage feedback signal intelligent control method as described in the first aspect of the present invention are implemented.

[0026] The beneficial effects of the present invention are as follows: the present invention utilizes digital signal processing technology to improve the accuracy of signal processing and reduce noise interference and distortion in analog signal processing. The design of the digital system reduces the impact of environmental factors on signal stability and improves the long-term stable operation capability of the system. The programmability of the digital system makes system maintenance and upgrading more convenient and reduces maintenance costs. The multi-level parallel processing architecture is adopted to improve the system's response speed to high-voltage signals and adapt to the real-time requirements of the power system. The integrated decision algorithm module can realize adaptive adjustment and intelligent management, and improve the automation level of the system. Digital signal processing technology has advantages in energy consumption control and helps to achieve energy conservation and emission reduction. The digital signal processing component is small in size, easy to integrate the system, and conducive to the miniaturization and lightweight of the equipment. An intuitive user interface is provided to facilitate operator monitoring and management, and improve the user experience. Through these technical advantages, this patented technology is expected to be widely used in the field of high-voltage power equipment monitoring, and improve the operating efficiency and safety of the entire power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A flow chart of a method for intelligently controlling a high-voltage feedback signal with multi-level digital processing;

[0029] Figure 2 A computer device diagram for a high voltage feedback signal intelligent control method for multi-level digital processing;

[0030] Figure 3 This is a system operation diagram of the intelligent control method for high-voltage feedback signals using multi-level digital processing. DETAILED DESCRIPTION

[0031] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0032] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0033] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0034] Example 1

[0035] Reference Figures 1 to 2 , which is the first embodiment of the present invention, provides a multi-level digital processing high-voltage feedback signal intelligent control method, including:

[0036] S100: Use a highly sensitive sensor to collect signals generated by high-voltage equipment, and convert the collected analog signals into digital signals through an analog-to-digital converter;

[0037] In the embodiment of the present application, the signals of the high-voltage equipment include: voltage signals, current signals, temperature signals and vibration signals. The signals are collected by high-sensitivity sensors and converted by high-precision analog-to-digital converters.

[0038] Specifically, voltage signal acquisition uses a high-voltage probe with an accuracy better than 0.1% and a measuring range of 0-100kV; current signal acquisition uses a Hall effect current sensor with a measuring range of 0-1000A; temperature signal acquisition uses a PT100 platinum resistance temperature sensor with a measuring range of -50℃ to 200℃; vibration signal acquisition uses a piezoelectric accelerometer with a frequency response range of 0.5Hz-5kHz.

[0039] In an optional embodiment, the selection of the sensor needs to consider multiple factors: first, the measurement range must meet the actual working requirements, second, the sampling rate must be fast enough to capture transient changes, and third, it must have good anti-interference ability and environmental adaptability. Especially in high-voltage environments, the sensor must have sufficient insulation strength and anti-electromagnetic interference ability.

[0040] It should be noted that the selection of high-sensitivity sensors plays a decisive role in the overall performance of the system. By selecting high-precision sensors, combined with reasonable installation layout and shielding measures, the accuracy and reliability of signal acquisition can be effectively improved. At the same time, the combined application of multiple types of sensors can achieve comprehensive monitoring of the status of high-voltage equipment.

[0041] In the embodiment of the present application, the analog-to-digital converter adopts a 16-bit high-speed ADC with a sampling rate of up to 2MSPS and multi-channel synchronous sampling capability. The converter adopts a pipeline structure with a built-in sample-and-hold circuit and a reference source, which can achieve high-speed and high-precision signal conversion.

[0042] In an optional embodiment, the working mode of the analog-to-digital converter can be configured according to actual needs. For example, when it is necessary to monitor a rapidly changing voltage signal, a continuous sampling mode can be used with the sampling rate set to the maximum value; when monitoring a slowly changing signal such as temperature, an intermittent sampling mode can be used to reduce system power consumption. The trigger source of the converter can be selected from an internal clock or an external trigger signal.

[0043] In the embodiment of the present application, in order to improve the sampling accuracy, the input end of the analog-to-digital converter is configured with a signal conditioning circuit. The circuit includes a precision operational amplifier, an anti-aliasing filter and an overvoltage protection circuit. Among them, the cutoff frequency of the anti-aliasing filter is set to 0.4 times the sampling frequency to ensure that the requirements of the Nyquist sampling theorem are met.

[0044] In a preferred embodiment, the analog-to-digital conversion system also includes a self-calibration function. By regularly comparing with an internal reference source, the system can automatically compensate for conversion errors caused by temperature changes and long-term drift. In addition, the system also has a fault diagnosis function, which can detect fault conditions such as abnormal input signals and clock loss.

[0045] S200: filtering the digital signal through the digital signal processor, and transmitting the filtered signal to the microprocessor for analysis;

[0046] In the embodiment of the present application, the digital signal processor uses TI's TMS320F28335 chip, with a main frequency of 150MHz, a floating point unit, and supports a rich DSP instruction set. The processor is equipped with 1MB program memory and 256KB data memory, and can implement complex digital signal processing algorithms.

[0047] Specifically, the filtering process adopts a multi-stage filtering strategy: first, the high-frequency noise is removed by an IIR low-pass filter, then the power frequency interference is suppressed by a notch filter, and finally the wavelet transform is used for detail processing. The filter parameters can be dynamically adjusted according to the signal characteristics to obtain the best filtering effect.

[0048] In an optional embodiment, the system supports the combined application of multiple filtering algorithms. For example, for signals containing mutation components, a method combining median filtering and wavelet transform can be used; for signals with severe periodic interference, an adaptive notch filter can be used for processing. The type and parameters of the filter can be configured through the host computer software.

[0049] It should be noted that the performance of digital signal processing directly affects the measurement accuracy and response speed of the system. By adopting advanced DSP chips and optimized algorithms, the system can achieve low processing delay while ensuring processing accuracy. The application of multi-level filtering strategy further improves the anti-interference ability of the system.

[0050] S201: Filtering processing includes: using the Kalman filter algorithm to perform preliminary noise removal on the digital signal; using an adaptive filter algorithm to further optimize the signal; and dynamically adjusting the filter parameters according to the signal characteristics.

[0051] In the embodiment of the present application, the Kalman filter adopts a state space model, and its state vector includes two components: signal amplitude and rate of change. The covariance matrix of process noise and measurement noise is determined by offline calibration to balance the tracking performance and stability of the filter.

[0052] In a preferred embodiment, the Kalman filter algorithm is implemented in a recursive form, and the prediction and update steps are performed once per sampling period. To improve the computational efficiency, the matrix operation is processed in a fixed-point manner, and the DSP hardware multiplier is used to accelerate the computational process. The system also implements a filter divergence detection mechanism, which automatically resets the filter state when abnormal filter performance is detected.

[0053] It should be noted that the key to the Kalman filter algorithm lies in the accuracy of the model and the reasonable setting of parameters. Only by fully analyzing the system offline and conducting actual tests to determine the optimal model structure and parameter configuration can the best performance of the Kalman filter be brought into play.

[0054] In the embodiment of the present application, the adaptive filtering adopts the LMS (least mean square) algorithm, and the order of the filter can be configured to be 32-256. The step size parameter of the adaptive algorithm is automatically adjusted according to the power of the input signal, which not only ensures the convergence speed but also avoids the algorithm divergence.

[0055] In an optional embodiment, the weight update of the adaptive filter adopts a block processing method, that is, a block of data (such as 1024 points) is processed each time, which can improve the calculation efficiency. At the same time, the system realizes the real-time calculation of multiple evaluation indicators, including the signal-to-noise ratio and mean square error after filtering, which are used to monitor the performance of the filter.

[0056] S202: The microprocessor performs analysis including: extracting features from the filtered digital signal; demodulating and analyzing the signal based on the extracted features; and generating a state assessment result.

[0057] In the embodiment of the present application, feature extraction adopts a multi-dimensional analysis method, including: time domain features (mean, variance, peak factor, etc.), frequency domain features (spectral analysis, harmonic content, etc.) and time-frequency joint features (wavelet packet decomposition coefficients). These features are calculated in real time through an optimized algorithm to provide a basis for subsequent state evaluation.

[0058] In a preferred embodiment, the signal demodulation adopts digital phase-sensitive demodulation technology, which can accurately extract the amplitude and phase information of the signal. The system supports multiple demodulation modes: synchronous demodulation, orthogonal demodulation and envelope detection, and the appropriate demodulation mode can be selected according to the characteristics of different types of signals. The demodulation parameters (such as carrier frequency, filter bandwidth, etc.) can be dynamically adjusted through the configuration file.

[0059] It should be noted that feature extraction and signal demodulation are important foundations for state assessment. By selecting appropriate feature indicators and demodulation methods, effective information contained in the signal can be effectively extracted. The system adopts a parallel processing architecture to ensure that feature calculation and signal demodulation can be completed in real time.

[0060] S300: According to the analysis result of the microprocessor, a control instruction is generated through the decision algorithm module, and a feedback control signal is output after conversion by a digital-to-analog converter.

[0061] In the embodiment of the present application, the decision algorithm module establishes a complete state assessment and control decision mechanism based on expert system and fuzzy logic. The system sets up multiple decision rule bases, including normal state rules, warning state rules and fault state rules. Each rule contains a condition part and an action part, and the system makes the final control decision through rule reasoning.

[0062] In an optional embodiment, the decision-making process is divided into three levels: the first level is threshold judgment, which compares the thresholds of various characteristic indicators; the second level is comprehensive evaluation, which calculates the system status based on fuzzy rules; the third level is control decision, which generates corresponding control instructions. The system also has self-learning capabilities and can optimize decision rules based on historical data.

[0063] S301: The decision algorithm module includes: performing multi-level judgment based on the state evaluation result; selecting the corresponding control strategy according to the judgment result; and generating the corresponding control instruction.

[0064] In the embodiment of the present application, the multi-level judgment adopts the hierarchical analysis method to weight each evaluation index according to its importance. The system sets three judgment levels: the primary judgment focuses on the over-limit situation of basic parameters (such as voltage and current); the intermediate judgment analyzes the change trend and correlation of parameters; the advanced judgment combines historical data for pattern recognition.

[0065] In a preferred embodiment, the control strategy library contains a variety of preset control schemes, such as normal regulation strategy, fault isolation strategy, emergency protection strategy, etc. The system automatically selects the most suitable control strategy based on the judgment result, and can optimize the strategy online based on the actual control effect.

[0066] It should be noted that the reliability of the decision-making algorithm is crucial to the safe operation of the system. By establishing a sound judgment mechanism and control strategy, combined with real-time effect evaluation and optimization adjustment, it can be ensured that the system can make correct control decisions under various working conditions.

[0067] S302: Also includes a real-time monitoring step: real-time monitoring of the operating status of each module of the system; recording key data and abnormal information; triggering an alarm mechanism when an abnormality is detected.

[0068] In the embodiment of the present application, real-time monitoring adopts a distributed architecture, and monitoring points are set in each functional module, including: ADC conversion status, DSP processing load, communication link quality, etc. The monitoring data is transmitted to the monitoring center in real time through a high-speed internal bus to achieve all-round system status monitoring.

[0069] In an optional embodiment, the abnormality detection mechanism includes two levels: the hardware level is implemented by a watchdog circuit and a redundant detection circuit; the software level is implemented by a state machine and timeout detection. Once an abnormality is detected, the system immediately initiates the corresponding protection action and notifies the maintenance personnel in a variety of ways (sound and light alarm, SMS notification, log record, etc.).

[0070] S303: Each module is integrated into a single control unit, which includes: a signal acquisition unit, a digital processing unit, a decision control unit and a monitoring unit; each unit is interconnected through an internal bus to achieve rapid data interaction.

[0071] In the embodiment of the present application, the single control unit adopts a modular design, and each functional unit adopts a standardized interface to facilitate maintenance and upgrading. The system adopts a multi-layer PCB design to arrange the digital circuit and analog circuit in layers to effectively reduce mutual interference. The power supply adopts a multi-channel independent power supply solution to ensure the power supply reliability of key modules.

[0072] Specifically, the internal bus adopts a high-speed serial bus architecture and supports multiple bus protocols: data bus: adopts a 32-bit parallel bus with an operating frequency of 100MHz; control bus: adopts a CAN bus and supports priority arbitration; status bus: adopts an SPI bus for fast status query. In a preferred embodiment, the system also implements an intelligent power management mechanism. Each functional unit can enter different working modes (normal mode, low power mode, standby mode, etc.) according to work requirements, thereby achieving optimized management of energy consumption. The system has a power-off protection function, which automatically saves important data when the power supply is abnormal.

[0073] It should be noted that the highly integrated system design not only reduces the volume and cost of the system, but also improves the reliability of the system. Through reasonable circuit layout and perfect electromagnetic compatibility design, it is ensured that each functional unit can work stably. The standardized interface design facilitates the expansion and upgrade of the system.

[0074] S304: Also includes user interaction steps: providing a parameter configuration interface; displaying system operation status and alarm information; receiving control instructions from operators.

[0075] In the embodiment of the present application, the user interaction system adopts a three-layer architecture: display layer: using a 7-inch TFT LCD display with a resolution of 1024×600 and supporting touch operation; control layer: implementing human-computer interaction logic, processing user input and interface refresh; data layer: managing system configuration and operation data.

[0076] Specifically, the parameter configuration interface is divided into multiple functional areas: system parameter area: set basic parameters such as sampling rate and filtering parameters; alarm parameter area: configure various alarm thresholds and alarm methods; control parameter area: set control strategies and control parameters; communication parameter area: configure communication interface and protocol parameters.

[0077] In an optional embodiment, the system operation status is displayed in a graphical manner, including: real-time waveform display: supporting simultaneous display of multi-channel waveforms, with zoom and cursor measurement functions; trend curve display: displaying the historical change trends of key parameters; status indication display: using a dashboard and indicator light to intuitively display the system status; alarm information display: real-time display of current alarms and historical alarm records.

[0078] It should be noted that a good human-computer interaction interface is crucial to the practical application of the system. Through intuitive display and convenient operation, the operability and maintenance efficiency of the system can be greatly improved. The system supports authority management, and users of different levels have different operating authorities to ensure the security of system operation.

[0079] In the specific implementation of this application, the following core devices are used in each functional module of the system: microcontroller: STM32H743, main frequency 480MHz, with hardware floating-point unit; ADC: ADS8688, 16-bit resolution, sampling rate 500kSPS; DSP: TMS320F28335, main frequency 150MHz; FPGA: Xilinx Artix-7, used to achieve high-speed data acquisition and processing; LCD controller: ST7796S, supporting 8-bit / 16-bit parallel interface; memory: 1GB DDR3 SDRAM, used for data caching; 8MB Flash, used for program storage; 32GB SD card, used for data recording.

[0080] The selection of these components is based on strict performance evaluation and actual testing to ensure that the system can operate stably and reliably. Key components are all industrial-grade products with a wide operating temperature range and strong anti-interference ability.

[0081] Furthermore, this embodiment also provides a multi-level digital processing high-voltage feedback signal intelligent control system, including:

[0082] The signal acquisition module uses a highly sensitive sensor to collect the signal generated by the high-voltage equipment, and converts the collected analog signal into a digital signal through an analog-to-digital converter;

[0083] A processing and analysis module filters the digital signal through a digital signal processor and transmits the filtered signal to a microprocessor for analysis;

[0084] The decision execution module generates control instructions through the decision algorithm module according to the analysis results of the microprocessor, and outputs feedback control signals after conversion by the digital-to-analog converter.

[0085] In summary, by using a combination of high-sensitivity sensors and high-precision analog-to-digital converters, the synchronous acquisition and precise conversion of multiple types of signals (voltage, current, temperature, vibration) are achieved. This solution not only solves the interference problem in traditional analog acquisition, but also achieves comprehensive monitoring of the working status of high-voltage equipment while ensuring measurement accuracy through the fusion analysis of multi-dimensional signals, ultimately achieving anti-interference capabilities and measurement stability that exceed the expectations of traditional technologies.

[0086] By adopting the multi-level filtering strategy of "Kalman filtering + adaptive filtering" and cooperating with the dynamic parameter adjustment mechanism, we can achieve hierarchical processing of different types of noise and gradual improvement of signal quality. This innovative filtering architecture not only solves the problem that traditional single filtering methods are difficult to deal with complex noise, but also improves the environmental adaptability of the system through parameter adaptive adjustment, and ultimately achieves significant breakthroughs in signal processing accuracy and real-time performance.

[0087] By building a multi-level decision-making mechanism based on expert systems and fuzzy logic, combined with self-learning optimization functions, intelligent closed-loop control from state evaluation to control strategy generation is achieved. This solution breaks through the limitations of the single function of traditional controllers. By introducing intelligent decision-making algorithms, it not only improves the system's adaptive ability, but also realizes dynamic optimization of control strategies, achieving control accuracy and reliability that exceeds expectations.

[0088] By adopting modular design and standardized interfaces, combined with a high-speed internal bus architecture, the high integration and efficient coordination of each functional unit is achieved. This design not only greatly reduces the system volume and power consumption, but also ensures the stable operation of each module through reasonable electromagnetic compatibility design, ultimately achieving a qualitative leap in system integration and reliability.

[0089] By designing a layered interactive architecture and a graphical display interface, the integrated management of system parameter configuration, status monitoring, alarm prompts and other functions is achieved. This design breaks through the limitations of traditional systems that are complex to operate and difficult to maintain, and greatly improves the operability and maintenance efficiency of the system through an intuitive operating interface and perfect authority management.

[0090] Example 2

[0091] Reference Figure 2 - Figure 3 , which is the second embodiment of the present invention.

[0092] The core principle of the present invention is to use digital signal processing (DSP) algorithms to accurately sample, quantize and filter high-voltage signals. By using a high-precision analog-to-digital converter (ADC) to convert analog signals into digital signals, combined with advanced digital filtering technology, noise interference can be effectively removed and the signal-to-noise ratio of the signal can be improved. In addition, the patented technology adopts a multi-level signal processing architecture to improve the response speed and processing power of the system through parallel processing. Taking advantage of the advantages of digital signal processing, this technical solution is also easy to program, upgrade and maintain, and can achieve adaptive adjustment and intelligent management to meet the requirements of high-voltage signal processing in terms of accuracy, stability and intelligence.

[0093] Signal acquisition: Use a highly sensitive sensor (marked as S1) to collect the signal generated by the high-voltage equipment. The sensor is connected to the analog-to-digital converter (ADC, marked as A1), which is responsible for converting the analog signal into a digital signal.

[0094] Analog-to-digital conversion: ADC (A1) converts analog signals into digital signals at a high sampling rate, ensuring that the original information of the signal is preserved.

[0095] Digital filtering: The digital signal is filtered by a digital signal processor (DSP, marked as P1) to remove noise and interference and improve the signal-to-noise ratio. The DSP (P1) uses specific algorithms, such as Kalman filtering or adaptive filtering, to adapt to different signal characteristics.

[0096] Signal Processing: The filtered digital signal is transmitted to the microprocessor (CPU, marked as C1), where more complex signal processing tasks such as demodulation and analysis of the signal are performed.

[0097] Data processing and decision-making: The processed signal is sent to the decision algorithm module (marked as D1), which is responsible for analyzing the signal characteristics, determining the system status, and generating corresponding control instructions.

[0098] Feedback and control: The control command is converted into an analog signal through a digital-to-analog converter (DAC, marked as A2) for feedback control of the high-voltage equipment to achieve stable operation of the system.

[0099] System monitoring: The status of the entire system is monitored in real time by the monitoring unit (marked as M1) to ensure the reliability and safety of the system.

[0100] User Interface: The system provides a user interface (UI, marked as I1) that allows operators to monitor system status, adjust parameters, and receive system alarms and notifications.

[0101] Attached Figure 3 S1: high voltage signal sensor; A1: analog-to-digital converter; P1: digital signal processor; C1: microprocessor; D1: decision algorithm module; -A2: digital to analog converter; M1: system monitoring unit; 11: user interface.

[0102] In practical applications, this technical solution can be applied to high-voltage equipment monitoring in power systems, such as transformers and circuit breakers. Through precise signal processing, real-time monitoring of equipment status and fault diagnosis can be achieved, thereby improving system reliability and safety.

[0103] Example 3

[0104] This embodiment also provides a computer device, which is suitable for a multi-level digital processing high-voltage feedback signal intelligent control method, including a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement a forced oscillation detection and positioning method for a distribution network as proposed in the above embodiment.

[0105] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, a forced oscillation detection and positioning method for a distribution network is implemented as proposed in the above embodiment.

[0106] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0107] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0108] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0109] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0110] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0111] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A multi-level digital processing high-voltage feedback signal intelligent control method, characterized in that: Including, using a highly sensitive sensor to collect the signal generated by the high-voltage equipment, and converting the collected analog signal into a digital signal through an analog-to-digital converter; Filtering the digital signal by a digital signal processor, and transmitting the filtered signal to a microprocessor for analysis; According to the analysis results of the microprocessor, the control instructions are generated by the decision algorithm module, and the feedback control signals are output after conversion by the digital-to-analog converter.

2. The multi-level digital processing high-voltage feedback signal intelligent control method according to claim 1, characterized in that: The filtering process includes: using a Kalman filtering algorithm to perform preliminary noise removal on a digital signal; using an adaptive filtering algorithm to further optimize the signal; and dynamically adjusting filtering parameters according to signal characteristics.

3. The multi-level digital processing high-voltage feedback signal intelligent control method according to claim 2, characterized in that: The analysis performed by the microprocessor includes: extracting features from the filtered digital signal; demodulating and analyzing the signal based on the extracted features; and generating a state evaluation result.

4. The multi-level digital processing high-voltage feedback signal intelligent control method according to claim 3, characterized in that: The decision algorithm module includes: performing multi-level judgment based on the state evaluation result; selecting the corresponding control strategy according to the judgment result; and generating the corresponding control instruction.

5. The multi-level digital processing high-voltage feedback signal intelligent control method according to claim 4, characterized in that: It also includes real-time monitoring steps: real-time monitoring of the operating status of each module of the system; recording key data and abnormal information; triggering an alarm mechanism when an abnormality is detected.

6. The multi-level digital processing high-voltage feedback signal intelligent control method according to claim 5, characterized in that: The modules are integrated into a single control unit, which includes a signal acquisition unit, a digital processing unit, a decision control unit and a monitoring unit; the units are interconnected through an internal bus to achieve rapid data interaction.

7. The multi-level digital processing high-voltage feedback signal intelligent control method according to claim 6, characterized in that: It also includes user interaction steps: providing a parameter configuration interface; displaying system operating status and alarm information; and receiving control instructions from operators.

8. A multi-level digital processing high-voltage feedback signal intelligent control system, based on the multi-level digital processing high-voltage feedback signal intelligent control method according to any one of claims 1 to 7, characterized in that: It also includes a signal acquisition module, which uses a highly sensitive sensor to collect signals generated by high-voltage equipment and converts the collected analog signals into digital signals through an analog-to-digital converter; A processing and analysis module filters the digital signal through a digital signal processor and transmits the filtered signal to a microprocessor for analysis; The decision execution module generates control instructions through the decision algorithm module according to the analysis results of the microprocessor, and outputs feedback control signals after conversion by the digital-to-analog converter.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the multi-stage digital processing high-voltage feedback signal intelligent control method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the multi-stage digital processing high-voltage feedback signal intelligent control method according to any one of claims 1 to 7 are implemented.

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