Power optical fiber on-line monitoring and fault early warning system

Abstract

The invention relates to a power optical fiber on-line monitoring and fault early warning system, which adopts a layered architecture design and comprises a data acquisition layer, a data processing layer, an application layer and a display layer. The data acquisition layer acquires optical fiber optical power and reflected light data; the data processing layer processes the data and identifies a prediction fault; the application layer realizes the functions of fault positioning, early warning and the like, and integrates a GIS system; and the display layer displays information through upper computer software. A controller of a specific model, an optical power meter core chip and a communication chip are selected as hardware, and an adaptive power supply circuit is designed. Multiple algorithms are applied to data processing, fault positioning is combined with OTDR and GIS technologies, and the system has the advantages of multi-channel monitoring, high-accuracy recognition and low-error positioning.

Description

Technical Field

[0001] This invention relates to the field of power communication technology, specifically to a power fiber optic online monitoring and fault early warning system. Background Technology

[0002] In power systems, power fiber optic cables are critical information transmission carriers, and their stable operation is essential for power system security. However, long-term operation of fiber optic cables is susceptible to external environmental factors (such as temperature, humidity, and external force damage) and equipment aging, leading to frequent failures. Traditional fault detection methods have significant limitations, with limited ability to detect minor losses or incomplete breaks, cumbersome operation, and significant environmental influences, making it difficult to meet the high-reliability communication requirements of modern power systems. With the intelligent development of power systems, higher demands are placed on the monitoring of the operational status of power fiber optic cables. Real-time and accurate monitoring of fiber optic cable operation and timely fault detection and location have become crucial to ensuring the safe and stable operation of power systems. Summary of the Invention

[0003] The purpose of this invention is to provide an online monitoring and fault early warning system for power fiber optics, so as to at least partially solve the problems existing in related technologies.

[0004] To achieve the above objectives, this disclosure provides a power fiber optic online monitoring and fault early warning system, comprising: a data acquisition layer, a data processing layer, an application layer, and a display layer connected in sequence;

[0005] The data acquisition layer consists of an STM32 microcontroller, an optical power meter, an optical time-domain analysis module, an optical path control module, a network communication module, and a power supply circuit, and is used to acquire optical power and reflected light data of optical fibers in real time.

[0006] The application layer includes the following steps:

[0007] Step S21: Implement fault location function based on the processed data output by the data processing layer;

[0008] Step S22 involves constructing a fault early warning model to monitor the processed data in real time. When the monitored feature parameters exceed the preset threshold, an early warning message is automatically generated. At the same time, a historical data query function is provided to classify and store past fault records and processing data according to dimensions such as time and fault type. Users can call historical data for statistical analysis through the query interface.

[0009] Step S23: The application layer integrates the above fault location results with the GIS geographic information system;

[0010] The display layer uses host computer software to show the fiber optic operating status and fault information.

[0011] Optionally, step S21 specifically includes: analyzing the preprocessed, feature-extracted, and fused fault feature data, and calculating the distance based on the distance calculation formula of the optical time domain reflectometer (OTDR). ;

[0012] in, Let be the length of the optical fiber from the fault point to the measurement end, and c be the speed of light in a vacuum, approximately... t is the time from the emission of the optical pulse to the reception of the reflected light, and n is the refractive index of the optical fiber. These parameters determine the specific location of the fault.

[0013] Optionally, in step S22, the early warning module determines the early warning signal based on a preset threshold using an early warning signal formula. and failure probability assessment formula Provide early warnings of potential faults;

[0014] in, This represents the number of historical fault samples. The total number of samples, and These represent the mean and standard deviation of optical power under normal conditions. K is the preset power threshold, and K is the rate of change threshold.

[0015] Optionally, step S23 includes:

[0016] Step S231 involves using a simplified latitude-longitude to plane coordinate formula based on Gaussian projection. ;

[0017] Where L is the difference in longitude, R is the latitude, and R is the Earth's radius;

[0018] Step S232, the fault distance formula is derived using the principle of optical time-domain reflectometry. The calculated location of the fault point is combined with geographic information to visually display the surface location of the fault point.

[0019] Where v is the speed of light propagation in the optical fiber, and t is the time difference between the transmission and reception of the optical signal.

[0020] Optionally, the data processing layer includes the following steps:

[0021] Step S11: Preprocess the collected raw data;

[0022] Step S12: Extract the signal strength change rate and spectral characteristics that reflect the state of the optical fiber from the preprocessed data;

[0023] Step S13: Weighted fusion of feature information from different sources. Integrate them to form a more comprehensive set of features;

[0024] in, For the i-th modal feature, Let F be the weight;

[0025] Step S14, using the discrete wavelet transform formula The wavelet coefficients at each scale are obtained, and then the signal is reconstructed based on these coefficients. To highlight the characteristics of the fault;

[0026] in, The original signal, These are wavelet basis functions;

[0027] Step S15: Calculate the Euclidean distance between the sample and the cluster center. The data is divided into different categories to enable the identification and prediction of fiber optic faults;

[0028] Where x is the fault feature vector to be classified, and j is the j-th cluster center.

[0029] Optionally, step S11 includes:

[0030] Step S111, using the moving average method Eliminate noise;

[0031] in, The original data, The data is smoothed, and N is the window size.

[0032] Step S112, using linear interpolation method ;

[0033] Among them, a <m<b, , Fill in missing values ​​for known data points;

[0034] Step S113, according to In principle, when When it is determined to be an outlier, among which The mean, The standard deviation is used to correct outliers to ensure data quality and lay the foundation for subsequent analysis.

[0035] Optionally, the STM32 microcontroller controller is an STM32F407ZGT6 microcontroller with a Cortex-M4 core from STMicroelectronics, with a main frequency of 168MHz, 144 pins, 14 timers, multiple 12-bit high-precision ADCs, and support for USART, SPI, and IIC communication protocols.

[0036] Optionally, the optical power meter uses Analog Devices' AD8304 logarithmic operational amplifier chip as its core, and is equipped with an LSIPD-A40 indium gallium arsenide PIN photodiode to sense the light intensity signal. The optical power signal is converted into current and then logarithmically amplified by the AD8304 to output in the form of voltage. A second-order 20Hz low-pass filter is built to filter out power frequency interference, and the optical power can be detected as low as -70dBm.

[0037] Optionally, a small switch module can be added to enable data transmission between the STM32 controller, the optical time-domain reflectometry polling module, and the host computer server. The STM32 controller achieves Ethernet communication through an external W5500 chip module. This chip communicates with the microcontroller via SPI and integrates a fully hardware-based TCP / IP protocol stack + MAC + PHY, simplifying the hardware and software design and ensuring the stability and efficiency of data transmission.

[0038] Optionally, it integrates two switching power supplies: one for AC 220V to DC 24V and the other for DC -48V to DC 24V, supporting both AC 220V and DC -48V power supply modes. A BUCK circuit is built using the AP1501 power chip to convert DC 24V to DC 12V and 5V, powering the optical time-domain reflectometry polling module and the STM32 controller. An AMS1117-3.3 LDO linear regulator chip is used on the STM32 core control board to provide 3.3V power to the microcontroller, ensuring stable power supply to all modules in the system.

[0039] The technical solutions provided by the embodiments of this disclosure can include the following beneficial effects: A layered architecture is adopted, including a data acquisition layer, a data processing layer, an application layer, and a presentation layer. The data acquisition layer acquires fiber optic power and reflected light data; the data processing layer processes the data and identifies and predicts faults; the application layer implements functions such as fault location and early warning, and integrates a GIS system; the presentation layer displays information through host computer software. The hardware uses specific models of controllers, optical power meter core chips, and communication chips, and designs compatible power supply circuits; data processing employs multiple algorithms, and fault location combines OTDR and GIS technologies, giving the system the characteristics of multi-channel monitoring, high-accuracy identification, and low-error location. Attached Figure Description

[0040] Figure 1 This is a diagram of the architecture of a power fiber optic online monitoring and fault early warning system;

[0041] Figure 2 This is a schematic diagram of the hardware connection of the data acquisition layer;

[0042] Figure 3 This is a schematic diagram of the fault location process;

[0043] Figure 4 This is a system workflow diagram.

[0044] Explanation of icon numbers

[0045] In Figure 1: 1 - Data acquisition layer, 2 - Data processing layer, 3 - Application layer, 4 - Presentation layer, 5 - STM32 controller, 6 - Optical power meter, 7 - Optical time domain analysis module, 8 - Optical path control module, 9 - Network communication module, 10 - Power supply circuit, 11 - GIS geographic information system, 12 - Host computer software, 31 - Communication server.

[0046] In Figure 2: 13-W5500 chip, 14-AD8304 chip, 15-LSIPD-A40 photodiode, 16-second-order 20Hz low-pass filter, 17-AMS1117-3.3 chip, 18-AP1501 chip.

[0047] In Figure 3: 19 - OTDR technology module, 20 - Fiber optic length calculation unit, 21 - GIS spatial mapping unit, 22 - Fault point coordinate output unit.

[0048] Figure 4 In the middle: 23-Data acquisition, 24-Data preprocessing, 25-Feature extraction, 26-Multimodal fusion analysis, 27-Fault identification and prediction, 28-Fault location, 29-Early warning triggering, 30-Information display. Detailed Implementation

[0049] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0050] In this disclosure, unless otherwise stated, directional terms such as "upper," "lower," "front," "rear," "left," and "right" are used for ease of description based on the drawing orientations of the corresponding figures, while "inner" and "outer" are defined based on the contours of the corresponding components themselves. Terms such as "first" and "second" used in this disclosure are used to distinguish one element from another and do not have sequential or importance implications. Furthermore, when the following description refers to the figures, unless otherwise indicated, the same numbers in different figures represent the same or similar elements.

[0051] This disclosure provides a power fiber optic online monitoring and fault early warning system, which includes a data acquisition layer, a data processing layer, an application layer and a display layer connected in sequence.

[0052] The data acquisition layer consists of an STM32 microcontroller, an optical power meter, an optical time-domain analysis module, an optical path control module, a network communication module, and a power supply circuit, and is used to acquire optical power and reflected light data of optical fibers in real time.

[0053] The application layer includes the following steps:

[0054] Step S21: Implement fault location function based on the processed data output by the data processing layer;

[0055] Step S22 involves constructing a fault early warning model to monitor the processed data in real time. When the monitored feature parameters exceed the preset threshold, an early warning message is automatically generated. At the same time, a historical data query function is provided to classify and store past fault records and processing data according to dimensions such as time and fault type. Users can call historical data for statistical analysis through the query interface.

[0056] Step S23: The application layer integrates the above fault location results with the GIS geographic information system;

[0057] The display layer uses host computer software to show the fiber optic operating status and fault information.

[0058] Understandably, a layered architecture is adopted, including a data acquisition layer, a data processing layer, an application layer, and a presentation layer. The data acquisition layer collects fiber optic power and reflected light data; the data processing layer processes the data and identifies and predicts faults; the application layer implements functions such as fault location and early warning, and integrates a GIS system; the presentation layer displays information through host computer software. The hardware uses specific models of controllers, optical power meter core chips, and communication chips, and is designed with compatible power supply circuits; data processing employs multiple algorithms, and fault location combines OTDR and GIS technologies, giving the system the characteristics of multi-channel monitoring, high-accuracy identification, and low-error location.

[0059] The system adopts a layered architecture, with each layer having independent yet collaborative functions. The data collection, processing, application, and display processes are clear, ensuring efficient and reliable monitoring and early warning.

[0060] Precise hardware selection, powerful STM32 controller, high-precision optical power meter, stable communication module transmission, and power supply circuit adapted to the needs of each module ensure a solid system hardware foundation.

[0061] By integrating multiple advanced algorithms and technologies, multimodal data fusion improves the accuracy of fault identification, and the combination of OTDR and GIS achieves precise positioning. The fault identification accuracy rate exceeds 95%, and the positioning error is less than 15 meters.

[0062] Each module has no fewer than 8 monitoring channels to meet the monitoring needs of large-scale fiber optic networks. It also has a real-time early warning function, which can detect potential faults in advance, reduce fault losses, and provide strong support for the stable operation of power communication networks.

[0063] In one embodiment, step S21 specifically includes: analyzing the preprocessed, feature-extracted, and fused fault feature data, and calculating the distance based on the distance calculation formula of the optical time domain reflectometer (OTDR). ;

[0064] in, Let be the length of the optical fiber from the fault point to the measurement end, and c be the speed of light in a vacuum, approximately... t is the time from the emission of the optical pulse to the reception of the reflected light, and n is the refractive index of the optical fiber. These parameters determine the specific location of the fault.

[0065] Optionally, in step S22, the early warning module determines the early warning signal based on a preset threshold using an early warning signal formula. and failure probability assessment formula Provide early warnings of potential faults;

[0066] in, This represents the number of historical fault samples. The total number of samples, and These represent the mean and standard deviation of optical power under normal conditions. K is the preset power threshold, and K is the rate of change threshold.

[0067] In one embodiment, step S23 includes:

[0068] Step S231 involves using a simplified latitude-longitude to plane coordinate formula based on Gaussian projection. ;

[0069] Where L is the difference in longitude, R is the latitude, and R is the Earth's radius;

[0070] Step S232, the fault distance formula is derived using the principle of optical time-domain reflectometry. The calculated location of the fault point is combined with geographic information to visually display the surface location of the fault point.

[0071] Where v is the propagation speed of the optical signal in the optical fiber, and t is the time difference between the transmission and reception of the optical signal.

[0072] In one embodiment, the data processing layer includes the steps of:

[0073] Step S11: Preprocess the collected raw data;

[0074] Step S12: Extract the signal strength change rate and spectral characteristics that reflect the state of the optical fiber from the preprocessed data;

[0075] Step S13: Weighted fusion of feature information from different sources. Integrate them to form a more comprehensive set of features;

[0076] in, For the i-th modal feature, Let F be the weight;

[0077] Step S14, using the discrete wavelet transform formula The wavelet coefficients at each scale are obtained, and then the signal is reconstructed based on these coefficients. To highlight the characteristics of the fault;

[0078] in, The original signal, These are wavelet basis functions;

[0079] Step S15: Calculate the Euclidean distance between the sample and the cluster center. The data is divided into different categories to enable the identification and prediction of fiber optic faults;

[0080] Where x is the fault feature vector to be classified, and j is the j-th cluster center.

[0081] In one embodiment, step S11 includes:

[0082] Step S111, using the moving average method Eliminate noise;

[0083] in, The original data, The data is smoothed, and N is the window size.

[0084] Step S112, using linear interpolation method ;

[0085] Among them, a <m<b, , Fill in missing values ​​for known data points;

[0086] Step S113, according to In principle, when When it is determined to be an outlier, among which The mean, The standard deviation is used to correct outliers to ensure data quality and lay the foundation for subsequent analysis.

[0087] In one embodiment, the STM32 microcontroller controller is an STM32F407ZGT6 microcontroller with a Cortex-M4 core from STMicroelectronics, with a main frequency of 168MHz, 144 pins, 14 timers, multiple 12-bit high-precision ADCs, and support for USART, SPI, and IIC communication protocols.

[0088] In one embodiment, the optical power meter uses Analog Devices' AD8304 logarithmic operational amplifier chip as its core, and is equipped with an LSIPD-A40 indium gallium arsenide PIN photodiode to sense the light intensity signal. The optical power signal is converted into current and then logarithmically amplified by the AD8304 to output in the form of voltage. A second-order 20Hz low-pass filter is built to filter out power frequency interference, and the optical power can be detected as low as -70dBm.

[0089] In one embodiment, a small switch module is added to enable data transmission between the STM32 controller, the optical time-domain reflectometry polling module, and the host computer server. The STM32 controller achieves Ethernet communication through an external W5500 chip module. This chip communicates with the microcontroller via SPI and integrates a fully hardware-based TCP / IP protocol stack + MAC + PHY, simplifying the hardware and software design and ensuring the stability and efficiency of data transmission.

[0090] In one implementation, two switching power supplies are built-in: one for converting AC 220V to DC 24V and the other for converting DC -48V to DC 24V, supporting both AC 220V and DC -48V power supply modes. A BUCK circuit is built using the AP1501 power chip to convert DC 24V to DC 12V and 5V, powering the optical time-domain reflectometry polling module and the STM32 controller. An AMS1117-3.3 LDO linear regulator chip is used on the STM32 core control board to provide 3.3V power to the microcontroller, ensuring stable power supply to all modules of the system.

[0091] according to Figure 1 , 4As shown, when the system is working, it first acquires the optical power and reflected light data of the optical fiber in real time through the STM32 controller 5, optical power meter 6, and optical time domain analysis module 7 in the data acquisition layer 1 (step 23). The acquired data is transmitted to the data processing layer 2, where it is first preprocessed (step 24) to remove noise interference, and then feature extraction is performed (step 25) to extract data features related to the fault. Subsequently, through multimodal fusion analysis (step 26), combined with wavelet decomposition reconstruction, k-means clustering, and Bayesian fusion algorithms, fault identification and prediction are achieved (step 27). If a fault or potential fault risk is identified, the application layer 3 initiates fault location (step 28), calculates the optical fiber length corresponding to the fault point using the OTDR technology module 19, and then converts the optical fiber length information into ground coordinates through the GIS spatial mapping unit 21, while triggering an early warning (step 29). Finally, the display layer 4 displays the optical fiber operating status, fault point location, early warning information, etc. through the host computer software 12 (step 30), which is convenient for operation and maintenance personnel to monitor and manage.

[0092] As shown in Figure 2, in the data acquisition layer hardware connection, the STM32 controller 5 is connected to the W5500 chip 13 via SPI to achieve Ethernet communication; the LSIPD-A40 photodiode 15 of the optical power meter 6 senses the light intensity signal, converts it into current and transmits it to the AD8304 chip 14, which outputs a voltage signal after logarithmic amplification, and the second-order 20Hz low-pass filter 16 filters out power frequency interference; in the power supply circuit 10, the AP1501 chip 18 converts DC 24V to 12V and 5V, and the AMS1117-3.3 chip 17 stabilizes the voltage to 3.3V to power the STM32 controller 5.

[0093] As shown in Figure 3, during the fault location process, the OTDR technology module 19, based on the principles of backscattering and Fresnel reflection of light, acquires data such as the optical pulse propagation time, which is then transmitted to the fiber optic length calculation unit 20. The data is then calculated using the formula... (Where L is the fiber length from the fault point to the measurement end, c is the speed of light in vacuum, approximately, t is the time from emission to reception of the reflected light from the light pulse, and n is the refractive index of the fiber.) Calculate the fiber length corresponding to the fault point; subsequently, the GIS spatial mapping unit 21 receives the fiber length data, combines it with the geographical coordinates of the fiber's starting point and the laying direction angle, and uses the coordinate transformation formula... (in These are the geographical coordinates of the fiber optic cable's starting point. The direction and angle for laying optical fibers. The fiber optic length information is mapped to ground coordinates (for the calculated fault point coordinates), and the fault point coordinate output unit 22 outputs the latitude and longitude of the fault point to complete the precise positioning.

[0094] This invention has been described through embodiments. Those skilled in the art will understand that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Furthermore, under the teachings of this invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the invention. Therefore, this invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the protection scope of this invention.

Claims

1. A power fiber optic online monitoring and fault early warning system, characterized in that, It consists of, in sequence, a data acquisition layer, a data processing layer, an application layer, and a presentation layer; The data acquisition layer consists of an STM32 microcontroller, an optical power meter, an optical time-domain analysis module, an optical path control module, a network communication module, and a power supply circuit, and is used to acquire optical power and reflected light data of optical fibers in real time. The application layer includes the following steps: Step S21: Implement fault location function based on the processed data output by the data processing layer; Step S22 involves constructing a fault early warning model to monitor the processed data in real time. When the monitored feature parameters exceed the preset threshold, an early warning message is automatically generated. At the same time, a historical data query function is provided to classify and store past fault records and processing data according to dimensions such as time and fault type. Users can call historical data for statistical analysis through the query interface. Step S23: The application layer integrates the above fault location results with the GIS geographic information system; The display layer uses host computer software to show the fiber optic operating status and fault information.

2. The power fiber optic online monitoring and fault early warning system according to claim 1, characterized in that, Step S21 specifically includes: analyzing the preprocessed, feature-extracted, and fused fault feature data, and calculating the distance based on the distance calculation formula of the Optical Time Domain Reflectometer (OTDR). ; in, Let be the length of the optical fiber from the fault point to the measurement end, and c be the speed of light in a vacuum, approximately... t is the time from the emission of the optical pulse to the reception of the reflected light, and n is the refractive index of the optical fiber. These parameters determine the specific location of the fault.

3. The power fiber optic online monitoring and fault early warning system according to claim 2, characterized in that, In step S22, the early warning module determines the early warning signal based on a preset threshold using the early warning signal formula. and failure probability assessment formula Provide early warnings of potential faults; in, This represents the number of historical fault samples. The total number of samples, and These represent the mean and standard deviation of optical power under normal conditions. K is the preset power threshold, and K is the rate of change threshold.

4. The power fiber optic online monitoring and fault early warning system according to claim 2, characterized in that, Step S23 includes: Step S231 involves using a simplified latitude-longitude to plane coordinate formula based on Gaussian projection. ; Where L is the difference in longitude, R is the latitude, and R is the Earth's radius; Step S232, the fault distance formula is derived using the principle of optical time-domain reflectometry. The calculated location of the fault point is combined with geographic information to visually display the surface location of the fault point. Where v is the propagation speed of the optical signal in the optical fiber, and t is the time difference between the transmission and reception of the optical signal.

5. The power fiber optic online monitoring and fault early warning system according to claim 1, characterized in that, The data processing layer includes the following steps: Step S11: Preprocess the collected raw data; Step S12: Extract the signal strength change rate and spectral characteristics that reflect the state of the optical fiber from the preprocessed data; Step S13: Weighted fusion of feature information from different sources. Integrate them to form a more comprehensive set of features; in, For the i-th modal feature, Let F be the weight; Step S14, using the discrete wavelet transform formula The wavelet coefficients at each scale are obtained, and then the signal is reconstructed based on these coefficients. To highlight the characteristics of the fault; in, The original signal, These are wavelet basis functions; Step S15: Calculate the Euclidean distance between the sample and the cluster center. The data is divided into different categories to enable the identification and prediction of fiber optic faults; Where x is the fault feature vector to be classified, and j is the j-th cluster center.

6. The power fiber optic online monitoring and fault early warning system according to claim 5, characterized in that, Step S11 includes: Step S111, using the moving average method Eliminate noise; in, The original data, The data is smoothed, and N is the window size. Step S112, using linear interpolation method ; Among them, a <m<b, , Fill in missing values ​​for known data points; Step S113, according to In principle, when When it is determined to be an outlier, among which, The original data, The mean, The standard deviation is used to correct outliers to ensure data quality and lay the foundation for subsequent analysis.

7. The power fiber optic online monitoring and fault early warning system according to claim 6, characterized in that, The STM32 microcontroller controller used is the STMicroelectronics STM32F407ZGT6 microcontroller with a Cortex-M4 core, a main frequency of 168MHz, 144 pins, 14 timers, multiple 12-bit high-precision ADCs, and supports USART, SPI, and IIC communication protocols.

8. The power fiber optic online monitoring and fault early warning system according to claim 6, characterized in that, The optical power meter uses Analog Devices' AD8304 logarithmic operational amplifier chip as its core, and is equipped with an LSIPD-A40 indium gallium arsenide PIN photodiode to sense the light intensity signal. The optical power signal is converted into current and then logarithmically amplified by the AD8304 to output in the form of voltage. A second-order 20Hz low-pass filter is built to filter out power frequency interference, and the minimum detectable optical power is -70dBm.

9. The power fiber optic online monitoring and fault early warning system according to claim 8, characterized in that, A small switch module is added to enable data transmission between the STM32 controller, the optical time domain reflection polling module, and the host computer server. The STM32 controller achieves Ethernet communication through an external W5500 chip module. This chip communicates with the microcontroller via SPI and integrates a fully hardware-based TCP / IP protocol stack + MAC + PHY, simplifying the hardware and software design and ensuring the stability and efficiency of data transmission.

10. The power fiber optic online monitoring and fault early warning system according to claim 8, characterized in that, It has two built-in switching power supplies: AC 220V to DC 24V and DC -48V to DC 24V, supporting both AC 220V and DC -48V power supply modes. The AP1501 power chip is used to build a BUCK circuit to realize DC 24V to DC 12V and 5V to power the optical time domain reflection polling module and STM32 controller. The AMS1117-3.3 LDO linear regulator chip is used on the STM32 core control board to provide 3.3V power to the microcontroller, ensuring stable power supply to all modules of the system.

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