Fault large current monitoring system and method based on tunnel magnetoresistive sensor

Abstract

The invention provides a fault large-current monitoring system and method based on a tunnel magnetoresistive sensor, and relates to the technical field of power system monitoring, and the system comprises a tunnel magnetoresistive sensor module which is used for measuring the near-field magnetic field intensity of a three-core cable in a non-contact manner, and inverting a current value through a magnetic field-current linear relation; the main control module comprises an ADC (Analog to Digital Converter) conversion unit and a DMA (Direct Memory Access) double-buffer receiving unit, and is configured to convert an analog signal output by the tunnel magnetoresistive sensor into digital magnetic field data and eliminate high-frequency interference; the dual-mode communication module integrates an NB-IOT module and a Bluetooth near field communication module, and supports real-time uploading of data to a cloud platform and debugging of field equipment; the power supply management module is composed of a multi-stage voltage conversion circuit and a solar energy storage module and realizes self-sustaining power supply without an external power supply; and the data storage module realizes comprehensive upgrading of high-precision non-contact measurement, all-weather remote monitoring, new energy self-power supply and intelligent operation and maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of power system monitoring, and particularly relates to a fault large current monitoring system and method based on a tunneling magnetoresistance sensor. Background Art

[0002] Due to the increasing demand for electricity in cities, the laying area of transmission lines is also increasing day by day, which also brings great troubles to urban construction. When the transmission line is dug and damaged, a fault large current will be generated in the transmission line. However, the current power distribution cabinets cannot alarm and monitor faults in real time. Moreover, currently, the contact measurement method using an instrument to access is often used to judge a faulty line. This contact measurement method directly introduces a current measuring instrument into the circuit to complete the reading of current parameters. For example, a traditional electromagnetic ammeter is usually used to measure large direct currents. This method is easy to implement and is stable and durable, but errors will be generated due to the introduction of the instrument circuit into the original measurement circuit, which cannot meet the measurement standards of high-precision equipment. Summary of the Invention

[0003] In view of this, for the large-scale grid equipment that requires safe, reliable and real-time information monitoring, in order to realize the current detection of the power system and solve the problems of low detection efficiency, poor operation safety and inability to monitor in real time existing in the development of the portability of traditional current sensors due to disadvantages such as large volume and high power consumption, the purpose of the present invention is to propose a fault large current monitoring system and method based on a tunneling magnetoresistance sensor.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] Based on the above object, in the first aspect, the present invention provides a fault large current monitoring system based on a tunneling magnetoresistance sensor, which includes the following components:

[0006] Tunneling magnetoresistance sensor (TMR) module: for non-contact measurement of the near-field magnetic field intensity of a three-core cable, and inversion of the current value through the magnetic field-current linear relationship;

[0007] Main control module: including an ADC conversion unit and a DMA double-buffer receiving unit, configured to convert the analog signal output by the tunneling magnetoresistance sensor (TMR) into digital magnetic field data and eliminate high-frequency interference;

[0008] Dual-mode communication module: integrating an NB-IOT module and a Bluetooth near-field communication module, supporting real-time data upload to the cloud platform and on-site device debugging;

[0009] Power management module: composed of a multi-stage voltage conversion circuit and a solar energy storage module, realizing self-sustained power supply without an external power supply;

[0010] Data storage module: An EEPROM memory based on the I2C protocol.

[0011] As a further solution of the present invention, the tunneling magnetoresistance sensor module uses a TMR2602-P3 chip, and the magnetic field measurement range covers -25 Oe to 25 Oe. The output voltage of the tunneling magnetoresistance sensor module has a linear relationship with the magnetic field strength: y = 0.054x + 1.65, where x is the magnetic field strength (unit: Oe) and y is the output voltage (unit: V).

[0012] As a further solution of the present invention, the main control module uses an STM32F412 RET6 as the main control chip, and a TMR magnetic field data acquisition circuit is arranged around the main control chip. The analog signal collected by the TMR chip is transmitted to the SMT32 chip through a serial port.

[0013] As a further solution of the present invention, the main control module integrates:

[0014] A 12-bit ADC converter;

[0015] Four USART serial communication interfaces;

[0016] A dual DMA controller to achieve dual-buffer data reception;

[0017] A hybrid clock system composed of a 32.768 kHz low-speed crystal oscillator and an 8 MHz high-speed crystal oscillator;

[0018] The main control module is connected to the analog signal output end of the TMR sensor through the ADC1_IN4 port, and a high-speed 8 MHz crystal oscillator circuit and a low-speed 32.768 kHz crystal oscillator circuit are configured.

[0019] As a further solution of the present invention, in the dual-mode communication module, the NB-IoT unit uploads data to the cloud platform through the MQTT protocol, the communication topic is bound to a dynamic device ID, and OTA firmware upgrade is supported; the Bluetooth module supports the mobile phone APP to read real-time data and configuration parameters at close range.

[0020] As a further solution of the present invention, the NB-IOT module in the dual-mode communication module includes a BC260Y-CN communication chip, a SIM card identification circuit, an MQTT protocol stack, and a data reporting period configurable unit. The Bluetooth near-field communication module uses a BLE-TPT-B-ANT chip, supports the Bluetooth 4.2 protocol, and is used to read the collected data at close range using the mobile phone APP. The tunneling magnetoresistance sensor module sends the digital signal stream after analog-to-digital conversion to the NB-IOT module through the AD conversion in the STM32F412RET6 chip and reports it to the Internet of Things cloud server.

[0021] As a further solution of the present invention, the NB-IOT module uses BC260Y-CN as the main control chip and is provided with a SIM card identification circuit, which is used to regularly report the collected magnetic field data to the cloud platform through the MQTT protocol and alarm after exceeding the threshold.

[0022] As a further solution of the present invention, the chip used in the Bluetooth near-field communication module is BLE-TPT-B-ANT, and the Bluetooth near-field communication module is used to read the collected data closely through a mobile phone APP.

[0023] As a further solution of the present invention, the multi-stage voltage conversion circuit in the power management module includes a 5V-to-4.2V input circuit and a 4.2V-to-3.3V circuit; among them, the power management chip used in the 5V-to-4.2V circuit is AP7335-WG-7 to supply power to the NB-IOT module; the power management chip used in the 4.2V-to-3.3V circuit is SI4463DY to supply power to the main control chip.

[0024] As a further solution of the present invention, the solar energy storage module in the power management module is jointly composed of a photovoltaic panel and a CN3791 chip module, using the constant current charging mode of the CN3791 module. The constant current charging current is set by the current detection resistor RCS between the CSP pin and the BAT pin. The VG port in the CN3791 module is the output of the internal voltage modulator, CHRG is the charging status indicator, DONE is the charging end indicator, and the MPPT port is the maximum power point tracking end of the solar panel. The solar energy storage module ensures the power supply of the main control and NB-IOT modules by charging the battery, and the output voltage of the battery is level-converted through the power management module.

[0025] As a further solution of the present invention, the constant current charging current of the solar energy storage module in the power management module is set by the current detection resistor RCS between the CSP pin and the BAT pin, and the constant voltage charging voltage is 4.2V with an accuracy of ±1%.

[0026] In the second aspect, the present invention provides a method for monitoring large fault currents based on a tunneling magnetoresistance sensor, including the following steps:

[0027] Signal acquisition: Non-contact measurement of the near-field magnetic field intensity of the cable through the TMR2602-P3 sensor, and output an analog voltage signal;

[0028] Signal processing: Use the ADC of the STM32F412RET6 chip to convert the analog signal into a digital signal, and realize continuous data reception through the DMA double-buffer mode;

[0029] Magnetic field analysis: Convert the voltage value into magnetic field intensity according to the formula x = (y - 1.65) / 0.054, where y is the output voltage of the sensor;

[0030] Data transmission:

[0031] Report the magnetic field data to the cloud platform through the NB-IoT module at a set period (default 50 seconds);

[0032] Push data to the mobile terminal in real time through the Bluetooth module;

[0033] Alarm trigger: When the magnetic field intensity exceeds the preset threshold, send an alarm command to the cloud platform.

[0034] As a further solution of the present invention, in the data transmission step, the NB-IoT module subscribes to a topic and reports data to the cloud platform through the MQTT protocol, where the device ID is a 5-digit unique code.

[0035] As a further solution of the present invention, the DMA double buffer mode specifically includes:

[0036] Set two buffer areas to alternately receive ADC data;

[0037] When one buffer area is full, trigger an interrupt, switch to the other buffer area to continue receiving, and process the full data at the same time.

[0038] As a further solution of the present invention, the power management step includes:

[0039] The solar panel charges the 4.2V lithium battery through the CN3791 chip, and starts the maximum power point tracking when the voltage of the MPPT pin > 1.23V;

[0040] The power management module monitors the battery voltage in real time, and cuts off the load power supply if it is lower than the latching threshold.

[0041] Compared with the prior art, a fault high-current monitoring system and method based on a tunneling magnetoresistive sensor proposed by the present invention have the following beneficial effects:

[0042] 1. Improve sensitivity and measurement accuracy. Adopt the TMR2602-P3 tunneling magnetoresistive chip, based on the quantum tunneling effect, it has extremely high sensitivity to magnetic field changes, and the resolution is much higher than that of traditional Hall sensors or magnetoelectric ammeters; through the linear relationship formula between the output voltage and the magnetic field intensity, the analog signal is accurately converted into the magnetic field intensity value, eliminating the non-linear error, ensuring that the measurement accuracy reaches the industrial standard, and there is no need to be directly electrically connected to the cable, avoiding circuit interference and safety hazards introduced by contact measurement, especially suitable for high-voltage and high-current scenarios.

[0043] 2. Real-time performance and remote monitoring capabilities. It adopts NB-IoT remote reporting and Bluetooth near-field interaction with a dual-mode communication architecture. The BC260Y-CN module is used to report data to the cloud platform at regular intervals (default 50 seconds), supporting ultra-low-power wide-area network coverage to ensure the stability of data transmission in remote areas. The Bluetooth module allows on-site personnel to read data in real time through the mobile phone APP to meet the immediate debugging requirements in complex environments. Moreover, the cloud platform generates a magnetic field intensity-time line graph, supporting historical data backtracking and abnormal event marking, which is convenient for maintenance personnel to quickly locate faults.

[0044] 3. High-efficiency power management through a solar self-power supply system and multi-level voltage conversion. By real-time tracking the maximum power point of the solar panel, the dual-mode charging extends the life of the lithium battery and avoids overcharging or undercharging problems. The DMA controller adopts a dual-buffer alternating reception mode to ensure continuous ADC sampling without interruption and avoid data loss. The NB-IoT module is bound to the operator's SIM card to ensure the security of the data transmission link. The power management module integrates an undervoltage lock function to automatically cut off the load when the battery voltage is lower than the threshold to prevent device damage.

[0045] 4. Lightweight deployment, with better portability than traditional monitoring systems. The device is only composed of a main control board, a collection board, and a solar panel. The weight of the main control board does not exceed 200g, which is convenient for carrying and installation. It uses photovoltaic power supply, which is green and environmentally friendly, and does not require an additional power supply, improving the installation speed. It supports remote real-time monitoring on the mobile side. The device supports remote clients (such as mobile phones and computers) to monitor data in real time and provides visual processing for the accessed data. It improves the safety of inspection personnel. Faults can be checked at close range by connecting to the device via Bluetooth to read data, improving operation safety.

[0046] In summary, a fault high-current monitoring system and method based on a tunneling magnetoresistance sensor of the present invention combines tunneling magnetoresistance sensing technology with an Internet of Things architecture, solves the pain points of traditional current monitoring devices, such as large volume, low accuracy, and dependence on manual inspections, realizes a comprehensive upgrade of high-precision non-contact measurement, all-weather remote monitoring, new energy self-power supply, and intelligent operation and maintenance, and provides an efficient, safe, and economical solution for power system fault early warning.

[0047] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. Brief Description of the Drawings

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or in the related art, the following will briefly introduce the drawings required for use in the description of the exemplary embodiments or the related art. The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0049] Figure 1 It is a structural block diagram of a fault high - current monitoring system method based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0050] Figure 2 It is a circuit diagram of a power management module in a fault high - current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0051] Figure 3 It is a circuit diagram of a power management chip AP7335 - WG - 7 in a fault high - current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0052] Figure 4 It is a circuit diagram of U1 in the power management module of a fault high - current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0053] Figure 5 It is a circuit diagram of an STM32F412RET6 chip in a fault high - current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0054] Figure 6 It is a circuit diagram of an EEPROM module in a fault high - current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0055] Figure 7 It is a circuit diagram of a BC260Y - CN module in a fault high - current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0056] Figure 8 It is a circuit diagram of a Bluetooth module in a fault high - current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0057] Figure 9 It is a schematic diagram of an N3791 module in a fault high - current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0058] Figure 10 It is a schematic diagram of the charging process of CN3791 in a fault high - current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0059] Figure 11Schematic diagram of the output curve of TMR2602-P3 in a fault high-current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention.

[0060] Figure 12 Schematic diagram of the cloud platform data visualization module in a fault high-current monitoring system based on a tunneling magnetoresistance sensor according to an embodiment of the present invention. Detailed implementation manners

[0061] Next, in combination with the accompanying drawings and specific implementation manners, the present application will be further described. It should be noted that, on the premise of no conflict, the following-described embodiments or technical features may be arbitrarily combined with each other to form new embodiments.

[0062] To make the purpose, technical solution and advantages of the present invention clearer and more understandable, the following will further elaborate on the embodiments of the present invention in combination with specific embodiments and with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0063] It should be noted that all the expressions using "first" and "second" in the embodiments of the present invention are used to distinguish two non-identical entities or non-identical parameters with the same name. It can be seen that "first" and "second" are only for the convenience of expression and should not be construed as a limitation to the embodiments of the present invention. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units inherently includes other steps or units.

[0064] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in combination with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0065] The flowcharts shown in the accompanying drawings are only illustrative examples and do not necessarily include all the content and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can be decomposed, combined or partially merged, so the actual execution order may change according to the actual situation.

[0066] Next, some implementation manners of the present application will be described in detail in combination with the accompanying drawings. On the premise of no conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0067] For large-scale power grid equipment, safe, reliable and real-time information monitoring is required. In order to achieve current detection in the power system and solve the problems of low detection efficiency, poor operation safety and inability to monitor in real time caused by the drawbacks of traditional current sensors such as large volume and high power consumption, which hinder the development of their portability. The present invention proposes a fault large current monitoring system and method based on a tunneling magnetoresistive sensor. Aiming at the problem of measuring the near-field magnetic field intensity of a three-core cable by a TMR sensor chip, STM32F412 RET6 is used as the main control chip, and a TMR magnetic field data acquisition circuit is designed around it. The analog signal collected by the TMR chip is transmitted to the SMT32 chip through the serial port. The device uses the AD conversion function in the STM32F412RET6 chip to send the digital signal stream after analog-to-digital conversion to the NB-IOT module and report it to the Internet of Things cloud server. The design of the NB-IOT module includes: an Internet of Things communication module BC260Y-CN and a SIM card module. To facilitate short-distance data reading, a Bluetooth communication circuit based on the CH9141 chip is designed to facilitate on-site real-time data reading. A solar energy storage module is designed to continuously supply power to the module.

[0068] See Figures 1 to 12 As shown, an embodiment of the present invention provides a fault large current monitoring system based on a tunneling magnetoresistive sensor. The system includes:

[0069] Tunneling magnetoresistive sensor (TMR) module: used for non-contact measurement of the near-field magnetic field intensity of a three-core cable, and inversely calculating the current value through the magnetic field-current linear relationship;

[0070] Main control module: includes an ADC conversion unit and a DMA double-buffer receiving unit, configured to convert the analog signal output by the tunneling magnetoresistive sensor (TMR) into digital magnetic field data and eliminate high-frequency interference;

[0071] Dual-mode communication module: integrates an NB-IOT module and a Bluetooth near-field communication module, supporting real-time data upload to the cloud platform and on-site device debugging;

[0072] Power management module: composed of a multi-stage voltage conversion circuit and a solar energy storage module, realizing self-sustained power supply without an external power supply;

[0073] Data storage module: an EEPROM memory based on the I2C protocol.

[0074] In this embodiment, the tunneling magnetoresistive sensor module uses a TMR2602-P3 chip, and the magnetic field measurement range covers -25 Oe to 25 Oe. The output voltage of the tunneling magnetoresistive sensor module and the magnetic field intensity satisfy a linear relationship: y = 0.054x + 1.65, where x is the magnetic field intensity (unit: Oe) and y is the output voltage (unit: V).

[0075] In this embodiment, the main control module uses STM32F412 RET6 as the main control chip. A TMR magnetic field data acquisition circuit is arranged around the main control chip, and the analog signal collected by the TMR chip is transmitted to the SMT32 chip through the serial port.

[0076] Among them, as shown in Figure 1 and Figure 5 , the main control module integrates:

[0077] A 12-bit ADC converter;

[0078] Four USART serial communication interfaces;

[0079] A dual DMA controller to achieve dual-buffer data reception;

[0080] A hybrid clock system composed of a 32.768 kHz low-speed crystal oscillator and an 8 MHz high-speed crystal oscillator;

[0081] The main control module is connected to the analog signal output terminal of the TMR sensor through the ADC1_IN4 port, and a high-speed 8 MHz crystal oscillator circuit and a low-speed 32.768 kHz crystal oscillator circuit are configured.

[0082] In this embodiment, in the dual-mode communication module, the NB-IoT unit uploads data to the cloud platform through the MQTT protocol, binds the communication topic to the dynamic device ID, and supports OTA firmware upgrade; the Bluetooth module supports the mobile phone APP to read real-time data and configure parameters at close range.

[0083] Among them, as shown in Figure 1 and Figure 5 , the NB-IOT module in the dual-mode communication module includes a BC260Y-CN communication chip, a SIM card identification circuit, an MQTT protocol stack, and a data reporting period configurable unit. The Bluetooth near-field communication module uses a BLE-TPT-B-ANT chip, supports the Bluetooth 4.2 protocol, and is used to read the collected data at close range using the mobile phone APP. The tunnel magnetoresistive sensor module sends the digital signal stream after analog-to-digital conversion to the NB-IOT module through the AD conversion in the STM32F412RET6 chip and reports it to the Internet of Things cloud server.

[0084] In this embodiment, as shown in Figure 5As shown in the figure, the main control module uses the STM32F412RET6 chip of STMicroelectronics, which has a high-capacity SRAM of 256KB and a FLASH of 1MB. The operating voltage of the STM32F412RET6 is between 1.7V and 3.6V. The STM32F412RET6 chip provides a 12-bit ADC, twelve general-purpose 16-bit timers, two general-purpose 32-bit timers, and a low-power RTC, and has 4 USART serial ports. Among them, the NRST reset circuit is connected to a high level, OSC32_IN and OSC32_OUT are connected to a 32.768KHz low-speed crystal oscillator circuit, and OSC_IN and OSC_OUT are connected to an 8MHz high-speed crystal oscillator circuit. ADC1_IN4 is connected to the USB port and is connected to the acquisition circuit of the TMR2602 chip to receive data information. I2C2_SCL and I2C2_SDA correspond to the control line and data line of the I2C bus respectively, and are connected to the EEPROM memory. Three USART serial ports are connected in the circuit, and USART1 is used to communicate with the upper PC. SWDIO and SWCLK are used for program download and simulation. The peripheral circuit design includes an 8MHz high-speed crystal oscillator circuit, a 32.768KHz low-speed crystal oscillator circuit, a serial port circuit, a debugging and download circuit, and a reset circuit.

[0085] Among them, see Figure 6 As shown in the figure, the EEPROM memory uses the AT24C32D storage chip with a size of 4KB, which is used to store the firmware information required for remote OTA upgrade, such as version number and written bytes, etc. The function of the EEPROM memory is realized through the I2C protocol.

[0086] See Figure 7 As shown in the figure, the NB-IOT module uses the BC260Y-CN as the main control chip and is equipped with a SIM card identification circuit, which is used to regularly report the collected magnetic field data to the cloud platform through the MQTT protocol and alarm after exceeding the threshold. See Figure 6 As shown in the figure, the chip used by the Bluetooth near-field communication module is BLE-TPT-B-ANT, and the Bluetooth near-field communication module is used to read the collected data closely through the mobile phone APP.

[0087] In this embodiment, see Figures 1 to 4 As shown in the figure, the multi-stage voltage conversion circuit in the power management module includes a 5V to 4.2V input circuit and a 4.2V to 3.3V circuit; among them, the power management chip used in the 5V to 4.2V circuit is AP7335-WG-7, which supplies power to the NB-IOT module; the power management chip used in the 4.2V to 3.3V circuit is SI4463DY, which supplies power to the main control chip.

[0088] Among them, seeFigure 9 and Figure 10 As shown, the solar energy storage module in the power management module is jointly composed of a photovoltaic panel and a CN3791 chip module. The constant current charging mode of the CN3791 module is used, and the constant current charging current is set by the current detection resistor RCS between the CSP pin and the BAT pin. The VG port in the CN3791 module is the output of the internal voltage modulator, CHRG is the charging status indicator terminal, DONE is the charging end indicator terminal, and the MPPT port is the maximum power point tracking terminal of the solar panel. The solar energy storage module ensures the power supply of the main control and NB-IOT modules by charging the battery, and the output voltage of the battery is level-converted through the power management module. The constant current charging current of the solar energy storage module in the power management module is set by the current detection resistor RCS between the CSP pin and the BAT pin, and the constant voltage charging voltage is 4.2V with an accuracy of ±1%. When the voltage of the VCC pin is greater than the low voltage latch threshold, greater than the battery voltage and the voltage of the MPPT pin is greater than 1.23V, the CN3791 works normally. See Figure 9 As shown, the VG port is the output of the internal voltage modulator, CHRG is the charging status indicator terminal, DONE is the charging end indicator terminal, and the MPPT port is the maximum power point tracking terminal of the solar panel. The schematic diagram of the charging process of the solar energy storage module is as Figure 10 shown. It ensures the power supply of the main control and NB-IOT modules by charging the battery, and the output voltage of the battery is level-converted through the power management module.

[0089] In the second aspect of the embodiments of the present invention, the embodiments of the present invention also provide a method for monitoring large fault currents based on a tunneling magnetoresistance sensor. The method includes the following steps:

[0090] Signal acquisition: Non-contact measurement of the near-field magnetic field intensity of the cable through the TMR2602-P3 sensor, and output an analog voltage signal;

[0091] Signal processing: Use the ADC of the STM32F412RET6 chip to convert the analog signal into a digital signal, and realize continuous data reception through the DMA double buffer mode;

[0092] Magnetic field analysis: Convert the voltage value into the magnetic field intensity according to the formula x=(y - 1.65) / 0.054, where y is the output voltage of the sensor;

[0093] Data transmission:

[0094] Report the magnetic field data to the cloud platform through the NB-IoT module at a set period (default 50 seconds);

[0095] Push the data to the mobile terminal in real time through the Bluetooth module;

[0096] Alarm Trigger: When the magnetic field strength exceeds the preset threshold, an alarm instruction is sent to the cloud platform.

[0097] In this embodiment, in the data transmission step, the NB-IoT module subscribes to a topic and reports data to the cloud platform through the MQTT protocol, where the device ID is a 5-digit unique code.

[0098] The DMA double-buffer mode specifically includes:

[0099] Set two buffer areas to alternately receive ADC data;

[0100] When one buffer area is full, an interruption is triggered, and the system switches to the other buffer area to continue receiving while processing the full data.

[0101] In this embodiment, the power management step includes:

[0102] The solar panel charges the 4.2V lithium battery through the CN3791 chip, and starts maximum power point tracking when the voltage of the MPPT pin > 1.23V;

[0103] The power management module monitors the battery voltage in real time, and cuts off the power supply to the load if it is lower than the latching threshold.

[0104] It should be noted that the signal processing logic of TMR2602-P3 is as follows: The main principle of sensing by the TMR tunnel magnetoresistance chip is the quantum tunneling effect, where the tunnel magnetoresistance effect occurs in the magnetic tunnel junction (MTJ). The MTJ element consists of a ferromagnetic free layer, a tunnel barrier layer, and a ferromagnetic pinned layer. The resistance of the tunneling magnetoresistive sensor is determined by the magnetization directions of the two ferromagnetic layers. When the magnetization direction changes, the tunneling resistance changes accordingly, and the resistance of the device changes accordingly. Therefore, it is called the tunnel magnetoresistance effect. The influence of the magnetization direction of the TMR element on the resistance.

[0105] According to the chip manual of TMR2602-P3, this chip can only measure the uniaxial magnetic field. Therefore, when measuring, it is necessary to select the measurement direction and record the measured point data in this direction. According to the chip manual, when the magnetic field strength is -25 Oe, the output voltage of TMR is 0.3V, and when the magnetic field strength is 25 Oe, the output voltage of TMR is 3V. Thus, it can be deduced that the TMR output voltage (y / unit: V) and the magnetic field strength (x / unit: Oe) satisfy a linear function y = 0.054x + 1.65. In this way, the magnitude of the magnetic induction intensity can be calculated according to the output voltage. The curve of the output of the TMR2602-P3 sensor changing with the externally applied magnetic field strength is as attached Figure 11 .

[0106] In this embodiment, when implementing digital signal acquisition, the ADC1 conversion port of the STM32F412RET6 main control chip is assigned to the analog signal output terminal of the TMR2602 chip, and the dual-buffer reception mode of the acquired data is realized through the DMA cyclic reception function. The serial port function sends the processed digital signal to the specified module, where UART1 is assigned to the serial port receiving end of the host computer PC, UART2 is assigned to the Bluetooth serial port receiving end, and UART3 is assigned to the BC260Y-CN serial port receiving end.

[0107] The device operation process and technical steps of a fault high-current monitoring system and method based on a tunneling magnetoresistive sensor of the present invention are as follows:

[0108] 1.1 Connect the power supply:

[0109] Connect the 5V DC power line to the main control board and turn on the power switch.

[0110] After connecting the programmer to the serial port and then to the main control board.

[0111] 1.2 Burn the program:

[0112] Connect the program burner and the serial port debugging assistant to the socket of the board, and connect the other end to the computer. Burn the firmware into the main control board through the code burner on the PC side and restart the main control board.

[0113] 1.3 View the printed information:

[0114] After restarting the main control board, the serial port software prints messages, prompting serial port initialization, BC260Y initialization, etc. If there are prompts such as initialization failure, it means there are problems with the device installation or the program. The device number can also be directly viewed through the main control board. The serial port debugging assistant on the PC side will print the board information and read the 5-digit device ID.

[0115] 1.4 Connect to MQTT:

[0116] Click the plus sign on the right side of Connections in MQTTX, create a new connection to access the cloud platform, create a new subscription to access the uplink data sent by the device. Set the subscription topic, / data / omNDWXFs / gateway / "device number" / upload.

[0117] 1.5 Set the device reporting period:

[0118] Set the data reporting period of BC260Y. Enter the downlink data format in the input box and set the reporting period to 50s. At this time, the serial port and the cloud platform will periodically report data and print it in the software window.

[0119] 1.6 Add the device to the cloud platform:

[0120] After creating a gateway on the cloud platform and adding a device number, data reporting line charts can be viewed in the monitoring center by creating a device again. See Figure 12 as shown.

[0121] Exemplarily, after successfully adding and installing a device, the specific method for reading and viewing device data is as follows:

[0122] 1. Log in to the cloud platform

[0123] Log in to the "Leakage Current Abnormality Detection" website.

[0124] 2. View detection data

[0125] Click on the monitoring center, then click on the device to be viewed, and a line chart showing the magnetic field change around the device will be displayed. As attached Figure 9 .

[0126] 3. Close-range Bluetooth connection

[0127] 3.1 Download the BLE Debug Assistant on the mobile phone

[0128] Download and install the BLE Debug Assistant from the mobile phone software store.

[0129] 3.2 Search for the device

[0130] Enter the BLE Debug Assistant, turn on Bluetooth, pull down to search for the JINCHI POWER DEVICE device and click CONNECT after it is found.

[0131] 3.3 Enter the password to log in to the device

[0132] Click on the unknown service at the bottom, the upload icon will be visible. Enter the password as shown below, note to change the device number for different devices. Here it is 47065.

[0133] $jcdl_wg47065_3.11, 3.12, 3.13, 3.14, 0030

[0134] After entering, click Read, close HEX, turn on the receive notification data, and the sampling value can be read in real time.

[0135] The present invention uses the TMR2602-P3 tunneling magnetoresistance chip, which is based on the quantum tunneling effect and has extremely high sensitivity to magnetic field changes. Its resolution is much higher than that of traditional Hall sensors or magnetoelectric ammeters. Through the linear relationship formula between the output voltage and the magnetic field strength, the analog signal is accurately converted into the magnetic field strength value, eliminating the non-linear error and ensuring that the measurement accuracy reaches the industrial grade standard. It does not need to be directly electrically connected to the cable, avoiding the circuit interference and safety hazards introduced by contact measurement, and is especially suitable for high-voltage and high-current scenarios. It adopts the NB-IoT remote reporting and Bluetooth near-field interaction of the dual-mode communication architecture. Through the BC260Y-CN module, the data is reported to the cloud platform at regular intervals (default 50 seconds), supporting ultra-low power wide area network coverage to ensure the stability of data transmission in remote areas. The Bluetooth module allows on-site personnel to read the data in real time through the mobile phone APP to solve the immediate debugging requirements in complex environments. Moreover, the cloud platform generates a magnetic field strength-time line graph, supporting the backtracking of historical data and the marking of abnormal events, which is convenient for maintenance personnel to quickly locate faults. It has a solar self-power supply system and a multi-stage voltage conversion high-efficiency power management. By continuously tracking the maximum power point of the solar panel, the dual-mode charging extends the life of the lithium battery and avoids overcharging or undercharging problems. The DMA controller adopts a dual-buffer alternating reception mode to ensure continuous sampling of the ADC without interruption and avoid data loss. The NB-IoT module is bound to the operator's SIM card to ensure the security of the data transmission link. The power management module integrates an undervoltage latch function, automatically cutting off the load when the battery voltage is lower than the threshold to prevent device damage. It has a lightweight deployment, with better portability than traditional monitoring systems. The device is only composed of a main control board, a data acquisition board and a solar panel, and the weight of the main control board does not exceed 200g, which is convenient for carrying and installation. It uses photovoltaic power supply, which is green and environmentally friendly and does not require an additional power supply, improving the installation speed. It supports remote real-time monitoring on the mobile side. The device supports remote clients (such as mobile phones and computers) to monitor the data in real time and provides visual processing for the accessed data. It improves the safety of the detection personnel. The fault can be checked closely by connecting the device via Bluetooth to read the data, improving the operation safety.

[0136] It should be noted that the above drawings are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present invention, rather than for limiting purposes. It is easy to understand that the processes shown in the above drawings do not indicate or limit the time sequence of these processes. Additionally, it is also easy to understand that these processes can be executed synchronously or asynchronously in, for example, multiple modules.

[0137] It should be understood that although the above is described in a certain order, these steps are not necessarily executed in the above order successively. Unless there is a clear indication in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, some steps of this embodiment may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0138] The above are exemplary embodiments disclosed by the present invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments disclosed by the present invention as defined by the claims. The functions, steps, and / or actions of the method claims according to the disclosed embodiments herein do not need to be executed in any specific order. In addition, although the elements disclosed in the embodiments of the present invention can be described or claimed in an individual form, they can also be understood as plural unless clearly limited to the singular.

[0139] It should be understood that, as used herein, unless the context clearly supports an exception, the singular form "a" is also intended to include the plural form. It should also be understood that "and / or" as used herein refers to any and all possible combinations of one or more of the related listed items. The above serial numbers of the disclosed embodiments of the present invention are only for description and do not represent the superiority or inferiority of the embodiments.

[0140] Those of ordinary skill in the art should understand that: the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the disclosure of the embodiments of the present invention (including the claims) is limited to these examples; under the concept of the embodiments of the present invention, the technical features between the above embodiments or different embodiments can also be combined, and there are many other variations in different aspects of the above embodiments of the present invention, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention shall be included within the protection scope of the embodiments of the present invention.

Claims

1. A fault large current monitoring system based on a tunneling magnetoresistance sensor, characterized in that The system includes: Tunnel magnetoresistive sensor module: used for non-contact measurement of the near-field magnetic field intensity of a three-core cable, and inversely calculating the current value through the linear relationship between the magnetic field and current; Main control module: including an ADC conversion unit and a DMA double-buffer receiving unit, configured to convert the analog signal output by the tunnel magnetoresistive sensor into digital magnetic field data and eliminate high-frequency interference; Dual-mode communication module: integrating an NB-IOT module and a Bluetooth near-field communication module, supporting real-time data upload to the cloud platform and on-site device debugging; Power management module: composed of a multi-stage voltage conversion circuit and a solar energy storage module, realizing self-sustained power supply without an external power source; Data storage module: an EEPROM memory based on the I2C protocol.

2. The fault large current monitoring system based on a tunneling magnetoresistance sensor according to claim 1, characterized in that The tunnel magnetoresistive sensor module uses a TMR2602-P3 chip, and the magnetic field measurement range covers -25 Oe to 25 Oe. The output voltage of the tunnel magnetoresistive sensor module and the magnetic field intensity satisfy a linear relationship: y = 0.054x + 1.65, where x is the magnetic field intensity and y is the output voltage.

3. The fault large current monitoring system based on a tunneling magnetoresistance sensor according to claim 2, wherein The main control module is provided with a TMR magnetic field data acquisition circuit around the main control chip, and transmits the analog signal collected by the tunnel magnetoresistive sensor chip to the main control module chip through a serial port.

4. The fault large current monitoring system based on a tunneling magnetoresistance sensor according to claim 3, characterized in that, The main control module integrates: A 12-bit ADC converter; Four USART serial communication interfaces; Dual DMA controllers to achieve data double-buffer reception; A hybrid clock system composed of a 32.768 kHz low-speed crystal oscillator and an 8 MHz high-speed crystal oscillator; The main control module is connected to the analog signal output end of the TMR sensor through the ADC1_IN4 port, and is configured with a high-speed 8 MHz crystal oscillator circuit and a low-speed 32.768 kHz crystal oscillator circuit.

5. The fault large current monitoring system based on a tunneling magnetoresistance sensor according to claim 1, wherein, In the dual-mode communication module, the NB-IoT unit uploads data to the cloud platform through the MQTT protocol, binds the communication topic to the dynamic device ID, and supports OTA firmware upgrade; the Bluetooth module supports the mobile phone APP to read real-time data and configuration parameters at close range.

6. The fault large current monitoring system based on a tunneling magnetoresistance sensor according to claim 5, characterized in that, In the dual-mode communication module, the NB-IOT module includes a BC260Y-CN communication chip, a SIM card identification circuit, an MQTT protocol stack, and a data reporting period configurable unit. The Bluetooth near-field communication module uses a BLE-TPT-B-ANT chip, supports the Bluetooth 4.2 protocol, and is used to read the collected data at close range using the mobile phone APP. The tunnel magnetoresistive sensor module sends the digital signal stream after analog-to-digital conversion to the NB-IOT module through the AD conversion in the STM32F412RET6 chip and reports it to the Internet of Things cloud server.

7. The fault large current monitoring system based on a tunneling magnetoresistance sensor according to claim 6, wherein The NB-IOT module uses BC260Y-CN as the main control chip and is provided with a SIM card identification circuit, which is used to regularly report the collected magnetic field data to the cloud platform through the MQTT protocol and alarm after exceeding the threshold.

8. The fault large current monitoring system based on a tunneling magnetoresistance sensor according to claim 7, characterized in that, The chip used by the Bluetooth near-field communication module is BLE-TPT-B-ANT, and the Bluetooth near-field communication module is used to read the collected data at close range using the mobile phone APP.

9. The fault large current monitoring system based on a tunneling magnetoresistance sensor according to claim 1, characterized in that, The multi-stage voltage conversion circuit in the power management module includes a 5V-to-4.2V circuit and a 4.2V-to-3.3V circuit; among them, the power management chip used in the 5V-to-4.2V circuit is AP7335-WG-7, which powers the NB-IOT module; the power management chip used in the 4.2V-to-3.3V circuit is SI4463DY, which powers the main control chip.

10. A fault large current monitoring method based on a tunneling magnetoresistance sensor, characterized in that, Performing the steps of the method by the fault large current monitoring system based on the tunneling magnetoresistive sensor according to any one of claims 1-9, the method comprising the following steps: Signal acquisition: non-contact measurement of the near-field magnetic field intensity of the cable by the TMR2602-P3 sensor, and output of an analog voltage signal; Signal processing: converting the analog signal into a digital signal by using the ADC of the main control module chip, and realizing continuous data reception through the DMA double buffer mode; Magnetic field analysis: converting the voltage value into the magnetic field intensity according to the linear relationship between the output voltage of the tunneling magnetoresistive sensor module and the magnetic field intensity; Data transmission: Reporting the magnetic field data to the cloud platform at a set period through the NB-IoT module; Pushing data to the mobile terminal in real time through the Bluetooth module; Alarm trigger: when the magnetic field intensity exceeds the preset threshold, sending an alarm instruction to the cloud platform.

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