Ultrahigh-precision load data implementation circuit

Abstract

The utility model relates to the technical field of industrial automation field data acquisition, in particular to an ultrahigh-precision load data implementation circuit. The circuit comprises a 32-bit embedded MCU (Microprogrammed Control Unit) based on an ARM Cortex-M4F kernel, wherein the 32-bit embedded MCU is connected with a 32-bit sigma-delta analog-to-digital converter through an SP I (Serial Peripheral Interface) bus; the sensor excitation module comprises a precise low-noise LDO (Low Dropout Regulator), a current-expanding triode and a 5V direct-current power supply of a current-limiting resistor, and is output to the load sensor through a pi-type filter network; and the signal conditioning module comprises a second-order active filter circuit formed by an operational amplifier and an anti-aliasing passive filter network. According to the utility model, the problems of nonlinear error accumulation and dynamic tracking failure caused by temperature drift of a load detection system under a wide-temperature working condition in the field of industrial automation are effectively solved. Specifically, a collaborative architecture of a precise low-noise power supply and a multistage filter network is adopted, so that high-frequency noise and temperature drift interference of a sensor excitation signal are remarkably reduced, and high stability of an original signal is ensured.

Description

Technical Field

[0001] This utility model relates to the field of industrial automation field data acquisition technology, specifically to an ultra-high precision load data realization circuit. Background Technology

[0002] In high-precision load detection systems in industrial automation, comprehensive compensation for sensor nonlinearity and temperature drift is a core challenge for improving system accuracy. Traditional multi-segment nonlinear regression methods, through linear fitting within fixed segment intervals, can improve sensor nonlinearity errors at a single temperature. However, under wide temperature conditions, temperature drift causes dynamic shifts in the theoretical load values ​​at each segment endpoint, leading to a nonlinear accumulation effect of errors across temperature ranges. This error accumulation exhibits a non-uniform distribution across the entire sensor operating temperature range. Especially during rapid temperature changes, the fixed-segment model cannot track the dynamic changes in temperature-load coupling characteristics in real time, resulting in systematic biases in the compensated load data. While increasing the number of segments or introducing a static temperature compensation coefficient can alleviate errors within a single temperature range, existing technologies struggle to address the mechanistic problem of segment endpoint drift caused by temperature gradient changes. Furthermore, the computational resource consumption and accuracy improvement exhibit a non-linear relationship, hindering the technical bottleneck of achieving system accuracy at the order of one ten-thousandth. Utility Model Content

[0003] This disclosure proposes an ultra-high precision load data realization circuit, with the aim of overcoming at least one of the defects existing in the prior art.

[0004] To achieve the above objectives, the technical solution disclosed in this utility model is as follows:

[0005] According to one aspect of this disclosure, a circuit for realizing ultra-high precision load data is provided, the circuit comprising:

[0006] A 32-bit embedded MCU based on the ARM Cortex-M4F core is connected to a 32-bit Σ-Δ analog-to-digital converter via an SPI bus;

[0007] The sensor excitation module, including a precision low-noise LDO, a current-expanding transistor, and a current-limiting resistor, provides a 5V DC power supply, which is output to the load sensor via a π-type filter network.

[0008] The signal conditioning module includes a second-order active filter circuit composed of operational amplifiers and an anti-aliasing passive filter network;

[0009] The temperature acquisition module uses a digital temperature sensor mounted on the sensor body, and connects via I... 2 C-bus communicates with MCU;

[0010] The isolated communication module includes a high-speed capacitive gate isolator, which isolates the SPI bus, UART interface and relay control signals respectively;

[0011] The transmitter output module includes a 16-bit digital-to-analog converter, a differential amplifier circuit, and a MOSFET current source. The output terminal is connected in series with an overcurrent protection transistor and a transient suppression diode.

[0012] Furthermore, the circuit structure of the sensor excitation module includes:

[0013] The secondary winding of the power frequency transformer is connected to a full-wave rectifier bridge, and the output is filtered by an electrolytic capacitor and then input to a low-drift voltage reference source.

[0014] The output of the reference source drives the sensor through a PNP transistor current amplification circuit, and the sampling resistor connected in series with the emitter forms a current negative feedback loop.

[0015] The current limiting protection circuit includes parallel N-channel MOSFETs and precision resistors, with the gate voltage controlled by a reference source voltage divider network.

[0016] Furthermore, the operational amplifier of the signal conditioning module is a zero-drift instrumentation amplifier, with its non-inverting input connected to the output of the anti-aliasing filter network and its inverting input grounded via an adjustable resistor network.

[0017] The reference voltage input of the analog-to-digital converter is connected to an independent voltage reference source, and its power supply pin is isolated from the digital power supply through a ferrite bead.

[0018] Furthermore, the transmitter output module includes:

[0019] The reference voltage of the 16-bit digital-to-analog converter is provided by a low-temperature drift voltage reference source, and the output terminal is connected to the non-inverting input terminal of the differential amplifier.

[0020] The MOSFET current source is composed of an N-channel power transistor. The gate drive circuit includes an accelerating diode and a gate pull-down resistor. The temperature compensation resistor connected in series with the source is proportional to the sampling resistor.

[0021] Furthermore, the capacitor gate isolator of the isolated communication module includes a four-channel isolation unit, of which two channels are used for isolation of the SCK and MOSI signals of the SPI bus, and the other two channels are used for isolation of the TX / RX signals of the UART.

[0022] The optocoupler output of the relay drive circuit is connected to a Darlington transistor array, and the collector is connected in series with a resettable fuse and then to the relay coil.

[0023] Furthermore, the differential amplifier circuit of the transmitter output module includes a precision operational amplifier, whose non-inverting input is connected to the output of the digital-to-analog converter, and whose inverting input is connected to the current sampling resistor via a precision resistor network.

[0024] The gate drive circuit of the MOSFET current source includes an accelerating diode and a gate pull-down resistor, and the temperature compensation resistor connected in series with the source is proportional to the sampling resistor.

[0025] The programmable gain amplifier of the analog-to-digital converter is configured in auto-range mode, and its gain control pin is connected to the GPIO port of the MCU through a buffer.

[0026] A combination of tantalum capacitors and ceramic capacitors is connected in parallel at the output of the reference voltage source to suppress the impact of high-frequency noise on conversion accuracy.

[0027] The beneficial effects of this utility model are:

[0028] This invention effectively overcomes the problems of nonlinear error accumulation and dynamic tracking failure caused by temperature drift in load detection systems under wide-temperature conditions in industrial automation. Specifically, this invention adopts a collaborative architecture of precision low-noise power supply and multi-stage filtering network to significantly reduce high-frequency noise and temperature drift interference in the sensor excitation signal, ensuring high stability of the original signal. By integrating a high-resolution analog-to-digital converter and a real-time temperature acquisition module, synchronous and accurate sampling of load signal and temperature data is achieved. The isolation communication module uses capacitive grid isolation technology to block the time-domain interference of digital circuit noise on the analog signal link, ensuring the integrity of signal transmission. The transmitter output module combines low-temperature drift components and a temperature compensation network to suppress drift errors in the output signal under wide-temperature conditions. The synergistic effect of each module solves the endpoint drift problem caused by fixed segmented models and static temperature compensation in traditional solutions from a hardware perspective, achieving adaptive suppression of nonlinear errors across the entire temperature range and improving the system accuracy and adaptability of load detection.

[0029] The above description is only an overview of the technical solution of this utility model. In order to better understand the technical means of this utility model and to implement it in accordance with the contents of the specification, the preferred embodiments of this utility model are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0030] Figure 1 This is a flowchart of the method for realizing ultra-high precision load data according to this utility model;

[0031] Figure 2 This is a structural block diagram of the data acquisition instrument of this utility model;

[0032] Figure 3 This is the system power regulation circuit of this utility model;

[0033] Figure 4 This utility model relates to a high-precision sensor signal conditioning circuit;

[0034] Figure 5 This invention relates to the MCU minimum system and the sensor operating temperature acquisition circuit.

[0035] Figure 6 This utility model relates to a keyboard display circuit.

[0036] Figure 7 This utility model relates to an RS485 and relay output control circuit.

[0037] Figure 8 This utility model relates to a high-precision 4-20mA analog transmitter signal output circuit;

[0038] Figure 9 This is a schematic diagram of the linear fitting method for conventional sensors;

[0039] Figure 10 This is a schematic diagram of a multi-segment nonlinear fitting method for a single temperature sensor.

[0040] Figure 11 This is a linear schematic diagram of the multi-segment nonlinear fitting method for the wide-temperature sensor of this utility model. Detailed Implementation

[0041] The technical solutions of the present utility model will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present utility model, not all embodiments. Based on the embodiments of the present utility model, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present utility model.

[0042] The term "comprising," and any variations thereof, used in the specification and claims of this application, is intended to cover a non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or apparatus. Furthermore, the use of "and / or" in the specification and claims indicates at least one of the connected objects, such as A and / or B, indicating the inclusion of A alone, B alone, or both A and B.

[0043] In this embodiment of the invention, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in this embodiment of the invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0044] The present invention provides the following preferred embodiments:

[0045] Example 1

[0046] To address the issue of decreased load measurement accuracy caused by sensor nonlinearity errors and dynamic environmental interference over a wide temperature range, this embodiment constructs an integrated high-precision load data processing system by combining multi-level signal conditioning, dynamic temperature compensation, and closed-loop feedback control. For example... Figure 1 As shown, the steps for achieving ultra-high precision load data are as follows:

[0047] S100: Provides an excitation signal to the load cell through a precision low-drift DC power supply. The excitation signal is applied to the power input terminal of the sensor after high-frequency noise is eliminated by a π-type filter network.

[0048] S200: Performs two-stage anti-aliasing filtering on the differential analog signal output by the sensor, including a passive low-pass filter composed of an RC network and a second-order active filter composed of an operational amplifier.

[0049] S300: The filtered differential signal is input to a 32-bit Σ-Δ analog-to-digital converter with an integrated programmable gain amplifier. Under the control of the embedded MCU, the signal is amplified and digitally sampled, and the sensor's operating environment temperature data is acquired in real time.

[0050] S400: Based on temperature data, it dynamically selects a preset cluster of multi-segment nonlinear regression curves and calculates the compensated load value using the endpoint slope interpolation method according to the segment interval to which the current load value belongs.

[0051] S500: The compensated load data is transmitted to a 16-bit high-precision digital-to-analog converter via an isolated SPI bus. The voltage-to-current conversion circuit generates a 4-20mA transmission signal that is linearly proportional to the load. At the same time, the analog output and digital control circuit are electrically isolated through a capacitor gate isolation module.

[0052] Specifically, a precision low-drift DC power supply provides an excitation signal to the load cell. The output of the load cell is filtered by a π-type filter network to remove high-frequency noise before being connected to the sensor's power supply. The differential analog signal output by the sensor is sequentially passed through a second-order active filter consisting of an RC passive low-pass filter and an operational amplifier. The cutoff frequencies of the two filters are set to suppress high-frequency interference and prevent aliasing, respectively, ensuring the frequency domain purity of the signal before analog-to-digital conversion. The filtered differential signal is input to a 32-bit Σ-Δ analog-to-digital converter with an integrated programmable gain amplifier. The embedded MCU dynamically adjusts the gain to adapt the signal amplitude to the ADC's range, while a synchronous clock triggering method is used to achieve timing alignment of the load and temperature data.

[0053] Furthermore, the embedded MCU pre-stores a three-dimensional lookup table obtained from calibration experiments. This table contains continuous sub-intervals divided according to the sensor's full range and their theoretical load endpoint values ​​at different temperatures. When the current ambient temperature is detected, the segmented endpoint parameters of adjacent temperature calibration points are extracted from the lookup table. The endpoint slope at the current temperature is calculated using linear interpolation, forming a dynamic temperature compensation coefficient. The slope is calculated as follows:

[0054] Among them, W T1 W T2 These are the theoretical load values ​​at adjacent temperatures T1 and T2, respectively, in K. T1 K represents the original endpoint slope at temperature T1. comp The slope of the endpoint is the compensated slope, and T is the current temperature.

[0055] It's important to understand that this interpolation process ensures the continuity of the compensation model during gradual temperature changes by weighting the slope changes of adjacent temperature points. Furthermore, if the rate of temperature change exceeds a preset threshold, the MCU subdivides the current sub-interval into two smaller intervals based on the direction of the load change gradient, and inserts a transition curve generated by cubic spline interpolation at the new endpoints to suppress model mismatch caused by abrupt temperature changes.

[0056] Furthermore, after determining the segmented interval to which the current load value belongs, the deviation rate between the actual sampled value and the theoretical value at the lower limit of the interval is calculated and input into an error compensation model trained offline using the least squares method. This model outputs corrected endpoint slope weight coefficients, which are used to dynamically adjust the linearity of the multi-segmented line fitting. For example, when the deviation rate indicates that the current sampled value is close to the upper limit of the interval, the model automatically increases the weight coefficient of the upper endpoint slope to improve the fitting accuracy of the local interval. Through this closed-loop feedback mechanism, the accumulation of nonlinear residuals within the interval can be effectively suppressed.

[0057] Furthermore, the high-precision digital temperature sensor utilizes I... 2Data is periodically transmitted via the C-bus. When the standard deviation of continuous temperature sampling values ​​exceeds the limit, the system switches to high-speed sampling mode and uses a timestamp alignment algorithm to ensure that the time deviation between temperature and load data is less than a set threshold. The compensated load data is transmitted to the digital-to-analog converter (DAC) via an isolated SPI bus. Its output signal is converted into a 4-20mA transmission signal through a voltage-to-current conversion circuit. During this process, the PID controller dynamically adjusts the integral time constant based on the step change of the digital-to-analog conversion value. When output current overshoot is detected, a reverse compensation pulse is injected to suppress oscillation. In the steady-state phase, a moving average filtering algorithm is introduced to smooth the output current and eliminate the impact of high-frequency ripple on signal stability.

[0058] Furthermore, a capacitor gate isolation module is deployed between the digital control circuit and the analog output circuit, blocking digital noise coupling through electrical isolation and electromagnetic shielding design. A differential trace layout is used between the digital-to-analog converter output and the voltage-to-current conversion circuit, combined with a common-mode choke to suppress conducted interference. The ground plane of the signal conditioning circuit forms a hybrid grounding architecture with an RC network through a single-point connection, further reducing high-frequency noise interference to the analog signal link.

[0059] The advantages of this embodiment are as follows: Through the synergistic effect of a temperature-driven dynamic segmented compensation algorithm and a deviation rate feedback mechanism, adaptive tracking and local accuracy optimization of the sensor's nonlinear characteristics are achieved over a wide temperature range; the multi-level filtering and isolation architecture design ensures low-noise characteristics of the signal link at the hardware level; and the integration of synchronous acquisition and adaptive transmission control strategies ensures the system's real-time performance and output stability under complex operating conditions. This method significantly improves the overall accuracy of load data processing without introducing additional hardware resources.

[0060] Example 2

[0061] This embodiment provides a reliable hardware platform for ultra-high precision load data acquisition through precise analog circuit design. Based on this, nonlinear compensation of the sensor is achieved through multi-segment nonlinear regression. By acquiring the real-time operating temperature of the sensor, a set of multi-segment nonlinear regression curves is obtained according to different operating temperatures, thereby realizing ultra-high precision data acquisition under wide temperature operating conditions.

[0062] like Figure 2The diagram shows the hardware block diagram of a system for acquiring ultra-high precision load data. A high-performance 32-bit M4 embedded MCU is used as the control core, providing the necessary computing power for software compensation algorithms and other logic control. To reduce the impact of power supply noise on the accuracy of the acquired data, a linear regulated power supply is used. A power frequency transformer regulates the 220V AC voltage, and then rectifies and regulates it to generate three system power supplies, which respectively power the sensor conditioning circuit, the MCU control circuit, and the RS485 / switching and analog signal modules. The sensor excitation power supply uses a 5V low-drift precision DC power supply. An internally integrated high-precision, high-resolution 32-bit ADC with PGA amplifies and converts the differential signal output by the sensor. An NST112 digital temperature sensor acquires the sensor's operating ambient temperature for subsequent sensor temperature compensation. Four independent keyboards and an 8-digit digital tube display serve as the human-machine interface. An RS485 interface and a switching output control module are configured, and a high-precision 4-20mA analog transmission signal output is generated through a 16-bit high-precision DAC and a precision V / I conversion circuit. To prevent crosstalk between different module circuits from affecting the accuracy of load data acquisition, highly integrated capacitor gate isolators are used for electrical isolation between the modules.

[0063] Furthermore, such as Figure 3 The power supply regulation circuit of the acquisition system is shown. Compared to switching power supplies, linear power supplies have lower power ripple noise, which is especially important for high-precision data acquisition, particularly at higher sampling speeds. The 220V AC power supply is fed into the power frequency transformer for voltage regulation after passing through the power line filter T2. F1 is a self-resetting fuse for overload protection. A full-wave rectifier composed of four diodes (D1-D4) and filtered by capacitors provides the 3.3V system power supply for the MCU control circuit through an LDO linear regulator U1. The analog circuit power supply first uses a full-wave rectifier composed of D5-D6 and filtered by capacitors to obtain a 10V DC power supply. This is then passed through a precision low-drift voltage reference U11 to obtain a 5V precision reference voltage Vref. Finally, a current-amplifying circuit composed of U12, Q4, and Q3 provides a 5V excitation power supply E+ for the precision sensor, which has a certain load-carrying capacity. Q3 and R8 form a current-limiting circuit, with the current-limiting value related to the resistance value of R8. The power supply for the relay, RS485, and analog output modules is first rectified by D9 to D12 and then filtered by capacitors to obtain 24V DC power, which drives the relay and provides power to the 4-20mA transmitter circuit. After being stepped down by an LDO, a 5V power supply is obtained. VCC2 provides DC regulated power to the relevant circuits of this module.

[0064] Furthermore, such as Figure 4The circuit shown is a high-precision strain gauge sensor signal conditioning circuit. The sensor differential signals S+ and S- first pass through a passive low-pass filter and an anti-aliasing filter composed of C10, C12, and C13 before being fed into U12 for AD conversion. U12 is a domestically produced high-performance 32-bit Σ-Δ ADC with an integrated extremely low-noise PGA, achieving a maximum amplification of 128 times, used for amplifying mV-level differential signals. The analog and digital power supplies of U21 are independent. The sensor's analog excitation power supply E+ is filtered by a π-type filter to obtain DVCC, which provides the digital power supply to U21. The reference voltage for U21 is provided by U11. The ADC conversion result is obtained by the MCU via the SPI bus. The ADC's SPI interface is electrically isolated from the MCU's SPI bus interface through a highly integrated capacitive gate isolator U10.

[0065] Furthermore, such as Figure 5 The diagram shows the minimum system and temperature acquisition circuit of the MCU. U13 is a 32-bit embedded microcontroller with an ARM Cortex-M4F core, supporting DSP instructions, integrating a floating-point unit, and possessing abundant internal resources, including SPI, IIC, and UART. As the system's control core, it provides the necessary computing power for the system's software compensation algorithms. P1 is the SWD interface, used for MCU simulation debugging and program downloading. R19 and C7 form the power-on reset circuit. A high-precision digital temperature sensor, NST112, acquires the sensor's on-site operating temperature and interacts with the MCU via IIC.

[0066] Furthermore, such as Figure 6 The circuit shown is a keyboard and display circuit. K1 to K4 are independent keyboards used for parameter setting and other functions. U18 and U19 are four common cathode diodes, which together form an 8-digit LED display for real-time display of load data and other functions. Buffer U20 is used for segment driving, resistor array R25 is used for current limiting, and U22 is a Darlington driver chip used for bit driving of the 8-digit LED display.

[0067] Furthermore, such as Figure 7 The diagram shows the RS485 and relay output control circuit. U17 is the RS485 interface chip, used for TTL to RS485 logic level conversion. It is electrically isolated from the MCU's UART via capacitor gate isolator U16. Resistors R16 and R20 effectively prevent the impact of this node failure on RS485 bus communication. R17 and R18 are used for bus reflected signal absorption. D16 and D17 are bidirectional transient suppression diodes, providing bus overvoltage protection. F2 and F3 are self-resetting fuses for bus overload protection. The two relays, JD1 and JD2, are controlled by the MCU via capacitor gate isolator U14 and a transistor drive circuit.

[0068] Furthermore, such as Figure 8 The circuit shown is a high-precision 4-20mA analog transmitter signal output circuit. The MCU controls a high-precision 16-bit DAC chip U8 via a capacitor gate isolator U9 through another SPI bus interface. U8 is a high-performance voltage output DAC manufactured by Silergy, with its reference voltage provided by U7. A precision current source circuit composed of differential amplifier U6, Q1, Q2, R3, R5, etc., performs high-precision V / I conversion on the DAC output voltage, and under the control of the MCU, obtains a 4-20mA transmitter signal output that follows the load data. This transmitter signal has overcurrent protection and reverse polarity protection functions. Q2 and R4 provide overcurrent protection, which depends on the value of the current sampling resistor R4. Diode D13 provides reverse polarity protection.

[0069] Furthermore, such as Figures 9 to 11 The diagram illustrates conventional sensor nonlinearity compensation methods and the nonlinear regression method adopted in this invention. It is evident that a major factor affecting load data acquisition is the sensor's nonlinearity, such as... Figure 9 As shown, generally speaking, a sensor has an objectively existing input-output characteristic curve, namely the theoretical actual curve. This curve is usually obtained through actual measurement. In actual operation, the two-point linear regression method, such as connecting the endpoints, is often used to fit the theoretical actual curve. Undoubtedly, within the full scale range, simply using the two-point connection method to fit the theoretical actual curve will result in a relatively large residual.

[0070] Furthermore, if the full-scale range of the sensor is divided into several segments, such as... Figure 10 As shown, using a two-endpoint line fitting method within each segment can effectively reduce fitting error, thereby achieving higher fitting accuracy and reducing nonlinear error. The more segments, the higher the fitting accuracy, but this also increases the computational load. Generally, for ordinary sensors such as S-type tension / compression sensors, dividing the full-scale range into several equal segments (usually less than ten segments) and then performing linear fitting at the two endpoints of each segment can achieve a nonlinear fitting error better than one ten-thousandth. For piecewise linear fitting, within the full-scale range, since the slopes of the lines in each segment are different, it is essentially a nonlinear regression, often referred to as multi-segment nonlinear regression.

[0071] Furthermore, besides the impact of the sensor's own nonlinearity on the accuracy of load data acquisition, the sensor's temperature drift is also a significant factor affecting load data acquisition. This invention employs... Figure 11The multi-segment nonlinear regression and temperature compensation method shown, when combined with a reasonable hardware circuit, can achieve ultra-high precision load data acquisition. The operating environment temperature of a sensor will undoubtedly vary; due to the inherent characteristics of the sensor, temperature drift is an objective reality. If multi-segment nonlinear regression is performed only at a single temperature, such as room temperature (25°C), then ultra-high precision across the entire temperature range of the sensor is still difficult to guarantee. In fact, for a sensor, its input-output characteristic curves are related to temperature. Essentially, as the sensor's operating temperature changes, its input-output characteristic curves form a series of curves. Therefore, by acquiring the sensor's operating environment temperature and using the values ​​at each segment endpoint of each curve cluster, and then performing multi-segment nonlinear regression separately, high precision load data acquisition across the entire operating temperature range of the sensor can be guaranteed. Figure 11 As shown, different curves correspond to different operating temperatures of the sensor. The sensor input-output characteristic curves over the entire operating temperature range are a series of curves. Typically, a curve is obtained every 5 to 10 degrees Celsius. A good temperature compensation effect can be obtained over the entire operating temperature range of the sensor.

[0072] Although the present invention has been specifically described above with reference to preferred embodiments, it should be understood that the present invention is not limited to the embodiments described above. Rather, various modifications and variations can be made by those skilled in the art without departing from the essence of the present invention, and such modifications and variations should fall within the scope defined by the appended claims and their equivalents.

Claims

1. A circuit for realizing ultra-high precision load data, characterized in that, The circuit includes: A 32-bit embedded MCU based on the ARM Cortex-M4F core is connected to a 32-bit Σ-Δ analog-to-digital converter via an SPI bus; The sensor excitation module, including a precision low-noise LDO, a current-expanding transistor, and a current-limiting resistor, provides a 5V DC power supply, which is output to the load sensor via a π-type filter network. The signal conditioning module includes a second-order active filter circuit composed of operational amplifiers and an anti-aliasing passive filter network; The temperature acquisition module uses a digital temperature sensor mounted on the sensor body, and connects via I... 2 C-bus communicates with MCU; The isolated communication module includes a high-speed capacitive gate isolator, which isolates the SPI bus, UART interface and relay control signals respectively; The transmitter output module includes a 16-bit digital-to-analog converter, a differential amplifier circuit, and a MOSFET current source. The output terminal is connected in series with an overcurrent protection transistor and a transient suppression diode.

2. The ultra-high precision load data realization circuit according to claim 1, characterized in that, The circuit structure of the sensor excitation module includes: The secondary winding of the power frequency transformer is connected to a full-wave rectifier bridge, and the output is filtered by an electrolytic capacitor and then input to a low-drift voltage reference source. The output of the reference source drives the sensor through a PNP transistor current amplification circuit, and the sampling resistor connected in series with the emitter forms a current negative feedback loop. The current limiting protection circuit includes parallel N-channel MOSFETs and precision resistors, with the gate voltage controlled by a reference source voltage divider network.

3. The ultra-high precision load data realization circuit according to claim 1, characterized in that, The operational amplifier of the signal conditioning module is a zero-drift instrumentation amplifier, with its non-inverting input connected to the output of the anti-aliasing filter network and its inverting input grounded through an adjustable resistor network. The reference voltage input of the analog-to-digital converter is connected to an independent voltage reference source, and its power supply pin is isolated from the digital power supply through a ferrite bead.

4. The ultra-high precision load data realization circuit according to claim 1, characterized in that, The transmitter output module includes: The reference voltage of the 16-bit digital-to-analog converter is provided by a low-temperature drift voltage reference source, and the output terminal is connected to the non-inverting input terminal of the differential amplifier. The MOSFET current source is composed of an N-channel power transistor. The gate drive circuit includes an accelerating diode and a gate pull-down resistor. The temperature compensation resistor connected in series with the source is proportional to the sampling resistor.

5. The ultra-high precision load data realization circuit according to claim 1, characterized in that, The capacitor gate isolator of the isolated communication module includes a four-channel isolation unit, of which two channels are used for the isolation of SCK and MOSI signals of the SPI bus, and the other two channels are used for the isolation of TX / RX signals of the UART. The optocoupler output of the relay drive circuit is connected to a Darlington transistor array, and the collector is connected in series with a resettable fuse and then to the relay coil.

6. The ultra-high precision load data realization circuit according to claim 1, characterized in that, The differential amplifier circuit of the transmitter output module includes a precision operational amplifier, whose non-inverting input is connected to the output of the digital-to-analog converter, and whose inverting input is connected to the current sampling resistor via a precision resistor network. The gate drive circuit of the MOSFET current source includes an accelerating diode and a gate pull-down resistor, and the temperature compensation resistor connected in series with the source is proportional to the sampling resistor. The programmable gain amplifier of the analog-to-digital converter is configured in auto-range mode, and its gain control pin is connected to the GPIO port of the MCU through a buffer. A combination of tantalum capacitors and ceramic capacitors is connected in parallel at the output of the reference voltage source to suppress the impact of high-frequency noise on conversion accuracy.

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