A sensor intelligent calibration system and method

Abstract

The application relates to the technical field of sensor calibration, and discloses a sensor intelligent calibration system and method, which comprises a hardware integrated host, a main control module, a calibration data storage module, a communication interface module, a sensor type identification module and PC end detection software. The method is applied to the system. According to the application, the multi-channel design of the hardware integrated host realizes convenient access and real-time calibration of multiple types of sensors, reduces the time consumption of equipment switching, solves the wide-temperature-range nonlinear compensation problem based on the impedance characteristics and voltage range matching segmented compensation model of the sensor type identification module, improves the calibration accuracy of platinum resistance, thermocouple and other sensors, and integrates standard source data to generate a calibration report through the calibration data storage module and the PC end detection software, realizes whole life cycle data management and quality tracing, and thus improves the adaptability to various sensors, calibration efficiency, data consistency and expandability.

Description

Technical Field

[0001] This application relates to the field of sensor calibration technology, specifically a sensor intelligent calibration system and method. Background Technology

[0002] In existing technologies, the following are typical solutions for calibration and data acquisition of various types of sensors:

[0003] Chinese patent with publication number CN101109662A discloses a resistance temperature measurement circuit. However, it adopts a single constant current source design, only supports three-wire RTD measurement, and cannot be compatible with thermocouple signal acquisition.

[0004] Chinese patent CN113503985A discloses an adaptive distributed intelligent measurement node for temperature sensors, which provides temperature data reading functions for multiple types of sensors, but does not involve the full life cycle management of sensors (such as calibration and compensation), and is only used for distributed measurement nodes.

[0005] The common drawback of the above solutions is that:

[0006] The hardware design is limited: it only supports specific types of sensors (such as three-wire RTDs or thermocouples) and cannot be compatible with signal inputs from multiple types of sensors.

[0007] Limitations of compensation methods: Using fixed compensation coefficients (such as constant current source power supply method and thermistor compensation method) is only effective within a narrow temperature range and is difficult to adapt to nonlinear changes over a wide temperature range;

[0008] Functional fragmentation: Functions such as calibration, compensation, and data acquisition rely on multiple independent devices, lacking an integrated solution.

[0009] Based on the above-mentioned shortcomings, it can be seen that, for existing technologies, different types of sensors (such as RTDs, thermocouples, and capacitive humidity sensors) require dedicated testing instruments (such as RTD testers and thermocouple calibrators), and the equipment only supports specific wiring methods (such as three-wire and four-wire RTDs), which cannot be compatible with the interface requirements of multiple types of sensors. This leads to the need to frequently switch test platforms and rewire during use, resulting in cumbersome and time-consuming operations. Furthermore, the existing compensation methods use fixed coefficients, which cannot adapt to the nonlinear characteristics of sensors in different temperature ranges. At the same time, the data formats output by various devices are not uniform, making it difficult to establish a unified quality traceability system.

[0010] Therefore, a new sensor calibration technology is urgently needed. Summary of the Invention

[0011] The purpose of this application is to provide a smart sensor calibration system and method to solve the technical problems mentioned in the background.

[0012] To achieve the above objectives, this application discloses the following technical solutions:

[0013] In a first aspect, this application discloses a smart sensor calibration system, which includes:

[0014] The hardware-integrated host is equipped with multiple sensor interface channels for connecting several sensor probes of different types and standard sources;

[0015] The main control module, connected to the hardware integrated host, is used to acquire the raw sensor signals and perform calibration compensation algorithms on the raw sensor signals;

[0016] A calibration data storage module, connected to the main control module, is used to store the sensor probe's serial number, compensation parameters, and calibration date.

[0017] A communication interface module, connected to the main control module, is used for data interaction with the PC-side detection software;

[0018] A sensor type identification module, connected to the main control module, is used to identify the type of the sensor by its impedance characteristics and voltage range, and match the corresponding segmented compensation model, using the matched segmented compensation model as the calibration compensation algorithm.

[0019] The PC-based testing software, connected to the communication interface module, is used to generate calibration reports, execute compensation algorithms, and integrate standard source data with sensor data to be calibrated.

[0020] Preferably, the hardware integration host includes a 20-channel sensor interface; in the 20-channel sensor interface:

[0021] Channels 1-16 are used for single-type sensors, while channels 17-20 support multi-type sensor expansion interfaces for I²C data transmission. Each channel 1-16 is configured with an independent signal conditioning circuit, which includes anti-aliasing filtering and ADC driving circuit. Channels 17-20 are equipped with an adaptive interface protocol dynamic switching mechanism and are designed to connect several sensor probes of different types without power interruption, and trigger an automatic calibration process through hardware interrupt.

[0022] Preferably, the sensor type identification module includes:

[0023] The data parsing unit is used to parse the raw sensor signals collected by the main control module and to collect the impedance characteristics and voltage range of the sensor to be calibrated.

[0024] The type identification unit stores a preset impedance-voltage mapping table and matches the sensor type based on the impedance-voltage mapping table and the acquired impedance characteristics and voltage range.

[0025] The model calling unit is used to transmit the sensor type identification result to the main control module and obtain the segmented compensation model for calibrating the sensor to be calibrated, which is matched by the main control module in the segmented compensation model library based on the identification result. The segmented compensation model library is stored in the calibration data storage module.

[0026] Preferably, the construction of the segmented compensation model library includes the following steps:

[0027] Based on the comparison between standard source data and raw data from sensor samples, the nonlinear range of multi-parameter physical quantities is defined, including temperature, humidity, and pressure.

[0028] Within each nonlinear interval, the least squares method is used to fit the polynomial compensation model, and the fitting error is calculated.

[0029] If the fitting error corresponding to a certain nonlinear interval exceeds the preset threshold, the nonlinear interval will be further divided and the compensation model will be refitted.

[0030] The parameters of the compensation models for all nonlinear regions are stored in the calibration data storage module to form a piecewise compensation model library.

[0031] Preferably, the invocation rules of the segmented compensation model include:

[0032] The main control module determines the nonlinear interval based on the physical quantity measurement values ​​of the sensor to be calibrated uploaded by the model calling unit;

[0033] If the current interval is different from the previous interval, the compensation model switching logic is triggered, and a smooth transition algorithm is executed to perform a transition switch of the segmented compensation model.

[0034] After switching the segmented compensation model, record the switching event and switching timestamp, and update the compensation model version information in the calibration report.

[0035] Preferably, the calibration compensation algorithm is used to calibrate different types of sensors, wherein:

[0036] For platinum resistance thermometers, the acquired temperature range is divided into N segments. Each segment is fitted with a quadratic or cubic polynomial. By minimizing the sum of squared fitting errors, the coefficients of each segment are determined. , and The calibrated temperature value is: ,in, , This is the resistance value of the platinum resistance sensor;

[0037] For thermocouple sensors, the cold junction temperature is collected and converted into an equivalent voltage according to the IEC 60584 standard calibration table. The corrected total voltage is: ,in, The voltage value collected by the thermocouple sensor. This is the equivalent voltage value corresponding to the cold junction temperature.

[0038] Preferably, for a platinum resistance sensor, the relationship between its resistance and temperature is as follows:

[0039]

[0040] in, The nominal resistance of the platinum resistance sensor at 0°C. , , This is the temperature value.

[0041] Preferably, for thermocouple sensors, the actual temperature is obtained using linear interpolation, and the expression for the actual temperature is:

[0042]

[0043] in, This is the upper limit of the temperature range. This is the lower limit of the temperature range. This represents the voltage value corresponding to the lower limit of the temperature range. This is the voltage value corresponding to the upper limit of the temperature range.

[0044] Preferably, the impedance-voltage mapping table is dynamically updated in the following manner:

[0045] When a new sensor is detected, the system automatically collects its impedance characteristics and voltage range, and uploads them to the cloud database through the PC-side detection software.

[0046] The cloud database uses clustering algorithms to classify historical data and generate a new impedance-voltage mapping table;

[0047] The updated impedance and voltage mapping table is synchronized to the main control module via OTA for real-time updates of the local impedance and voltage mapping table.

[0048] Secondly, this application discloses a sensor intelligent calibration method, applied to the sensor intelligent calibration system described above, the method comprising the following steps:

[0049] The hardware integration host connects to several different types of sensor probes and standard sources, and the hardware integration host is configured with multiple sensor interface channels.

[0050] The main control module is used to acquire raw signals from the sensors.

[0051] Store the sensor probe's serial number, compensation parameters, and calibration date to the calibration data storage module;

[0052] The communication interface module interacts with the PC-based testing software to transmit calibration data and issue control commands.

[0053] The sensor type identification module acquires the impedance characteristics and voltage range of the sensor to be calibrated, identifies the type of sensor to be calibrated, and matches the corresponding piecewise compensation model. The matched piecewise compensation model is then used as the calibration compensation algorithm.

[0054] The main control module executes the calibration compensation algorithm to calibrate the sensor to be calibrated.

[0055] The PC-based testing software generates a calibration report and integrates standard source data with the data from the sensor to be calibrated to form a complete calibration record.

[0056] Beneficial effects: The intelligent sensor calibration system and method of this application, through the multi-channel design of the hardware integrated host, realizes convenient access and real-time calibration of various types of sensors, reducing the time spent on device switching; through the sensor type identification module based on impedance characteristics and voltage range matching segmented compensation model, it solves the problem of wide-temperature-range nonlinear compensation, improving the calibration accuracy of sensors such as platinum resistance thermometers and thermocouples; through the calibration data storage module and PC-side testing software, it integrates standard source data to generate calibration reports, realizing full life cycle data management and quality traceability, thereby improving the adaptability to various sensors, improving calibration efficiency, data consistency and scalability. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a structural block diagram of the intelligent sensor calibration system provided in an embodiment of this application. Detailed Implementation

[0059] The technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0060] In this document, the term "comprising" is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0061] This embodiment provides, in a first aspect, a method such as Figure 1 The intelligent sensor calibration system shown is designed to achieve intelligent calibration and full lifecycle management of sensors. Specifically, the system includes a hardware integrated host, a main control module, a calibration data storage module, a communication interface module, a sensor type identification module, and PC-based testing software.

[0062] In detail

[0063] The hardware-integrated host is equipped with multiple sensor interface channels for connecting several sensor probes and standard sources of different types. In this embodiment, the standard source can be a high-precision reference signal generator that can output stable physical quantities (such as temperature, pressure, voltage, current, etc.) or electrical signals (such as standard voltage, frequency, resistance value, etc.). The accuracy level of its output value is much higher than that of the sensor to be calibrated. The reference signal output by the standard source serves as standard source data (such as temperature standard source data, pressure standard source data, electrical standard source data, and other physical quantity standard source data).

[0064] In this embodiment, the hardware integration host includes a 20-channel sensor interface; in the 20-channel sensor interface:

[0065] Channels 1-16 are used for single-type sensors, while channels 17-20 support multi-type sensor expansion interfaces for I²C data transmission. This means channels 17-20 can be used for data transmission of different types of sensor probes based on I²C data transmission. Each channel 1-16 is equipped with an independent signal conditioning circuit, including anti-aliasing filtering and an ADC driver circuit. Channels 17-20 have an adaptive interface protocol dynamic switching mechanism, such as adaptively switching to interface protocols like Modbus RTU, CANopen, and I²C based on the protocol type of the connected sensor probe. It also supports hot-swapping, meaning that channels 17-20 can directly insert or remove sensor probes while the system is running normally (without power off or interrupted), allowing access to several different types of sensor probes and triggering an automatic calibration process via a hardware interrupt.

[0066] The main control module, connected to the hardware integrated host, is used to acquire the raw sensor signals and perform calibration compensation algorithms on the raw sensor signals.

[0067] In this embodiment, the main control module can be any of the existing technologies, and multiple microcontrollers (such as 8 microcontrollers to process 1-16 channels) can be used to collect the original signals from the sensor.

[0068] The calibration data storage module, connected to the main control module, is used to store the sensor probe's serial number, compensation parameters, and calibration date.

[0069] In this embodiment, the calibration data storage module can use EEPROM / Flash and support OTA updates.

[0070] The communication interface module is connected to the main control module and is used to interact with the PC-side detection software.

[0071] In this embodiment, the communication interface module can interact with the PC-side detection software using RS-485 / Modbus / CAN protocols.

[0072] The sensor type identification module, connected to the main control module, is used to identify the type of the sensor by its impedance characteristics and voltage range, and match the corresponding segmented compensation model, using the matched segmented compensation model as the calibration compensation algorithm.

[0073] In this embodiment, the sensor type identification module includes:

[0074] The data parsing unit communicates with the main control module and is used to parse the original sensor signals collected by the main control module and collect the impedance characteristics (such as 100Ω and 1000Ω of platinum resistance) and voltage range (such as 0-5V and 0-10V) of the sensor to be calibrated.

[0075] The type identification unit, connected to the data parsing unit, stores a preset impedance and voltage mapping table (e.g., 100Ω for a platinum resistance thermometer corresponds to 0-5V, and 10kΩ for a thermocouple corresponds to 0-10V), and matches the sensor type based on the impedance and voltage mapping table and the acquired impedance characteristics and voltage range.

[0076] The model calling unit communicates with the type recognition unit and the main control module. It is used to transmit the sensor type recognition result to the main control module and obtain the segmented compensation model for calibrating the sensor to be calibrated, which is matched by the main control module in the segmented compensation model library based on the recognition result. The segmented compensation model library is stored in the calibration data storage module.

[0077] Furthermore, the construction of the segmented compensation model library includes the following steps:

[0078] The sensor sample is placed in a standard temperature and humidity environment (such as a constant temperature and humidity chamber), and standard source data and sensor raw data are collected. Based on the comparison between the standard source data and the sensor sample raw data, the nonlinear range of multiple physical quantities is divided (such as the temperature 0-100℃ is divided into 3 segments). The multiple physical quantities include temperature, humidity and pressure. The sensor sample can be a sample with multiple different physical quantity parameters prepared according to empirical values.

[0079] Within each nonlinear interval, the least squares method is used to fit the polynomial compensation model, and the fitting error is calculated.

[0080] If the fitting error corresponding to a certain nonlinear interval exceeds a preset threshold (e.g., 0.5℃), the nonlinear interval will be further divided, and the compensation model will be refitted until the error meets the standard.

[0081] The parameters of the compensation model for all nonlinear intervals (as described later) , and The data is stored in the calibration data storage module to form a segmented compensation model library.

[0082] Feasible, the invocation rules of the segmented compensation model include:

[0083] The main control module determines the nonlinear interval based on the physical quantity measurement values ​​(such as temperature values) of the sensor to be calibrated uploaded by the model calling unit;

[0084] If the current interval is different from the previous interval, the compensation model switching logic is triggered, and a smooth transition algorithm is executed to perform a transition switch of the segmented compensation model (such as linear interpolation or S-curve transition) to avoid abrupt changes in output.

[0085] After switching the segmented compensation model, record the switching event and switching timestamp, and update the compensation model version information in the calibration report.

[0086] Based on the above, the calibration compensation algorithm is used to calibrate different types of sensors, wherein:

[0087] For platinum resistance thermometers, the acquired temperature range is divided into N segments (2-3 ends). Referring to the calibration table of IEC 60751 standard, each segment is fitted with a quadratic or cubic polynomial. By minimizing the sum of squared fitting errors, the coefficients of each segment are determined. , and The calibrated temperature value is: ,in, , This is the resistance value of the platinum resistance sensor;

[0088] For thermocouple sensors, the cold junction temperature of the thermocouple sensor is collected (which can be the ambient temperature). According to the IEC 60584 standard calibration table, the cold junction temperature is converted into an equivalent voltage. The corrected total voltage is: ,in, The voltage value collected by the thermocouple sensor. This is the equivalent voltage value corresponding to the cold junction temperature.

[0089] Furthermore, for a platinum resistance sensor, the relationship between its resistance and temperature is as follows:

[0090]

[0091] in, The nominal resistance of the platinum resistance sensor at 0°C. , , This is the temperature value.

[0092] In addition, for thermocouple sensors, the actual temperature is obtained through linear interpolation, and the expression for the actual temperature is:

[0093]

[0094] in, This is the upper limit of the temperature range. This is the lower limit of the temperature range. This represents the voltage value corresponding to the lower limit of the temperature range. This is the voltage value corresponding to the upper limit of the temperature range.

[0095] To ensure the accuracy of the mapping relationship, in this embodiment, the impedance-voltage mapping table is dynamically updated in the following way:

[0096] When a new sensor is detected, the system automatically collects its impedance characteristics and voltage range, and uploads them to the cloud database through the PC-side detection software.

[0097] The cloud database uses clustering algorithms (such as K-means clustering) to classify historical data and generate new impedance-voltage mapping tables;

[0098] The updated impedance and voltage mapping table is synchronized to the main control module via OTA (Over-The-Air, a technology for remote management of terminal device data via mobile communication air interface) for real-time updates of the local impedance and voltage mapping table.

[0099] The PC-based testing software, connected to the communication interface module, is used to generate calibration reports, execute compensation algorithms, and integrate standard source data with data from the sensor to be calibrated. This PC-based testing software is the software that controls and implements intelligent sensor calibration; it stores corresponding computer programs that, when executed, perform the corresponding functions of the aforementioned system components. A section of pseudocode is shown below:

[0100] loat raw_temp = read_sensor_temp(); / / Read the raw temperature

[0101] float A = eeprom_read(probe_id + 0); / / Read compensation parameters from EEPROM

[0102] float B = eeprom_read(probe_id + 4);

[0103] float calibrated_temp = raw_temp * A + B

[0104] The physical process corresponding to the above procedure is as follows: First, the sensor probe is calibrated in a standard temperature and humidity environment (such as a constant temperature and humidity chamber). The sensor probe is connected to the hardware integration host. The hardware integration host determines the sensor type through the corresponding interface. The user selects the probe serial number in the PC-side testing software. The system matches the compensation algorithm and writes the compensation parameters into the corresponding main control module to realize the calibration compensation of the sensor probe (i.e., the main control module reads the raw data → retrieves the corresponding parameters from the calibration data storage module → executes the calibration compensation algorithm → outputs the correction value).

[0105] Based on the above, the intelligent sensor calibration system of this embodiment achieves unified access and signal acquisition of multiple types of sensors through a multi-channel sensor interface host; based on sensor type identification and a piecewise compensation model library, it uses the least squares method to fit a polynomial compensation model and supports dynamic updates; it integrates standard source data and sensor data through PC-side testing software to generate a standardized calibration report and record the compensation model version and switching events, achieving full lifecycle management; it supports hot-swapping functionality and automatic calibration triggered by hardware interrupts through a hardware integrated host interface, reducing manual operation and improving testing efficiency; it solves problems such as discrete testing equipment, fixed compensation algorithms, and scattered data, realizing intelligent calibration and full lifecycle management of sensors.

[0106] This embodiment provides a second aspect of a sensor intelligent calibration method, applied to the sensor intelligent calibration system described above, the method comprising the following steps:

[0107] The hardware integration host connects to several different types of sensor probes and standard sources, and the hardware integration host is configured with multiple sensor interface channels.

[0108] The main control module is used to acquire raw signals from the sensors.

[0109] Store the sensor probe's serial number, compensation parameters, and calibration date to the calibration data storage module;

[0110] The communication interface module interacts with the PC-based testing software to transmit calibration data and issue control commands.

[0111] The sensor type identification module acquires the impedance characteristics and voltage range of the sensor to be calibrated, identifies the type of sensor to be calibrated, and matches the corresponding piecewise compensation model. The matched piecewise compensation model is then used as the calibration compensation algorithm.

[0112] The main control module executes the calibration compensation algorithm to calibrate the sensor to be calibrated.

[0113] The PC-based testing software generates a calibration report and integrates standard source data with the data from the sensor to be calibrated to form a complete calibration record.

[0114] It should be noted that the intelligent sensor calibration method of this embodiment corresponds to the aforementioned intelligent sensor calibration system. Therefore, the parts of the intelligent sensor calibration method described in this embodiment (including but not limited to specific implementation techniques and effects) can be referred to the relevant records in the aforementioned intelligent sensor calibration system, and will not be repeated here.

[0115] In the embodiments provided in this application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor may be implemented in one or more of the following: application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments may be performed by a computer program instructing the associated hardware. During implementation, the program may be stored in a computer-readable storage medium or transmitted as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media may be any available medium accessible to a computer. Computer-readable storage media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.

[0116] Finally, it should be noted that the above description is only a preferred embodiment of this application and is not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A sensor intelligent calibration system, characterized in that, The system includes: The hardware-integrated host is equipped with multiple sensor interface channels for connecting several sensor probes of different types and standard sources; The main control module, connected to the hardware integrated host, is used to acquire the raw sensor signals and perform calibration compensation algorithms on the raw sensor signals; A calibration data storage module, connected to the main control module, is used to store the sensor probe's serial number, compensation parameters, and calibration date. A communication interface module, connected to the main control module, is used for data interaction with the PC-side detection software; A sensor type identification module, connected to the main control module, is used to identify the type of the sensor by its impedance characteristics and voltage range, and match the corresponding segmented compensation model, using the matched segmented compensation model as the calibration compensation algorithm. The PC-based testing software, connected to the communication interface module, is used to generate calibration reports and execute compensation algorithms, and to integrate standard source data with sensor data to be calibrated. The sensor type identification module includes: The data parsing unit is used to parse the raw sensor signals collected by the main control module and to collect the impedance characteristics and voltage range of the sensor to be calibrated. The type identification unit stores a preset impedance-voltage mapping table and matches the sensor type based on the impedance-voltage mapping table and the acquired impedance characteristics and voltage range. The model calling unit is used to transmit the sensor type identification result to the main control module, and obtain the segmented compensation model for calibrating the sensor to be calibrated, which is matched by the main control module in the segmented compensation model library based on the identification result. The segmented compensation model library is stored in the calibration data storage module. The construction of the segmented compensation model library includes the following steps: Based on the comparison between standard source data and raw data from sensor samples, the nonlinear range of multi-parameter physical quantities is defined, including temperature, humidity, and pressure. Within each nonlinear interval, the least squares method is used to fit the polynomial compensation model, and the fitting error is calculated. If the fitting error corresponding to a certain nonlinear interval exceeds the preset threshold, the nonlinear interval will be further divided and the compensation model will be refitted. The parameters of the compensation models for all nonlinear regions are stored in the calibration data storage module to form a piecewise compensation model library; The invocation rules of the segmented compensation model include: The main control module determines the nonlinear interval based on the physical quantity measurement values ​​of the sensor to be calibrated uploaded by the model calling unit; If the current interval is different from the previous interval, the compensation model switching logic is triggered, and a smooth transition algorithm is executed to perform a transition switch of the segmented compensation model. After switching the segmented compensation model, record the switching event and switching timestamp, and update the compensation model version information in the calibration report.

2. The intelligent sensor calibration system according to claim 1, characterized in that, The hardware integration host includes a 20-channel sensor interface; in the 20-channel sensor interface: Channels 1-16 are for single-type sensors, while channels 17-20 support multi-type sensor expansion interfaces for I²C data transmission; Each of channels 1-16 is equipped with an independent signal conditioning circuit, which includes an anti-aliasing filter and an ADC driving circuit. Channels 17-20 are equipped with an adaptive interface protocol dynamic switching mechanism and are designed to be able to connect several sensor probes of different types without power interruption, and trigger the automatic calibration process through hardware interrupt.

3. The intelligent sensor calibration system according to claim 1, characterized in that, The calibration compensation algorithm is used to calibrate different types of sensors, wherein: For platinum resistance thermometers, the acquired temperature range is divided into N segments. Each segment is fitted with a quadratic or cubic polynomial. By minimizing the sum of squared fitting errors, the coefficients of each segment are determined. , and The calibrated temperature value is: ,in, , This is the resistance value of the platinum resistance sensor; For thermocouple sensors, the cold junction temperature is collected and converted into an equivalent voltage according to the IEC 60584 standard calibration table. The corrected total voltage is: ,in, The voltage value collected by the thermocouple sensor. This is the equivalent voltage value corresponding to the cold junction temperature.

4. The intelligent sensor calibration system according to claim 3, characterized in that, For a platinum resistance sensor, the relationship between its resistance and temperature is as follows: in, The nominal resistance of the platinum resistance sensor at 0°C. , , This is the temperature value.

5. The intelligent sensor calibration system according to claim 3, characterized in that, For thermocouple sensors, the actual temperature is obtained through linear interpolation, and the expression for the actual temperature is: in, This is the upper limit of the temperature range. This is the lower limit of the temperature range. This represents the voltage value corresponding to the lower limit of the temperature range. This is the voltage value corresponding to the upper limit of the temperature range.

6. The intelligent sensor calibration system according to claim 1, characterized in that, The impedance-voltage mapping table is dynamically updated in the following way: When a new sensor is detected, the system automatically collects its impedance characteristics and voltage range, and uploads them to the cloud database through the PC-side detection software. The cloud database uses clustering algorithms to classify historical data and generate a new impedance-voltage mapping table; The updated impedance and voltage mapping table is synchronized to the main control module via OTA for real-time updates of the local impedance and voltage mapping table.

7. A sensor intelligent calibration method, applied to the sensor intelligent calibration system as described in any one of claims 1-6, characterized in that, The method includes the following steps: The hardware integration host connects to several different types of sensor probes and standard sources, and the hardware integration host is configured with multiple sensor interface channels. The main control module is used to acquire raw signals from the sensors. Store the sensor probe's serial number, compensation parameters, and calibration date to the calibration data storage module; The communication interface module interacts with the PC-based testing software to transmit calibration data and issue control commands. The sensor type identification module acquires the impedance characteristics and voltage range of the sensor to be calibrated, identifies the type of sensor to be calibrated, and matches the corresponding piecewise compensation model. The matched piecewise compensation model is then used as the calibration compensation algorithm. The main control module executes the calibration compensation algorithm to calibrate the sensor to be calibrated. The PC-based testing software generates a calibration report and integrates standard source data with data from the sensor to be calibrated to form a complete calibration record.

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