An adaptive thermometer-hygrometer calibration method

Abstract

This invention discloses an adaptive temperature and humidity meter calibration method. The method involves placing the temperature and humidity meter to be calibrated and a high-precision reference temperature and humidity device together in the same sealed constant temperature and humidity calibration environment and starting them with the same sampling frequency. A preset temperature and humidity gradient for the sealed constant temperature and humidity calibration environment is established, and the environment is controlled to adjust according to this gradient. A chip module controls a temperature and humidity sensing module to continuously collect raw temperature and humidity data multiple times, performs moving average filtering, and obtains the calibration data of the temperature and humidity meter under this gradient and the standard temperature and humidity data of the high-precision reference temperature and humidity device, forming a calibration dataset. The chip module performs temperature and humidity calibration calculations based on the calibration dataset, using a third-order polynomial fitting algorithm to obtain the calibrated temperature data and a piecewise linear interpolation algorithm to obtain the calibrated humidity data.

Description

Technical Field

[0001] This invention relates to the field of temperature and humidity measurement and calibration technology, and in particular to an adaptive temperature and humidity meter calibration method. Background Technology

[0002] The accuracy and stability of temperature and humidity measurements depend not only on the performance of the sensor itself but also on the calibration method. Existing temperature and humidity calibration methods mostly employ fixed-point calibration and simple linear fitting, which have the following drawbacks: the calibration method is simple and cannot effectively compensate for the nonlinearity of temperature and humidity sensors, cross-interference of temperature and humidity, and hysteresis effects; the calibration parameters are fixed and cannot adapt to measurement drift caused by environmental changes and device aging; the calibration process is complex and requires external professional equipment, making it impossible to achieve automatic calibration and parameter updates by the equipment itself.

[0003] Among the currently published patents, such as the design patent with publication number CN216050011U, its calibration method is simple fixed-point calibration, which cannot compensate for sensor nonlinearity and cross-interference.

[0004] Therefore, it is of great significance to develop an adaptive method that is compatible with temperature and humidity sensors and BLE SoC architecture and can automatically complete calibration and compensation. Summary of the Invention

[0005] In view of the above-mentioned shortcomings in the current temperature and humidity measurement and calibration technology, the present invention provides an adaptive temperature and humidity meter calibration method, which uses third-order or higher polynomial fitting for temperature calibration and combines piecewise linear interpolation for humidity calibration, effectively compensating for nonlinearity, cross-interference and hysteresis effects, and achieving high accuracy after calibration.

[0006] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0007] An adaptive temperature and humidity meter calibration method is provided for calibrating a temperature and humidity meter, the temperature and humidity meter including a connected temperature and humidity sensing module and a chip module, and further comprising:

[0008] Place the thermometer and hygrometer to be calibrated together with the high-precision reference temperature and humidity device in the same closed constant temperature and humidity calibration environment and start them at the same sampling frequency.

[0009] The temperature and humidity gradient of the closed constant temperature and humidity calibration environment is preset, and the closed constant temperature and humidity calibration environment is adjusted according to the preset temperature and humidity gradient.

[0010] The chip module controls the temperature and humidity sensing module to continuously collect raw temperature and humidity data multiple times, performs moving average filtering processing, and obtains the calibration data of the temperature and humidity meter under the temperature and humidity gradient and the standard temperature and humidity data of the high-precision reference temperature and humidity device to form a calibration dataset.

[0011] The chip module performs temperature and humidity calibration operations based on the calibration dataset. It uses a third-order polynomial fitting algorithm to obtain the calibrated temperature data and a piecewise linear interpolation algorithm to obtain the calibrated humidity data.

[0012] According to one aspect of the present invention, the temperature calibration operation includes: extracting the raw temperature data collected by the temperature and humidity sensing module and the standard temperature data of the high-precision reference temperature and humidity device, establishing a temperature calibration model, and calculating the calibrated temperature data.

[0013] According to one aspect of the invention, it further includes: setting T raw For the original temperature data, set T ref For the standard temperature data, set T cal For the calibrated temperature data, a0, a1, a2, and a3 are set as the first temperature fitting coefficient, the second temperature fitting coefficient, the third temperature fitting coefficient, and the fourth temperature fitting coefficient, respectively. Then, the temperature calibration model is: .

[0014] According to one aspect of the present invention, the humidity calibration calculation includes:

[0015] Extract the raw humidity data collected by the temperature and humidity sensing module, the standard humidity data from the high-precision reference temperature and humidity device, and the calibrated temperature data under the corresponding temperature and humidity gradient;

[0016] A piecewise linear interpolation algorithm is used to establish a humidity calibration model by using the calibrated temperature data as an auxiliary input, in order to compensate for the cross-interference and hysteresis effect of temperature and humidity.

[0017] The temperature range is divided into temperature segments. Within each temperature segment, a linear interpolation formula is used to establish the correspondence between the original humidity data and the standard humidity data, thus completing the humidity calibration.

[0018] According to one aspect of the present invention, the chip module further includes: comparing the calibrated data with standard temperature and humidity data, and calculating the calibration error; if the error is within a set threshold range, the calibration is qualified; if the error is outside the set threshold range, the temperature and humidity gradient is readjusted and recalibrated.

[0019] According to one aspect of the present invention, the control of the closed constant temperature and humidity calibration environment to adjust according to a preset temperature and humidity gradient includes: gradually adjusting the temperature and humidity of the closed constant temperature and humidity calibration environment from the minimum value of the working range of the temperature and humidity sensing module to the maximum value.

[0020] According to one aspect of the present invention, the sealed constant temperature and humidity calibration environment maintains the temperature and humidity for a certain period of time at each temperature and humidity gradient, at least 5 minutes and at most 10 minutes, to ensure that the temperature and humidity are uniform and without fluctuation.

[0021] According to one aspect of the present invention, the temperature and humidity meter is provided with a data storage unit, which is connected to the chip module and is used to store data transmitted by the chip module.

[0022] According to one aspect of the present invention, the chip module repeatedly collects the calibration data of the thermometer and hygrometer under each temperature and humidity gradient and the standard temperature and humidity data of the high-precision reference temperature and humidity device, and stores the collected data in the data storage unit.

[0023] According to one aspect of the present invention, the chip module stores the calibrated temperature data and the calibrated humidity data in a data storage unit as calibration parameters and measurement corrections for subsequent real-time measurements.

[0024] The advantages of this invention are: temperature calibration is performed using third-order or higher polynomial fitting, and humidity calibration is performed using piecewise linear interpolation, which effectively compensates for nonlinearity, cross-interference and hysteresis effects. After calibration, the temperature accuracy is ≤ ±0.05℃ and the humidity accuracy is ≤ ±1%RH. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic flowchart of an adaptive temperature and humidity meter calibration method according to the present invention.

[0027] Figure 2 This is a schematic diagram of the structure of a thermometer and hygrometer according to the adaptive thermometer and hygrometer calibration method of the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Example 1

[0030] like Figure 1 and Figure 2 As shown, an adaptive hygrometer calibration method is used to calibrate a hygrometer.

[0031] The thermometer and hygrometer include a housing and a circuit board installed inside the housing. The circuit board has a temperature and humidity sensing module and a chip module connected in sequence. The chip module has a built-in DC-DC power supply module that outputs a stable 3.3V voltage to avoid power ripple affecting the sampling accuracy of the temperature and humidity sensing module. The chip module uses an EFR32BG22SoC, and the temperature and humidity sensing module uses an SHT45 sensor. The sampling frequency of the temperature and humidity sensing module is set to 10Hz, and eight raw data points are continuously read for each acquisition. A moving average filter is used to eliminate measurement noise and ensure stable sampling data. It also includes an RTC timing module and a data storage module connected to the chip module. The data storage module is used to store the data transmitted by the chip module.

[0032] It also includes the following steps:

[0033] S1: Place the thermometer and hygrometer to be calibrated together with the high-precision reference temperature and humidity device in the same closed constant temperature and humidity calibration environment, and start them with the same sampling frequency.

[0034] The thermometer and hygrometer to be calibrated, along with the high-precision reference temperature and humidity device, must be placed together in the same sealed, constant-temperature and constant-humidity calibration environment to ensure complete consistency in their temperature and humidity conditions, with a maximum distance of 15cm between them. When starting the thermometer and hygrometer and the high-precision reference temperature and humidity device, their sampling frequencies are adjusted to be consistent; in this embodiment, it is set to 10 SPS to ensure synchronized sampling and eliminate calibration errors caused by sampling time differences. The chip module controls the temperature and humidity sensing module to enter calibration mode, ensuring the sensor module reaches its operating temperature and preheating for 5 to 10 minutes. The high-precision reference temperature and humidity device has an accuracy of ±0.01℃ for temperature and ±0.5%RH for humidity.

[0035] The closed temperature and humidity calibration environment is set as a closed temperature and humidity chamber. The closed temperature and humidity chamber is initially adjusted to a state without fluctuations, with a temperature range of -40℃ to 85℃ and a humidity range of 0%RH to 100%RH. The environmental fluctuation is ≤±0.05℃ / ±0.1%RH.

[0036] S2: Preset the temperature and humidity gradient of the closed constant temperature and humidity calibration environment, and control the closed constant temperature and humidity calibration environment to adjust according to the preset temperature and humidity gradient.

[0037] The temperature and humidity of the closed, constant-temperature and constant-humidity calibration environment are controlled according to a preset temperature and humidity gradient, gradually adjusting from the minimum to the maximum value of the temperature and humidity sensing module's operating range to achieve full-range coverage. Under each temperature and humidity gradient, the closed, constant-temperature and constant-humidity calibration environment maintains stable temperature and humidity for 5 to 10 minutes to ensure uniform temperature and humidity without fluctuations.

[0038] S3: The chip module controls the temperature and humidity sensing module to continuously collect raw temperature and humidity data multiple times, perform moving average filtering processing, and obtain the calibration data of the temperature and humidity meter under the temperature and humidity gradient and the standard temperature and humidity data of the high-precision reference temperature and humidity device to form a calibration dataset.

[0039] The chip module controls the temperature and humidity sensing module to continuously acquire raw temperature and humidity data eight times, performs moving average filtering, and obtains the calibration data for that temperature gradient. Simultaneously, the chip module records the standard temperature and humidity data from a high-precision reference temperature and humidity device, forming a one-to-one corresponding calibration dataset. Afterward, the chip module repeats the above steps to complete the data acquisition for all temperature and humidity gradients and stores the acquired calibration data in the data storage unit.

[0040] S4: The chip module performs temperature and humidity calibration operations based on the calibration dataset. It uses a third-order polynomial fitting algorithm to obtain the calibrated temperature data and a piecewise linear interpolation algorithm to obtain the calibrated humidity data.

[0041] This involves extracting the raw temperature data collected by the temperature and humidity sensing module and the standard temperature data from the high-precision reference temperature and humidity device, and setting T... raw For the original temperature data, set T ref For the standard temperature data, set T cal For the calibrated temperature data, a0, a1, a2, and a3 are set as the first, second, third, and fourth temperature fitting coefficients, respectively. A temperature calibration model is established using a third-order polynomial fitting algorithm, which can be upgraded to fourth-order or higher according to accuracy requirements. The calibrated temperature data is then calculated. The temperature calibration model formula is: The chip module stores the fitting coefficients and calibrated temperature data in the data storage unit, which serves as calibration parameters for subsequent real-time measurements.

[0042] The chip module performs humidity calibration based on the temperature-calibrated parameters and the cross-interference characteristics of temperature and humidity from the temperature and humidity sensing module, using a piecewise linear interpolation algorithm. The chip module then extracts humidity-related data from the calibration dataset, including the raw humidity data H collected by the temperature and humidity sensing module. raw Standard humidity data H from high-precision reference temperature and humidity equipment ref and the calibrated temperature data T under the corresponding temperature and humidity gradient cal A piecewise linear interpolation algorithm is used to interpolate the calibrated temperature data T. calAs an auxiliary input, a humidity calibration model is established to compensate for the cross-interference and hysteresis effect of temperature and humidity. The piecewise linear interpolation algorithm includes: dividing the temperature range into segments with an interval of ≤1℃ between each segment, and using a linear interpolation formula within each segment to establish the original humidity data H. raw Compared with standard humidity data H ref The chip module establishes a correspondence between humidity parameters and data, enabling rapid humidity calibration. It stores the calibration parameters and the calibrated humidity data in a data storage unit for subsequent real-time measurement and correction.

[0043] After calibration, the chip module controls the entire device to enter normal operation mode, collecting temperature and humidity data from the temperature and humidity sensor module and inputting it into the calibration module to obtain calibrated data. The chip module compares the calibrated data with standard temperature and humidity data and calculates the calibration error. The error threshold range is set as follows: temperature error ≤ ±0.05℃, humidity error ≤ ±1%RH. If the error is within the set threshold range, the calibration is considered successful. If the error is outside the set threshold range, the process returns to step S2, readjusts the temperature and humidity gradient density, increases the amount of data collected, and recalibrates. During normal operation of the entire device, the chip module automatically initiates the calibration process, re-collects data, updates calibration parameters, and dynamically compensates for measurement drift caused by device aging and environmental changes, ensuring long-term measurement stability.

[0044] The advantages of this invention are: temperature calibration is performed using third-order or higher polynomial fitting, and humidity calibration is performed using piecewise linear interpolation, which effectively compensates for nonlinearity, cross-interference and hysteresis effects. After calibration, the temperature accuracy is ≤ ±0.05℃ and the humidity accuracy is ≤ ±1%RH.

[0045] Example 2

[0046] like Figure 1 and Figure 2 As shown, an adaptive hygrometer calibration method is used to calibrate a hygrometer.

[0047] The thermometer and hygrometer include a housing and a circuit board installed inside the housing. The circuit board has a temperature and humidity sensing module and a chip module connected in sequence. The chip module has a built-in DC-DC power supply module that outputs a stable 3.3V voltage to avoid power ripple affecting the sampling accuracy of the temperature and humidity sensing module. The chip module uses an EFR32BG22SoC, and the temperature and humidity sensing module uses an SHT45 sensor. The sampling frequency of the temperature and humidity sensing module is set to 10Hz, and eight raw data points are continuously read for each acquisition. A moving average filter is used to eliminate measurement noise and ensure stable sampling data. It also includes an RTC timing module and a data storage module connected to the chip module. The data storage module is used to store the data transmitted by the chip module.

[0048] It also includes the following steps:

[0049] S1: Place the thermometer and hygrometer to be calibrated together with the high-precision reference temperature and humidity device in the same closed constant temperature and humidity calibration environment, and start them with the same sampling frequency.

[0050] The thermometer and hygrometer to be calibrated, along with the high-precision reference temperature and humidity device, must be placed together in the same sealed, constant-temperature and constant-humidity calibration environment to ensure complete consistency in their temperature and humidity conditions, with a maximum distance of 15cm between them. When starting the thermometer and hygrometer and the high-precision reference temperature and humidity device, their sampling frequencies are adjusted to be consistent; in this embodiment, it is set to 10 SPS to ensure synchronized sampling and eliminate calibration errors caused by sampling time differences. The chip module controls the temperature and humidity sensing module to enter calibration mode, ensuring the sensor module reaches its operating temperature and preheating for 5 to 10 minutes. The high-precision reference temperature and humidity device has an accuracy of ±0.01℃ for temperature and ±0.5%RH for humidity.

[0051] The closed temperature and humidity calibration environment is set as a closed temperature and humidity chamber. The closed temperature and humidity chamber is initially adjusted to a state without fluctuations, with a temperature range of -40℃ to 85℃ and a humidity range of 0%RH to 100%RH. The environmental fluctuation is ≤±0.05℃ / ±0.1%RH.

[0052] S2: Preset the temperature and humidity gradient of the closed constant temperature and humidity calibration environment, and control the closed constant temperature and humidity calibration environment to adjust according to the preset temperature and humidity gradient.

[0053] The temperature and humidity of the closed, constant-temperature and constant-humidity calibration environment are controlled according to a preset temperature and humidity gradient, gradually adjusting from the minimum to the maximum value of the temperature and humidity sensing module's operating range to achieve full-range coverage. Under each temperature and humidity gradient, the closed, constant-temperature and constant-humidity calibration environment maintains stable temperature and humidity for 5 to 10 minutes to ensure uniform temperature and humidity without fluctuations.

[0054] S3: The chip module controls the temperature and humidity sensing module to continuously collect raw temperature and humidity data multiple times, perform moving average filtering processing, and obtain the calibration data of the temperature and humidity meter under the temperature and humidity gradient and the standard temperature and humidity data of the high-precision reference temperature and humidity device to form a calibration dataset.

[0055] The chip module controls the temperature and humidity sensing module to continuously acquire raw temperature and humidity data eight times, performs moving average filtering, and obtains the calibration data for that temperature gradient. Simultaneously, the chip module records the standard temperature and humidity data from a high-precision reference temperature and humidity device, forming a one-to-one corresponding calibration dataset. Afterward, the chip module repeats the above steps to complete the data acquisition for all temperature and humidity gradients and stores the acquired calibration data in the data storage unit.

[0056] S4: The chip module performs temperature and humidity calibration operations based on the calibration dataset. It uses a third-order polynomial fitting algorithm to obtain the calibrated temperature data and a piecewise linear interpolation algorithm to obtain the calibrated humidity data.

[0057] The process involves extracting raw temperature data from a temperature and humidity sensing module and standard temperature data from a high-precision reference temperature and humidity device. The raw temperature data (Traw) is defined as the raw temperature data, the standard temperature data (Tref) as the standard temperature data, and the calibrated temperature data (Tcal) as the calibrated temperature data. Coefficients a0, a1, a2, and a3 are defined as the first, second, third, and fourth temperature fitting coefficients, respectively. A temperature calibration model is established using a third-order polynomial fitting algorithm, which can be upgraded to fourth-order or higher algorithms based on accuracy requirements. The calibrated temperature data is then calculated. The temperature calibration model formula is: The chip module stores the fitting coefficients and calibrated temperature data in the data storage unit, which serves as calibration parameters for subsequent real-time measurements.

[0058] The chip module performs humidity calibration based on the temperature-calibrated parameters and the cross-interference characteristics of temperature and humidity sensing modules, employing a piecewise linear interpolation algorithm. The chip module extracts humidity-related data from the calibration dataset, including raw humidity data (Hraw) collected by the temperature and humidity sensing modules, standard humidity data (Href) from a high-precision reference temperature and humidity device, and calibrated temperature data (Tcal) under the corresponding temperature and humidity gradient. Using the calibrated temperature data (Tcal) as auxiliary input, a piecewise linear interpolation algorithm is used to establish a humidity calibration model, compensating for temperature and humidity cross-interference and hysteresis effects. The piecewise linear interpolation algorithm involves dividing the temperature range into segments with an interval of ≤1℃, and using a linear interpolation formula within each segment to establish the correspondence between the raw humidity data (Hraw) and the standard humidity data (Href), quickly completing the humidity calibration. The chip module stores the humidity calibration parameters and the calibrated humidity data in a data storage unit for subsequent real-time measurement correction.

[0059] After calibration, the chip module controls the entire device to enter normal operation mode, collecting temperature and humidity data from the temperature and humidity sensor module and inputting it into the calibration module to obtain calibrated data. The chip module compares the calibrated data with standard temperature and humidity data and calculates the calibration error. The error threshold range is set as follows: temperature error ≤ ±0.05℃, humidity error ≤ ±1%RH. If the error is within the set threshold range, the calibration is considered successful. If the error is outside the set threshold range, the process returns to step S2, readjusts the temperature and humidity gradient density, increases the amount of data collected, and recalibrates. During normal operation of the entire device, the chip module automatically initiates the calibration process, re-collects data, updates calibration parameters, and dynamically compensates for measurement drift caused by device aging and environmental changes, ensuring long-term measurement stability.

[0060] In this embodiment, temperature gradients are set for 12 key nodes, including -40℃, -30℃, -20℃, -10℃, 0℃, 10℃, 20℃, 30℃, 40℃, 50℃, 60℃, and 85℃. The ranges from -40℃ to 0℃ and from 60℃ to 85℃ are designated as cross-interference sensitive zones, which will be further refined later. Humidity gradients are set for 9 key nodes, including 20%RH, 30%RH, 40%RH, 50%RH, 60%RH, 70%RH, 80%RH, 90%RH, and 100%RH. The ranges from 0%RH to 20%RH and from 90%RH to 100%RH are designated as edge zones, which will be further refined later. The temperature and humidity meter to be calibrated is placed together with a high-precision reference temperature and humidity device in a constant temperature and humidity chamber. The environment is kept stable for 10 minutes under each temperature and humidity gradient to ensure uniform temperature and humidity without fluctuations. Simultaneously, 10 sets of valid data were collected for each temperature and humidity gradient. Each set of data was the result of 8 moving averages. The average value of the 10 sets of data was taken as the calibration sample for that temperature and humidity gradient, including the raw temperature data T collected by the temperature and humidity sensing module. raw And the original humidity data H raw And standard temperature data T from high-precision reference temperature and humidity equipment. ref and standard humidity data H ref After all temperature and humidity gradients are collected, the calibration samples are compiled into a calibration dataset and stored in the data storage unit within the chip module. During temperature calibration, a third-order polynomial fitting algorithm is used to compensate for the temperature nonlinearity error of the temperature and humidity sensing module, and the calibrated temperature data is calculated in real time. The least squares method is used to fit the temperature calibration samples, ensuring that the calibrated temperature data T... cal Compared with standard temperature data T ref The solution minimizes the sum of squared residuals, yields specific fitting coefficients, and writes them into the data storage unit. During normal operation of the device, the chip module collects raw temperature data T from the temperature and humidity sensor module. rawThen, the data is directly substituted into the temperature calibration model, resulting in low computational load and low power consumption, suitable for low-power requirements. During humidity calibration, the temperature is segmented, dividing the entire temperature range from -40℃ to 85℃ into segments. Specifically, 0℃ to 60℃ is designated as the normal range, with each segment being 1℃, totaling 61 segments; -40℃ to 0℃ and 60℃ to 85℃ are designated as sensitive ranges, with each segment being 0.5℃, totaling 115 segments. The entire range has 176 temperature segments, ensuring coverage of all measurement ranges and compensating for cross-interference. Simultaneously, within each temperature segment, nodes are set according to the humidity range from 0%RH to 100%RH. Specifically, 20%RH to 90%RH is designated as the normal range, with each node being 1%RH, totaling 71 nodes; 90%RH to 100%RH is designated as the edge range, with each node being 1%RH, totaling 11 nodes; the 0%RH to 20%RH range has very few application scenarios and is not calibrated. The raw humidity data H in each temperature segment raw With the corresponding standard humidity data H ref A one-to-one correspondence is established to generate an initial segmented interpolation table. For the raw humidity data between two adjacent humidity nodes, a linear interpolation algorithm is used to calculate the corresponding standard humidity correction value, which is then added to the initial segmented interpolation table to form a complete segmented interpolation table. The complete segmented interpolation table is then subjected to error verification, and outlier data is removed to ensure that the error between the correction value and the standard value for each node is ≤ ±0.1%RH. After optimization, the data is stored in the data storage unit. During calibration verification, five non-calibrated temperature and humidity points are randomly selected, and raw humidity data H is collected. raw Compared with the original temperature data T raw Substituting the values ​​into the temperature calibration model and the humidity piecewise interpolation table respectively, we obtain the calibrated temperature data T. cal Compared with the calibrated humidity data H cal The calibration is considered successful if the temperature error is ≤ ±0.1 degrees Celsius and the humidity error is ≤ 1%RH compared with the standard source value. During dynamic updates, the chip module automatically triggers a full-process calibration every two months during normal operation of the equipment. This re-collects calibration data, updates the temperature fitting coefficient and humidity segmented interpolation table, compensates for measurement drift caused by device aging and environmental changes, and ensures long-term stability.

[0061] The advantages of this invention are: temperature calibration is performed using third-order or higher polynomial fitting, and humidity calibration is performed using piecewise linear interpolation, which effectively compensates for nonlinearity, cross-interference and hysteresis effects. After calibration, the temperature accuracy is ≤ ±0.05℃ and the humidity accuracy is ≤ ±1%RH.

[0062] Example 3

[0063] like Figure 1 and Figure 2 As shown, an adaptive hygrometer calibration method is used to calibrate a hygrometer.

[0064] The thermometer and hygrometer include a housing and a circuit board installed inside the housing. The circuit board has a temperature and humidity sensing module and a chip module connected in sequence. The chip module has a built-in DC-DC power supply module that outputs a stable 3.3V voltage to avoid power ripple affecting the sampling accuracy of the temperature and humidity sensing module. The chip module uses an EFR32BG22SoC, and the temperature and humidity sensing module uses an SHT45 sensor. The sampling frequency of the temperature and humidity sensing module is set to 10Hz, and eight raw data points are continuously read for each acquisition. A moving average filter is used to eliminate measurement noise and ensure stable sampling data. It also includes an RTC timing module and a data storage module connected to the chip module. The data storage module is used to store the data transmitted by the chip module.

[0065] It also includes the following steps:

[0066] S1: Place the thermometer and hygrometer to be calibrated together with the high-precision reference temperature and humidity device in the same closed constant temperature and humidity calibration environment, and start them with the same sampling frequency.

[0067] The thermometer and hygrometer to be calibrated, along with the high-precision reference temperature and humidity device, must be placed together in the same sealed, constant-temperature and constant-humidity calibration environment to ensure complete consistency in their temperature and humidity conditions, with a maximum distance of 15cm between them. When starting the thermometer and hygrometer and the high-precision reference temperature and humidity device, their sampling frequencies are adjusted to be consistent; in this embodiment, it is set to 10 SPS to ensure synchronized sampling and eliminate calibration errors caused by sampling time differences. The chip module controls the temperature and humidity sensing module to enter calibration mode, ensuring the sensor module reaches its operating temperature and preheating for 5 to 10 minutes. The high-precision reference temperature and humidity device has an accuracy of ±0.01℃ for temperature and ±0.5%RH for humidity.

[0068] The closed temperature and humidity calibration environment is set as a closed temperature and humidity chamber. The closed temperature and humidity chamber is initially adjusted to a state without fluctuations, with a temperature range of -40℃ to 85℃ and a humidity range of 0%RH to 100%RH. The environmental fluctuation is ≤±0.05℃ / ±0.1%RH.

[0069] S2: Preset the temperature and humidity gradient of the closed constant temperature and humidity calibration environment, and control the closed constant temperature and humidity calibration environment to adjust according to the preset temperature and humidity gradient.

[0070] The temperature and humidity of the closed, constant-temperature and constant-humidity calibration environment are controlled according to a preset temperature and humidity gradient, gradually adjusting from the minimum to the maximum value of the temperature and humidity sensing module's operating range to achieve full-range coverage. Under each temperature and humidity gradient, the closed, constant-temperature and constant-humidity calibration environment maintains stable temperature and humidity for 5 to 10 minutes to ensure uniform temperature and humidity without fluctuations.

[0071] S3: The chip module controls the temperature and humidity sensing module to continuously collect raw temperature and humidity data multiple times, perform moving average filtering processing, and obtain the calibration data of the temperature and humidity meter under the temperature and humidity gradient and the standard temperature and humidity data of the high-precision reference temperature and humidity device to form a calibration dataset.

[0072] The chip module controls the temperature and humidity sensor to continuously acquire raw temperature and humidity data eight times, performs moving average filtering, and obtains the calibration data for that temperature gradient. Simultaneously, the chip module records the standard temperature and humidity data from a high-precision reference temperature and humidity device, forming a one-to-one calibration dataset. The chip module then repeats the above steps to complete the data acquisition for all temperature and humidity gradients and stores the acquired calibration data in the data storage unit.

[0073] S4: The chip module performs temperature and humidity calibration operations based on the calibration dataset. It uses a third-order polynomial fitting algorithm to obtain the calibrated temperature data and a piecewise linear interpolation algorithm to obtain the calibrated humidity data.

[0074] The process involves extracting raw temperature data from a temperature and humidity sensing module and standard temperature data from a high-precision reference temperature and humidity device. The raw temperature data (Traw) is defined as the raw temperature data, the standard temperature data (Tref) as the standard temperature data, and the calibrated temperature data (Tcal) as the calibrated temperature data. Coefficients a0, a1, a2, and a3 are defined as the first, second, third, and fourth temperature fitting coefficients, respectively. A temperature calibration model is established using a third-order polynomial fitting algorithm, which can be upgraded to fourth-order or higher algorithms based on accuracy requirements. The calibrated temperature data is then calculated. The temperature calibration model formula is: The chip module stores the fitting coefficients and calibrated temperature data in the data storage unit, which serves as calibration parameters for subsequent real-time measurements.

[0075] The chip module performs humidity calibration based on the temperature-calibrated parameters and the cross-interference characteristics of temperature and humidity sensing modules, employing a piecewise linear interpolation algorithm. The chip module extracts humidity-related data from the calibration dataset, including raw humidity data (Hraw) collected by the temperature and humidity sensing modules, standard humidity data (Href) from a high-precision reference temperature and humidity device, and calibrated temperature data (Tcal) under the corresponding temperature and humidity gradient. Using the calibrated temperature data (Tcal) as auxiliary input, a piecewise linear interpolation algorithm is used to establish a humidity calibration model, compensating for temperature and humidity cross-interference and hysteresis effects. The piecewise linear interpolation algorithm involves dividing the temperature range into segments with an interval of ≤1℃, and using a linear interpolation formula within each segment to establish the correspondence between the raw humidity data (Hraw) and the standard humidity data (Href), quickly completing the humidity calibration. The chip module stores the humidity calibration parameters and the calibrated humidity data in a data storage unit for subsequent real-time measurement correction.

[0076] After calibration, the chip module controls the entire device to enter normal operation mode, collecting temperature and humidity data from the temperature and humidity sensor module and inputting it into the calibration module to obtain calibrated data. The chip module compares the calibrated data with standard temperature and humidity data and calculates the calibration error. The error threshold range is set as follows: temperature error ≤ ±0.05℃, humidity error ≤ ±1%RH. If the error is within the set threshold range, the calibration is considered successful. If the error is outside the set threshold range, the process returns to step S2, readjusts the temperature and humidity gradient density, increases the amount of data collected, and recalibrates. During normal operation of the entire device, the chip module automatically initiates the calibration process, re-collects data, updates calibration parameters, and dynamically compensates for measurement drift caused by device aging and environmental changes, ensuring long-term measurement stability.

[0077] In this embodiment, the temperature calibration samples are set as shown in the table below:

[0078]

[0079] The first temperature fitting coefficient a0 is set to 0.021, the second temperature fitting coefficient a1 to 0.9978, and the third temperature fitting coefficient a2 to 1.52 × 10⁻⁶. -5 The fourth temperature fitting coefficient, a3, is 7.8 × 10⁻⁶. -8 The temperature calibration model is then: .

[0080] When T is collected raw When the temperature is 20.05℃, substitute the values ​​into the formula: The error at this point is: This meets the accuracy requirements.

[0081] In this embodiment, the humidity calibration samples are set as shown in the table below:

[0082]

[0083] When the calibrated temperature is 20.00℃, the temperature-segmented humidity interpolation table is as follows:

[0084]

[0085] Collect raw humidity data H raw =60.4%RH, original temperature data T raw =20.05℃, the calibrated temperature data T is obtained after temperature calibration. cal =20.00℃, matching the 20.00℃ temperature segment, the standard humidity data H is obtained from the table. ref =60.00℃, then the calibrated humidity data H cal=60.00%RH, with an error of 0.00%RH.

[0086] When the raw humidity data H is collected raw =15.25%RH, original temperature data T raw At 20.05℃, the calibrated temperature data T is obtained after temperature calibration. cal =20.00℃, match the 20.00℃ temperature segment, and obtain the adjacent node H by looking up the table. raw =10.2%RH and H raw =20.3%RH, perform linear interpolation calculation: And the error is: This meets the accuracy requirements.

[0087] When performing calibration verification, five non-calibrated temperature and humidity points were randomly selected to verify the calibration accuracy. The test data is shown in the table below:

[0088]

[0089] All test points showed temperature errors ≤0.01℃ and humidity errors ≤0.03℃, meeting the calibration accuracy requirement of ≤±0.1℃ / ±1%RH, and were therefore qualified for calibration.

[0090] During normal operation, temperature calibration consumes ≤8% of the chip module's computing power, and humidity calibration consumes ≤5%. In terms of device power consumption, the sleep current is ≤0.17μA, and the normal operating current is ≤1mA. In battery life testing, using a 3.6V / 2000mAh lithium-ion battery, the battery life can reach over 18 months, meeting the requirements for low-power usage.

[0091] The advantages of this invention are: temperature calibration is performed using third-order or higher polynomial fitting, and humidity calibration is performed using piecewise linear interpolation, which effectively compensates for nonlinearity, cross-interference and hysteresis effects. After calibration, the temperature accuracy is ≤ ±0.05℃ and the humidity accuracy is ≤ ±1%RH.

[0092] Example 4

[0093] An adaptive wireless thermo-hygrometer calibration method is provided, based on the adaptive thermo-hygrometer calibration method described in Embodiment 1, for calibrating wireless thermo-hygrometers.

[0094] The wireless thermometer and hygrometer includes a housing and a circuit board installed inside the housing. The circuit board has a temperature and humidity sensing module, a Bluetooth chip module, and a Bluetooth radio frequency module connected in sequence. The Bluetooth chip module has a built-in DC-DC power supply module that outputs a stable 3.3V voltage to avoid power ripple affecting the sampling accuracy of the temperature and humidity sensing module. The Bluetooth chip module uses an EFR32BG22SoC, and the temperature and humidity sensing module uses an SHT45 sensor. The sampling frequency of the temperature and humidity sensing module is set to 10Hz, and eight raw data points are continuously read for each acquisition. A moving average filter is used to eliminate measurement noise and ensure stable sampling data. It also includes an RTC timing module and a data storage module connected to the Bluetooth chip module, and an antenna connected to the Bluetooth radio frequency module. The data storage module stores the data transmitted by the Bluetooth chip module, and the antenna receives and transmits information transmitted by the Bluetooth radio frequency module.

[0095] It also includes the following steps:

[0096] S1: Place the wireless thermometer and hygrometer to be calibrated together with the high-precision reference temperature and humidity device in the same closed constant temperature and humidity calibration environment, and start them with the same sampling frequency.

[0097] The wireless thermometer and hygrometer to be calibrated, along with the high-precision reference temperature and humidity device, must be placed together in the same sealed, constant-temperature and constant-humidity calibration environment to ensure that their temperature and humidity environments are completely identical, and the distance between them is no more than 15cm. When starting the wireless thermometer and hygrometer and the high-precision reference temperature and humidity device, their sampling frequencies are adjusted to be the same; in this embodiment, it is set to 10SPS to ensure sampling synchronization and eliminate calibration errors caused by sampling time differences. The Bluetooth chip module controls the temperature and humidity sensing module to enter calibration mode, ensuring the operating temperature of the temperature and humidity sensing module and preheating it for 5 to 10 minutes. The accuracy of the high-precision reference temperature and humidity device is ±0.01℃ for temperature and ±0.5%RH for humidity.

[0098] The closed temperature and humidity calibration environment is set as a closed temperature and humidity chamber. The closed temperature and humidity chamber is initially adjusted to a state without fluctuations, with a temperature range of -40℃ to 85℃ and a humidity range of 0%RH to 100%RH. The environmental fluctuation is ≤±0.05℃ / ±0.1%RH.

[0099] S2: Preset the temperature and humidity gradient of the closed constant temperature and humidity calibration environment, and control the closed constant temperature and humidity calibration environment to adjust according to the preset temperature and humidity gradient.

[0100] The temperature and humidity of the closed, constant-temperature and constant-humidity calibration environment are controlled according to a preset temperature and humidity gradient, gradually adjusting from the minimum to the maximum value of the temperature and humidity sensing module's operating range to achieve full-range coverage. Under each temperature and humidity gradient, the closed, constant-temperature and constant-humidity calibration environment maintains stable temperature and humidity for 5 to 10 minutes to ensure uniform temperature and humidity without fluctuations.

[0101] S3: The Bluetooth chip module controls the temperature and humidity sensing module to continuously collect raw temperature and humidity data multiple times, perform moving average filtering processing, and obtain the calibration data of the wireless temperature and humidity meter under the temperature and humidity gradient and the standard temperature and humidity data of the high-precision reference temperature and humidity device to form a calibration dataset.

[0102] The Bluetooth chip module controls the temperature and humidity sensing module to continuously collect raw temperature and humidity data eight times, performs moving average filtering, and obtains the calibration data for that temperature gradient. Simultaneously, the Bluetooth chip module records the standard temperature and humidity data from a high-precision reference temperature and humidity device, forming a one-to-one corresponding calibration dataset. Afterward, the Bluetooth chip module repeats the above steps to complete the data collection for all temperature and humidity gradients and stores the collected calibration data in the data storage unit.

[0103] S4: The Bluetooth chip module performs temperature and humidity calibration calculations based on the calibration dataset. It uses a third-order polynomial fitting algorithm to obtain the calibrated temperature data and a piecewise linear interpolation algorithm to obtain the calibrated humidity data.

[0104] This involves extracting the raw temperature data collected by the temperature and humidity sensing module and the standard temperature data from the high-precision reference temperature and humidity device, and setting T... raw For the original temperature data, set T ref For the standard temperature data, set T cal For the calibrated temperature data, a0, a1, a2, and a3 are set as the first, second, third, and fourth temperature fitting coefficients, respectively. A temperature calibration model is established using a third-order polynomial fitting algorithm, which can be upgraded to fourth-order or higher according to accuracy requirements. The calibrated temperature data is then calculated. The temperature calibration model formula is: The Bluetooth chip module stores the fitting coefficients and calibrated temperature data in the data storage unit, which serves as calibration parameters for subsequent real-time measurements.

[0105] The Bluetooth chip module performs humidity calibration based on the temperature-calibrated parameters and the cross-interference characteristics of temperature and humidity from the temperature and humidity sensing module, using a piecewise linear interpolation algorithm. The Bluetooth chip module extracts humidity-related data from the calibration dataset, including the raw humidity data H collected by the temperature and humidity sensing module. raw Standard humidity data H from high-precision reference temperature and humidity equipment ref and the calibrated temperature data T under the corresponding temperature and humidity gradient cal A piecewise linear interpolation algorithm is used to interpolate the calibrated temperature data T. calAs an auxiliary input, a humidity calibration model is established to compensate for the cross-interference and hysteresis effect of temperature and humidity. The piecewise linear interpolation algorithm includes: dividing the temperature range into segments with an interval of ≤1℃ between each segment, and using a linear interpolation formula within each segment to establish the original humidity data H. raw Compared with standard humidity data H ref The Bluetooth chip module quickly completes humidity calibration by establishing the corresponding relationship between the humidity parameters and the calibrated humidity data, which is then stored in the data storage unit for subsequent real-time measurement and correction.

[0106] After calibration, the Bluetooth chip module controls the device to enter normal operation mode, collecting temperature and humidity data from the temperature and humidity sensor module and inputting it into the calibration module to obtain calibrated data. The Bluetooth chip module compares the calibrated data with standard temperature and humidity data and calculates the calibration error. The error threshold range is set as follows: temperature error ≤ ±0.05℃, humidity error ≤ ±1%RH. If the error is within the set threshold range, the calibration is considered successful. If the error is outside the set threshold range, the process returns to step S2, readjusts the temperature and humidity gradient density, increases the amount of data collected, and recalibrates. During normal operation of the device, the Bluetooth chip module automatically initiates the calibration process, re-collects data, updates calibration parameters, and dynamically compensates for measurement drift caused by device aging and environmental changes, ensuring long-term measurement stability.

[0107] The advantages of this invention are: temperature calibration is performed using third-order or higher polynomial fitting, and humidity calibration is performed using piecewise linear interpolation, which effectively compensates for nonlinearity, cross-interference and hysteresis effects. After calibration, the temperature accuracy is ≤ ±0.05℃ and the humidity accuracy is ≤ ±1%RH.

[0108] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An adaptive temperature and humidity meter calibration method, used for calibrating a temperature and humidity meter, characterized in that, The temperature and humidity meter includes a connected temperature and humidity sensing module and a chip module, and also includes: Place the thermometer and hygrometer to be calibrated together with the high-precision reference temperature and humidity device in the same closed constant temperature and humidity calibration environment and start them at the same sampling frequency. The temperature and humidity gradient of the closed constant temperature and humidity calibration environment is preset, and the closed constant temperature and humidity calibration environment is adjusted according to the preset temperature and humidity gradient. The chip module controls the temperature and humidity sensing module to continuously collect raw temperature and humidity data multiple times, perform moving average filtering processing, and obtain the calibration data of the temperature and humidity meter under the temperature and humidity gradient and the standard temperature and humidity data of the high-precision reference temperature and humidity device to form a calibration dataset. The chip module performs temperature and humidity calibration operations based on the calibration dataset. It uses a third-order polynomial fitting algorithm to obtain the calibrated temperature data and a piecewise linear interpolation algorithm to obtain the calibrated humidity data.

2. The adaptive temperature and humidity meter calibration method according to claim 1, characterized in that, The temperature calibration operation includes: extracting the raw temperature data collected by the temperature and humidity sensing module and the standard temperature data of the high-precision reference temperature and humidity device, establishing a temperature calibration model, and calculating the calibrated temperature data.

3. The adaptive temperature and humidity meter calibration method according to claim 2, characterized in that, Also includes: Set T raw For the original temperature data, set T ref For the standard temperature data, set T cal For the calibrated temperature data, a0, a1, a2, and a3 are set as the first temperature fitting coefficient, the second temperature fitting coefficient, the third temperature fitting coefficient, and the fourth temperature fitting coefficient, respectively. Then, the temperature calibration model is: .

4. The adaptive temperature and humidity meter calibration method according to claim 1, characterized in that, The humidity calibration calculation includes: Extract the raw humidity data collected by the temperature and humidity sensing module, the standard humidity data from the high-precision reference temperature and humidity device, and the calibrated temperature data under the corresponding temperature and humidity gradient; A piecewise linear interpolation algorithm is used to establish a humidity calibration model by using the calibrated temperature data as an auxiliary input, in order to compensate for the cross-interference and hysteresis effect of temperature and humidity. The temperature range is divided into temperature segments. Within each temperature segment, a linear interpolation formula is used to establish the correspondence between the original humidity data and the standard humidity data, thus completing the humidity calibration.

5. The adaptive temperature and humidity meter calibration method according to claim 1, characterized in that, Also includes: The chip module compares the calibrated data with the standard temperature and humidity data and calculates the calibration error. If the error is within the set threshold range, the calibration is qualified. If the error is outside the set threshold range, the temperature and humidity gradient is readjusted and recalibrated.

6. The adaptive temperature and humidity meter calibration method according to claim 1, characterized in that, The control of the sealed constant temperature and humidity calibration environment is adjusted according to the preset temperature and humidity gradient, including: gradually adjusting the temperature and humidity of the sealed constant temperature and humidity calibration environment from the minimum value of the working range of the temperature and humidity sensing module to the maximum value.

7. The adaptive temperature and humidity meter calibration method according to claim 6, characterized in that, The closed temperature and humidity calibration environment maintains the temperature and humidity for a certain period of time at each temperature and humidity gradient, at least 5 minutes and at most 10 minutes, to ensure that the temperature and humidity are uniform and without fluctuations.

8. The adaptive temperature and humidity meter calibration method according to any one of claims 1 to 7, characterized in that, The temperature and humidity meter is equipped with a data storage unit, which is connected to the chip module and is used to store the data transmitted by the chip module.

9. The adaptive temperature and humidity meter calibration method according to claim 8, characterized in that, The chip module repeatedly collects the calibration data of the thermometer and hygrometer under each temperature and humidity gradient and the standard temperature and humidity data of the high-precision reference temperature and humidity device, and stores the collected data in the data storage unit.

10. The adaptive temperature and humidity meter calibration method according to claim 8, characterized in that, The chip module stores the calibrated temperature and humidity data in the data storage unit as calibration parameters and measurement corrections for subsequent real-time measurements.

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