Calibration temperature point selection method, device and storage medium for temperature compensation of transmitter

Abstract

The application discloses a method, device and storage medium for selecting a calibration temperature point of a transmitter temperature compensation, comprising: obtaining a temperature drift model of the transmitter in a rated working temperature interval in an uncompensated state; determining virtual zero-point output values and virtual upper-limit reference output values corresponding to each temperature point in a plurality of candidate calibration temperature combinations based on the temperature drift model; determining compensation coefficients corresponding to each candidate calibration temperature combination based on the virtual zero-point output values and the virtual upper-limit reference output values; performing output virtual compensation calculation on each temperature point in the rated working temperature interval after discretization by using the compensation coefficients, and obtaining compensated zero-point output values and compensated upper-limit reference output values corresponding to each temperature point in each candidate calibration temperature combination; and determining an actual calibration temperature point based on a first deviation between the compensated zero-point output values and preset zero-point output values and a second deviation between the compensated upper-limit reference output values and preset upper-limit reference output values.

Description

Technical Field

[0001] This invention relates to the field of transmitter technology, and in particular to a method for selecting calibration temperature points, a computing device, and a readable storage medium for transmitter temperature compensation. Background Technology

[0002] Pressure transmitters are widely used in industrial process control, automotive, aerospace, and other fields. Their zero-point and full-scale outputs experience nonlinear drift due to temperature changes, directly affecting measurement accuracy. Temperature compensation is the core method for improving the transmitter's measurement accuracy across the entire temperature range. However, existing temperature compensation schemes rely on experience in selecting calibration temperature points, lacking scientific quantitative basis, which affects the measurement accuracy across the entire temperature range. Summary of the Invention

[0003] The purpose of this application is to provide a method for selecting calibration temperature points, a computing device, and a readable storage medium for transmitter temperature compensation, which can effectively improve the measurement accuracy of the transmitter across the entire temperature range and improve calibration efficiency.

[0004] To achieve the above objectives: In a first aspect, embodiments of this application provide a method for selecting calibration temperature points for transmitter temperature compensation, the method comprising: Obtain the temperature drift model of the transmitter in the rated operating temperature range under uncompensated conditions. The temperature drift model is used to characterize the change of the zero-point output value and the upper limit reference output value of the transmitter with temperature. Based on the temperature drift model, the virtual zero-point output value and virtual upper limit reference output value corresponding to each temperature point in multiple candidate calibration temperature combinations are determined respectively; each candidate calibration temperature combination contains N temperature points, where N is an integer not less than 2, and the N temperature points are selected from the discretized temperature points within the rated operating temperature range. Based on the virtual zero-point output value and the virtual upper limit reference output value, determine the compensation coefficients corresponding to each group of candidate calibration temperature combinations; Using the compensation coefficient, output virtual compensation calculation is performed on each temperature point after discretization within the rated operating temperature range to obtain the compensated zero-point output value and the compensated upper limit reference output value for each group of candidate calibration temperature combinations with respect to each temperature point. Based on the first deviation between the compensated zero-point output value and the preset zero-point output value, and the second deviation between the compensated upper limit reference output value and the preset upper limit reference output value, the actual calibration temperature point is determined from the multiple sets of candidate calibration temperature combinations.

[0005] In some embodiments, the temperature drift model includes a zero-point output temperature drift sub-model for characterizing the change of the zero-point output value with temperature and an upper limit reference output temperature drift sub-model for characterizing the change of the upper limit reference output value with temperature; obtaining the temperature drift model of the transmitter in the rated operating temperature range under uncompensated conditions includes: The zero-point output measured value and the upper limit reference output measured value of the transmitter are obtained at multiple discretized temperature points within the rated operating temperature range. Based on the measured values ​​of the zero-point output and the measured values ​​of the upper limit benchmark output, the zero-point output temperature drift model and the upper limit benchmark output temperature drift model are established by fitting.

[0006] In some embodiments, the generation of the multiple sets of candidate calibration temperature combinations includes at least one of the following: The rated operating temperature range is discretized using a set temperature step size. From the multiple discretized temperature points obtained, a traversal or combination optimization strategy is used to filter all combinations of N temperature points that meet the distribution requirements of the first, second, and third temperature points, generating the multiple sets of candidate calibration temperature combinations. The rated operating temperature range is divided into a first temperature range, a second temperature range, and a third temperature range in order of temperature value from low to high or from high to low. The first temperature point is selected from the first temperature range, the second temperature point is selected from the second temperature range, and the third temperature point is selected from the third temperature range. N temperature points are selected from a preset set of temperature points and combined to generate the multiple sets of candidate calibration temperature combinations.

[0007] In some embodiments, the compensation coefficient includes a zero-point compensation coefficient and an upper limit reference compensation coefficient; determining the compensation coefficient corresponding to each group of candidate calibration temperature combinations based on the virtual zero-point output value and the virtual upper limit reference output value includes: Based on the virtual zero-point output value and the virtual upper limit benchmark output value, fitting functions corresponding to each group of candidate calibration temperature combinations are constructed by interpolation or fitting, and the coefficients of the fitting functions are determined as the compensation coefficients; the fitting functions include the zero-point fitting function and the upper limit benchmark fitting function.

[0008] In some embodiments, the step of using the compensation coefficient to perform output virtual compensation calculations on each discretized temperature point within the rated operating temperature range to obtain the compensated zero-point output value and the compensated upper limit reference output value for each group of candidate calibration temperature combinations with respect to each temperature point includes: For any discretized temperature point within the rated operating temperature range, based on the compensation coefficient, the zero-point output value of the zero-point fitting function and the upper limit benchmark output value of the upper limit benchmark fitting function at the temperature point are obtained, as well as the target virtual output value of the temperature drift model at the temperature point; the target virtual output value includes the target virtual zero-point output value and the target virtual upper limit benchmark output value. Based on the fitted zero-point output value, the fitted upper limit benchmark output value, the target virtual output value, and the preset zero-point output value and preset upper limit benchmark output value, determine the compensation correction amount corresponding to the temperature point; The compensation correction amount is superimposed on the preset zero-point output value to obtain the compensated output value at the temperature point; the compensated output value includes the compensated zero-point output value and the compensated upper limit reference output value.

[0009] In some embodiments, determining the compensation correction amount corresponding to the temperature point based on the fitted zero-point output value, the fitted upper limit benchmark output value, the target virtual output value, and the preset zero-point output value and the preset upper limit benchmark output value includes: Obtain the offset of the target virtual output value relative to the fitted zero-point output value; The offset is scaled proportionally according to the ratio of the target range to the virtual range, and the scaled offset is determined as the compensation correction amount; the target range is the difference between the preset upper limit reference output value and the preset zero point output value, and the virtual range is the difference between the fitted upper limit reference output value and the fitted zero point output value.

[0010] In some embodiments, determining the actual calibration temperature point from the plurality of candidate calibration temperature combinations includes: Determine the maximum first deviation and the maximum second deviation of the target candidate calibration temperature combination within the rated operating temperature range; the target candidate calibration temperature combination is any of the aforementioned candidate calibration temperature combinations. The larger of the maximum first deviation and the maximum second deviation is determined as the comprehensive deviation of the target candidate calibration temperature combination; Based on the overall deviation, the actual calibration temperature point is determined from the multiple candidate calibration temperature combinations.

[0011] In some embodiments, determining the actual calibration temperature point from the plurality of candidate calibration temperature combinations based on the comprehensive deviation includes at least one of the following: The candidate calibration temperature combination with the smallest overall deviation is determined as the actual calibration temperature point; The actual calibration temperature point is determined from the candidate calibration temperature combinations whose overall deviation is less than or equal to a preset deviation threshold, according to a preset cost optimization strategy.

[0012] Secondly, embodiments of this application provide a computing device, including: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the calibration temperature point selection method for transmitter temperature compensation as described in the first aspect.

[0013] Thirdly, embodiments of this application provide a readable storage medium storing a computer program, which, when executed by a processor, implements the calibration temperature point selection method for transmitter temperature compensation as described in the first aspect.

[0014] The method, computing device, and readable storage medium for selecting calibration temperature points for transmitter temperature compensation provided in this application embodiment include: obtaining a temperature drift model of the transmitter in its uncompensated state within the rated operating temperature range; determining, based on the temperature drift model, the virtual zero-point output value and virtual upper limit reference output value corresponding to each temperature point in multiple candidate calibration temperature combinations; each candidate calibration temperature combination contains N temperature points, where N is an integer not less than 2, and the N temperature points are selected from the discretized temperature points within the rated operating temperature range; determining the compensation coefficients corresponding to each candidate calibration temperature combination based on the virtual zero-point output value and the virtual upper limit reference output value; performing virtual compensation calculations on each discretized temperature point within the rated operating temperature range using the compensation coefficients to obtain the compensated zero-point output value and the compensated upper limit reference output value corresponding to each temperature point in each candidate calibration temperature combination; and determining the actual calibration temperature point from multiple candidate calibration temperature combinations based on a first deviation between the compensated zero-point output value and a preset zero-point output value, and a second deviation between the compensated upper limit reference output value and the preset upper limit reference output value. In this way, by scientifically comparing and quantitatively screening multiple sets of candidate calibration temperature combinations, the blindness of traditional calibration temperature point selection relying on experience is overcome, ensuring that the selected calibration temperature point has the best compensation accuracy or the best accuracy-cost balance in the entire temperature range, thereby effectively improving the full-temperature range measurement accuracy of the transmitter and improving calibration efficiency. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the method for selecting calibration temperature points for transmitter temperature compensation provided in an embodiment of the present invention.

[0016] Figure 2 This is a schematic diagram showing the 0MPa output of a pressure transmitter when tested at different temperatures.

[0017] Figure 3This is a schematic diagram showing the 1MPa output of a pressure transmitter when tested at different temperatures.

[0018] Figure 4 This is a schematic diagram of the full-scale output of a pressure transmitter when tested at different temperatures.

[0019] Figure 5 This is a schematic diagram showing the change of the zero-point output of a cubic polynomial fitting with temperature.

[0020] Figure 6 This is a schematic diagram showing the variation of the 1MPa output with temperature for fitting a cubic polynomial.

[0021] Figure 7 A schematic diagram showing the 0MPa output accuracy after compensation for different candidate calibration temperature combinations.

[0022] Figure 8 A schematic diagram showing the 1MPa output accuracy after compensation for different candidate calibration temperature combinations.

[0023] Figure 9 This is a schematic diagram of the structure of a computing device provided in an embodiment of the present invention. Detailed Implementation

[0024] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. In the following description relating to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements.

[0025] See Figure 1 This application provides a method for selecting calibration temperature points for transmitter temperature compensation. This method can be executed by a device for selecting calibration temperature points for transmitter temperature compensation, which can be implemented using software and / or hardware, such as a computer or server. In this embodiment, a computing device is used as the executing entity. The method provided in this embodiment includes the following steps: S101, Obtain the temperature drift model of the transmitter in the rated operating temperature range under uncompensated conditions. The temperature drift model is used to characterize the changes in the zero-point output value and the upper limit reference output value of the transmitter with temperature.

[0026] The transmitter in this embodiment is a calibrable transmitter with nonlinear temperature drift characteristics. Temperature drift refers to the deviation of the transmitter's zero-point output and / or full-scale output (i.e., the difference between the upper limit reference output and the zero-point output) as the ambient temperature changes. Specifically, it can be divided into zero-point temperature drift and full-scale temperature drift (also known as sensitivity temperature drift). The transmitter can be any one of a pressure transmitter, a differential pressure transmitter, or a level transmitter. The pressure transmitter can be a piezoresistive pressure transmitter, and piezoresistive pressure transmitters include, but are not limited to, diffused silicon pressure transmitters, sputtered thin-film pressure transmitters, ceramic piezoresistive pressure transmitters, sapphire pressure transmitters, and strain gauge pressure transmitters.

[0027] In this context, the uncompensated state refers to the transmitter's state before any temperature compensation processing. Data collected in this state best reflects the transmitter's inherent temperature drift characteristics. The rated operating temperature range refers to the ambient temperature range specified in the transmitter's technical specifications to ensure measurement accuracy, such as -40℃ to 125℃. The temperature drift model is a mathematical function describing the change in the transmitter's output value with temperature. It can include a zero-point output temperature drift sub-model to characterize the change in the zero-point output value with temperature and an upper limit reference output temperature drift sub-model to characterize the change in the upper limit reference output value with temperature. In this embodiment, the temperature drift model can also be called a "virtual transmitter" because it can "virtually" represent the transmitter's output behavior at any temperature in a computing device. The zero-point output value refers to the electrical signal value generated at the transmitter's output terminal when there is zero input signal, such as zero pressure or zero atmospheric pressure. For example, the zero-point output of a transmitter with a 4mA to 20mA output is 4mA. The upper limit reference output value refers to the output value corresponding to the transmitter under the action of an input signal at the upper limit of its rated measurement range. For pressure transmitters, the upper limit reference output value is the output value corresponding to the highest pressure point of the pressure transmitter, such as the full-scale pressure, which can be called the highest pressure point output value; for level transmitters, the upper limit reference output value is the output value corresponding to its highest liquid level, and so on.

[0028] For transmitters of the same model, since they use the same pressure core and electronic components, their temperature drift characteristics are basically consistent across batches. The zero-point output value and upper limit reference output value of a single sample at multiple temperature points can be tested to establish a temperature drift model based on the test data to characterize the change of the zero-point output value and upper limit reference output value of the transmitter with temperature.

[0029] In some embodiments, the temperature drift model includes a zero-point output temperature drift sub-model for characterizing the change of the zero-point output value with temperature and an upper limit reference output temperature drift sub-model for characterizing the change of the upper limit reference output value with temperature; step S101, obtaining the temperature drift model of the transmitter in the rated operating temperature range under uncompensated conditions, includes: Acquire the zero-point output measured value and the upper limit reference output measured value of the transmitter at multiple discretized temperature points within the rated operating temperature range; Based on the measured values ​​of zero-point output and upper limit benchmark output, a zero-point output temperature drift model and an upper limit benchmark output temperature drift model are established by fitting.

[0030] Specifically, the computing device can acquire the zero-point output measured value and the upper limit reference output measured value of multiple discretized temperature points selected within the rated operating temperature range at a set temperature step size (such as 5℃ or 10℃) when the transmitter used as the test sample is not temperature compensated. Then, based on the zero-point output measured value, a zero-point output temperature drift model is established by fitting, and based on the upper limit reference output measured value, an upper limit reference output temperature drift model is established by fitting.

[0031] The discretized temperature points are a finite number of discrete temperature values ​​obtained by dividing the rated operating temperature range, which includes a continuous range of temperature points, into a certain number of discrete step sizes, such as -40℃, -30℃, -20℃, etc. The fitting method can be at least one of the following: regression fitting based on least squares, table lookup combined with linear interpolation, or machine learning algorithms such as neural networks. The regression fitting is a polynomial regression fitting, and the order of the polynomial regression fitting can be quadratic, cubic, or quartic, etc. For example, taking quartic polynomial regression fitting as an example, the zero-point output temperature drift model can be expressed as: , a 0、 a 1. a 2. a 3. a 4 represents the above quartic polynomial equation. Z ( T The coefficients of each term, the upper limit of the benchmark output temperature drift model can be expressed as: , b 0、 b 1. b 2. b 3. b 4 represents the above quartic polynomial equation. H ( T The coefficients of each item, T Indicates temperature.

[0032] Thus, based on the batch consistency of transmitters, using the measured data of transmitters used as test samples to model the temperature drift model can significantly reduce the testing workload in batch production, improve calibration efficiency, and reduce calibration costs.

[0033] In some embodiments, when the temperature drift nonlinearity of the transmitter is lower than a preset threshold, a second-order polynomial is used for fitting; when the temperature drift nonlinearity of the transmitter is higher than the preset threshold and the fitting error of a single-segment high-order polynomial exceeds the standard, a piecewise high-order polynomial is used for fitting.

[0034] Temperature drift nonlinearity is a measure of how much the transmitter's output-temperature curve deviates from linearity, and can be characterized by indicators such as the residual after polynomial fitting. The preset threshold can be set according to actual needs, for example, to 0.1%FS. Exceeding the allowable error in a single-segment high-order polynomial fitting means that the fitting error of a single-segment high-order polynomial exceeds the allowable range (e.g., 0.12%FS), indicating that a single polynomial cannot adequately approximate the measured data across the entire temperature range. The core idea of ​​piecewise high-order polynomial fitting is to divide the entire rated operating temperature range into several continuous sub-intervals, and establish a high-order polynomial (e.g., cubic or quartic) fitting model as the temperature drift model within each sub-interval. Thus, by using a second-order polynomial for fitting transmitters with low nonlinearity, the fitting and computational complexity can be effectively reduced, while using piecewise high-order polynomial fitting for transmitters with high nonlinearity can effectively increase the fitting accuracy.

[0035] S102, based on the temperature drift model, determines the virtual zero-point output value and virtual upper limit reference output value corresponding to each temperature point in multiple candidate calibration temperature combinations; each candidate calibration temperature combination contains N temperature points, where N is an integer not less than 2, and the N temperature points are selected from the discretized temperature points within the rated operating temperature range.

[0036] Here, a candidate calibration temperature combination refers to a set of alternative calibration temperature schemes consisting of several temperature points. For each temperature point in each candidate calibration temperature combination, it is substituted into the two sub-models of the temperature drift model to obtain the virtual zero-point output value and the virtual upper limit reference output value at that temperature point.

[0037] The candidate calibration temperature combinations can be generated through a traversal optimization algorithm or selected from a preset set of temperature points. In some embodiments, the generation of multiple candidate calibration temperature combinations includes at least one of the following: The rated operating temperature range is discretized using a set temperature step size. From the multiple discretized temperature points obtained, a traversal or combination optimization strategy is used to select all combinations of N temperature points that meet the distribution requirements of the first, second, and third temperature points, generating multiple sets of candidate calibration temperature combinations. The rated operating temperature range is divided into the first, second, and third temperature ranges in order of temperature value from low to high or from high to low. The first temperature point is selected from the first temperature range, the second temperature point is selected from the second temperature range, and the third temperature point is selected from the third temperature range. Select N temperature points from a preset set of temperature points and combine them to generate multiple sets of candidate calibration temperature combinations.

[0038] Since the rated operating temperature range is continuous and contains an infinite number of temperature points, it is impossible to list and combine them all. Therefore, it can be discretized into a finite number of operable temperature points. Then, N combinations of temperature points that meet the distribution requirements of the first, second, and third temperature points are selected as candidate calibration temperature combinations. In this example, the rated operating temperature range is divided into three temperature ranges in ascending order of temperature value: the first temperature range, the second temperature range, and the third temperature range. The first temperature range can refer to the area with lower temperatures within the rated operating temperature range, such as the area composed of temperature points near the lower limit of the range; the second temperature range can refer to the area with moderate temperatures within the rated operating temperature range, such as the area composed of temperature points near the middle of the range; and the third temperature range can refer to the area with higher temperatures within the rated operating temperature range, such as the area composed of temperature points near the upper limit of the range. For example, the first temperature range includes the temperature range from the lowest temperature of the rated operating temperature range to one-third of the sum of the lowest and highest temperatures; the second temperature range includes the temperature range from one-third to two-thirds of the sum of the lowest and highest temperatures of the rated operating temperature range; and the third temperature range includes the temperature range from two-thirds of the sum of the lowest and highest temperatures of the rated operating temperature range to the highest temperature. For instance, if the rated temperature range is -40℃ to 125℃, then the first temperature point can be selected from the first temperature range of -40℃ to 15℃, the second temperature point can be selected from the second temperature range of 15℃ to 70℃, and the third temperature point can be selected from the third temperature range of 70℃ to 125℃. Preferably, the first, second, and third temperature ranges together cover the entire rated operating temperature range.

[0039] The process employs two main strategies: First, a traversal strategy is used to select all combinations of N temperature points that satisfy the distribution requirements of the first, second, and third temperature points, generating multiple candidate calibration temperature combinations. This can be achieved by selecting N combinations of N temperature points that meet the distribution requirements from a set of discretized temperature points as the current candidate combination; this process is repeated until all combinations of N temperature points that meet the distribution requirements have been selected, generating multiple candidate calibration temperature combinations to ensure that the candidate calibration temperature combinations cover the global optimal solution. Second, a combinatorial optimization strategy is employed to select all combinations of N temperature points that satisfy the distribution requirements of the first, second, and third temperature points, generating multiple candidate calibration temperature combinations. This can be based on constraints, such as a 30°C interval between the first and second temperature points and a 50°C interval between the third and second temperature points, selecting N temperature points for combination to generate multiple candidate calibration temperature combinations, thereby reducing computational load while maintaining optimization effectiveness.

[0040] When high production efficiency is required and there is no need to pursue global optimization, temperature points can be selected from a preset set of temperature points and combined to generate candidate calibration temperature combinations, thereby significantly reducing the amount of computation. For example, assuming the preset set of temperature points includes -40℃, -30℃, -20℃, 20℃, 25℃, 70℃, 85℃, and 125℃, for the above set of temperature points, a temperature point can be arbitrarily selected from "-40℃, -30℃, -20℃" as the first temperature point, a temperature point can be arbitrarily selected from "20℃, 25℃" as the second temperature point, and a temperature point can be arbitrarily selected from "70℃, 85℃, 125℃" as the third temperature point. The selected temperature points can then be combined to generate candidate calibration temperature combinations, such as "-40℃, 25℃, 85℃" and "-30℃, 20℃, 70℃".

[0041] In this way, by setting up the two generation methods in parallel, a balance between scientific point selection and efficiency is achieved, while ensuring that the candidate calibration temperature combination covers the entire temperature range, further improving the full-temperature range measurement accuracy of the transmitter and increasing calibration efficiency.

[0042] S103 determines the compensation coefficients corresponding to each group of candidate calibration temperature combinations based on the virtual zero-point output value and the virtual upper limit reference output value.

[0043] The compensation coefficients include the zero-point compensation coefficient and the upper limit reference compensation coefficient. The zero-point compensation coefficient is determined based on the virtual zero-point output value corresponding to each temperature point in each group of candidate calibration temperature combinations, and the upper limit reference compensation coefficient is determined based on the virtual upper limit reference output value corresponding to each temperature point in each group of candidate calibration temperature combinations.

[0044] In some embodiments, compensation coefficients corresponding to each group of candidate calibration temperature combinations are determined based on the virtual zero-point output value and the virtual upper limit reference output value, including: Based on the virtual zero-point output value and the virtual upper limit benchmark output value, fitting functions corresponding to each group of candidate calibration temperature combinations are constructed through interpolation or fitting methods, and the coefficients of the fitting functions are determined as compensation coefficients; the fitting functions include the zero-point fitting function and the upper limit benchmark fitting function.

[0045] Specifically, the computing device can construct a zero-point fitting function for each candidate calibration temperature combination based on the virtual zero-point output value corresponding to each temperature point in each group of candidate calibration temperature combinations through interpolation or fitting, and use the coefficients of the zero-point fitting function as the zero-point compensation coefficients of the group of candidate calibration temperature combinations; and, based on the virtual upper limit reference output value corresponding to each temperature point in each group of candidate calibration temperature combinations, construct an upper limit reference fitting function for the group of candidate calibration temperature combinations through interpolation or fitting, and use the coefficients of the upper limit reference fitting function as the upper limit reference compensation coefficients of the group of candidate calibration temperature combinations.

[0046] The fitting function is a continuous mathematical expression describing the change of the output value with temperature, used to replace discrete data points. The zero-point fitting function characterizes the fitting relationship between the zero-point output value and temperature, while the upper limit reference fitting function characterizes the fitting relationship between the upper limit reference output value and temperature. For example, taking N=3 and a quadratic polynomial fitting method, the three temperature points and their corresponding virtual zero-point output values ​​from each candidate calibration temperature combination can be substituted into the quadratic polynomial equation used for zero-point fitting. Solve for the coefficients of the terms in this quadratic polynomial equation. c 0、 c 1. c 2, as the zero-point compensation coefficient; and, substituting the three temperature points and their corresponding virtual upper limit reference output values ​​from each group of candidate calibration temperature combinations into the quadratic polynomial equation used for upper limit reference fitting. Solve for the coefficients of the terms in this quadratic polynomial equation. d 0、 d 1. d 2, as the upper limit benchmark compensation coefficient.

[0047] In this way, by constructing a fitting function through interpolation or fitting and determining the coefficients of the fitting function as compensation coefficients, it is possible to achieve a precise mathematical transformation from discrete "temperature-output value" data points to continuous compensation parameters, and to achieve refined independent compensation of the zero point and upper limit benchmark.

[0048] S104 uses the compensation coefficient to perform output virtual compensation calculations on each temperature point after discretization within the rated operating temperature range, and obtains the compensated zero-point output value and the compensated upper limit reference output value for each group of candidate calibration temperature combinations at each temperature point.

[0049] It is understandable that temperature compensation using the corresponding compensation coefficient can achieve a good compensation effect for any temperature point in a candidate calibration temperature combination. However, this cannot reflect the true compensation effect across the entire rated operating temperature range. Therefore, the compensation output value can be calculated for each discrete temperature point in the entire temperature range (i.e., the rated operating temperature range) to analyze the compensation effect of the compensation coefficient corresponding to each candidate calibration temperature combination. This allows us to know in advance which candidate calibration temperature combinations perform well at non-calibration points (i.e., temperature points not belonging to the candidate calibration temperature combinations) and which have serious errors.

[0050] In some embodiments, virtual compensation calculations are performed on each discretized temperature point within the rated operating temperature range using compensation coefficients to obtain the compensated zero-point output value and the compensated upper limit reference output value for each group of candidate calibration temperature combinations at each temperature point, including: For any discretized temperature point within the rated operating temperature range, the zero-point output value of the zero-point fitting function and the upper limit benchmark output value of the upper limit benchmark fitting function at the temperature point are obtained based on the compensation coefficient, as well as the target virtual output value of the temperature drift model at the temperature point; the target virtual output value includes the target virtual zero-point output value and the target virtual upper limit benchmark output value. Based on the fitted zero-point output value, the fitted upper limit benchmark output value, the target virtual output value, and the preset zero-point output value and preset upper limit benchmark output value, determine the compensation correction amount corresponding to the temperature point; The compensation correction is superimposed on the preset zero-point output value to obtain the compensated output value at the temperature point; the compensated output value includes the compensated zero-point output value and the compensated upper limit reference output value.

[0051] Specifically, for any candidate calibration temperature combination, for any discretized temperature point within the rated operating temperature range, this temperature point is substituted into the zero-point fitting function and the upper limit benchmark fitting function determined by the compensation coefficients corresponding to the candidate calibration temperature combination to obtain the fitted zero-point output value and the fitted upper limit benchmark output value at that temperature point. Simultaneously, this temperature point is substituted into the temperature drift model to obtain the target virtual zero-point output value and the target virtual upper limit benchmark output value at that temperature point. Next, the temperature point is compensated and corrected based on the fitted zero-point output value, the fitted upper limit benchmark output value, the target virtual output value, and the preset zero-point output value and preset upper limit benchmark output value to determine the corresponding compensation correction amount. Then, the compensation correction amount corresponding to this temperature point is superimposed on the preset zero-point output value, i.e., the compensation correction amount corresponding to this temperature point is added to the preset zero-point output value to obtain the compensated zero-point output value and the compensated upper limit benchmark output value at that temperature point. This process is repeated cyclically to obtain the compensated zero-point output value and the compensated upper limit benchmark output value corresponding to each discretized temperature point within the rated operating temperature range for the candidate calibration temperature combination.

[0052] The zero-point output value is calculated by substituting the temperature point into the zero-point fitting function, representing the value of the zero-point temperature drift curve determined by the candidate calibration temperature combination at that temperature point. The upper limit reference output value is calculated by substituting the temperature point into the upper limit reference fitting function, representing the value of the upper limit reference temperature drift curve determined by the candidate calibration temperature combination at that temperature point. The target virtual output value is the output value calculated by substituting the temperature point into the temperature drift model, serving as the original object for subsequent compensation and correction. The preset zero-point output value is the ideal output value of the transmitter at zero input, representing the target value for temperature compensation. For example, the preset zero-point output value for a transmitter with a 4mA to 20mA output is 4mA. The preset upper limit reference output value is the ideal output value of the transmitter at the upper limit of its rated measurement range, representing the target value for temperature compensation. For example, the preset upper limit reference output value for a transmitter with a 4mA to 20mA output is 20mA. The compensated zero-point output value is the value obtained after compensation calculation for the zero-point output, characterizing the result after the zero-point temperature drift has been corrected. The compensated upper limit reference output value is the value obtained after compensation calculation of the upper limit reference output, representing the result after the upper limit reference temperature drift is corrected.

[0053] In this way, a complete transformation from abstract compensation coefficients to specific output values ​​after compensation is achieved, making the compensation effect quantifiable and evaluable. At the same time, calculations are performed on each discrete temperature point to ensure that there are no evaluation blind spots across the entire temperature range, further improving the full-temperature range measurement accuracy of the transmitter.

[0054] In some embodiments, the compensation correction amount corresponding to the temperature point is determined based on the fitted zero-point output value, the fitted upper limit reference output value, the target virtual output value, and the preset zero-point output value and the preset upper limit reference output value, including: Obtain the offset of the target virtual output value relative to the fitted zero-point output value; The offset is scaled proportionally based on the ratio of the target range to the virtual range, and the scaled offset is determined as the compensation correction amount; the target range is the difference between the preset upper limit reference output value and the preset zero point output value, and the virtual range is the difference between the fitted upper limit reference output value and the fitted zero point output value.

[0055] The offset of the target virtual output value relative to the fitted zero-point output value characterizes the degree to which the virtual output value deviates from the fitted zero-point at the current temperature. When calculating the compensated zero-point output value, the offset of the target virtual output value relative to the fitted zero-point output value is used. Conversely, when calculating the compensated upper limit benchmark output value, the offset of the target virtual output value relative to the fitted zero-point output value is used. The ratio of the target range to the virtual range determines the scaling factor of the offset. Scaling the offset proportionally based on the ratio of the target range to the virtual range can be understood as multiplying the offset by this ratio to obtain the scaled offset.

[0056] In this way, the offset of the target virtual output value relative to the fitted zero point is used as the basic correction direction, and the ratio of the target range to the virtual range is used as the scaling factor, so that the compensation correction amount can adaptively adapt to the actual range changes at different temperature points and achieve accurate correction.

[0057] S105, based on the first deviation between the compensated zero-point output value and the preset zero-point output value, and the second deviation between the compensated upper limit reference output value and the preset upper limit reference output value, determines the actual calibration temperature point from multiple candidate calibration temperature combinations.

[0058] Specifically, for each candidate calibration temperature combination, the computing device can calculate the first deviation between the compensated zero-point output value and the compensated upper limit reference output value corresponding to each temperature point after discretization within the rated operating temperature range, and the second deviation between the compensated upper limit reference output value and the preset upper limit reference output value corresponding to each temperature point. Then, based on the first and second deviations corresponding to each candidate calibration temperature combination after discretization within the rated operating temperature range, the actual calibration temperature point is determined from multiple candidate calibration temperature combinations.

[0059] The preset zero-point output value is the ideal output value of the transmitter at zero input, and the preset upper limit reference output value is the ideal output value of the transmitter at the upper limit of its rated measurement range. The deviation is the difference between the compensated output value and the preset output value, used to measure the compensation accuracy at that temperature point. Specifically, it can be an absolute deviation or a relative deviation (such as a percentage deviation relative to full scale). For example, a transmitter with a 4mA to 20mA output has a compensated output value of 20.064mA at -40℃, and a preset output value of 20.000mA. The deviation can be expressed as +0.064mA or 0.400%FS. A deviation greater than zero indicates that the compensated output value is higher than the preset output value, i.e., overcompensation, while a deviation less than zero indicates that the compensated output value is lower than the preset output value, i.e., undercompensation. Furthermore, the smaller the absolute value of the deviation, the higher the compensation accuracy at that temperature point; the larger the absolute value of the deviation, the lower the compensation accuracy at that temperature point. The first deviation reflects the residual error after zero-point temperature drift compensation, while the second deviation reflects the residual error after upper limit reference temperature drift compensation.

[0060] It is understandable that, based on the first and second deviations corresponding to each discretized temperature point within the rated operating temperature range for each candidate calibration temperature combination, the compensation effect of each candidate calibration temperature combination over the entire temperature range can be determined. Therefore, the actual calibration temperature point can be determined from multiple candidate calibration temperature combinations based on the first and second deviations corresponding to each discretized temperature point within the rated operating temperature range for each candidate calibration temperature combination. It should be noted that determining the actual calibration temperature point from multiple candidate calibration temperature combinations can be achieved by selecting one combination as the actual calibration temperature point, such as selecting the candidate calibration temperature combination with the highest accuracy, or by selecting two or more combinations and determining the actual calibration temperature point based on the selected two or more combinations. For example, if each candidate calibration temperature combination includes 3 temperature points and these 3 temperature points are selected from different temperature ranges, and the two candidate calibration temperature combinations with the highest accuracy are selected from multiple candidate calibration temperature combinations, then the average value of the temperature points belonging to the same temperature range in these two candidate calibration temperature combinations can be taken, and then the average value corresponding to the three temperature ranges can be used as the actual calibration temperature point.

[0061] In some embodiments, determining the actual calibration temperature point from a plurality of candidate calibration temperature combinations includes: Determine the maximum first deviation and the maximum second deviation of the target candidate calibration temperature combination within the rated operating temperature range; the target candidate calibration temperature combination can be any candidate calibration temperature combination. The larger of the maximum first deviation and the maximum second deviation is determined as the overall deviation of the target candidate calibration temperature combination; Based on the overall deviation, the actual calibration temperature point is determined from multiple candidate calibration temperature combinations.

[0062] For any candidate calibration temperature combination, i.e., the target candidate calibration temperature combination, a comprehensive analysis of the deviations of all discrete temperature points within the entire temperature range (i.e., the rated operating temperature range) is required to determine the full-temperature range accuracy index of the target candidate calibration temperature combination. Specifically, the computing device determines the maximum first deviation and the maximum second deviation based on the first and second deviations corresponding to each discrete temperature point within the rated operating temperature range of the target candidate calibration temperature combination. Then, the maximum first deviation and the maximum second deviation are compared, and the larger of the two is taken as the comprehensive deviation of the target candidate calibration temperature combination. Finally, based on the comprehensive deviations corresponding to each group of candidate calibration temperature combinations, the actual calibration temperature point is determined from multiple groups of candidate calibration temperature combinations.

[0063] It should be noted that in this embodiment, the maximum first deviation is the maximum absolute value of the first deviation, and the maximum second deviation is the maximum absolute value of the second deviation. The actual calibration temperature point refers to the final determined combination of calibration temperature points to be used for mass production. It can be understood that since the larger of the maximum first deviation and the maximum second deviation represents the worst accuracy of that group of candidate calibration temperature combinations across the entire temperature range, the compensation effect of each group of candidate calibration temperature combinations can be analyzed based on the larger of the maximum first deviation and the maximum second deviation, thereby determining the actual calibration temperature point from multiple groups of candidate calibration temperature combinations. After obtaining the comprehensive deviation of each group of candidate combinations, the actual calibration temperature point can be determined from multiple groups of candidate calibration temperature combinations according to actual needs, such as determining the candidate calibration temperature combination with the smallest comprehensive deviation as the actual calibration temperature point.

[0064] Thus, by determining the maximum zero-point deviation and the maximum upper limit reference deviation separately, and taking the larger of the two as the comprehensive deviation, a unified quantitative evaluation of the compensation effect of each candidate calibration temperature combination across the entire temperature range is achieved.

[0065] In some embodiments, the actual calibration temperature point is determined from multiple combinations of candidate calibration temperatures based on the overall deviation, including at least one of the following: The candidate calibration temperature combination with the smallest overall deviation is determined as the actual calibration temperature point; From the candidate calibration temperature combinations whose overall deviation is less than or equal to the preset deviation threshold, the actual calibration temperature point is determined according to the preset cost optimization strategy.

[0066] It's understandable that for applications requiring extremely high measurement accuracy, the candidate calibration temperature combination with the smallest overall deviation means that using this combination as the actual calibration temperature point can maximize measurement accuracy and minimize measurement errors. For mass production and cost-sensitive applications, the actual calibration temperature point can be determined from candidate calibration temperature combinations with an overall deviation less than or equal to a preset deviation threshold (e.g., accuracy less than or equal to 0.5%FS) according to a preset cost optimization strategy. This preset cost optimization strategy is a pre-defined criterion used to evaluate the cost of different calibration temperature combinations, such as minimizing the temperature point span, ensuring the temperature point is closest to room temperature, and being the easiest to implement. The temperature point span refers to the temperature difference between the highest and lowest temperatures in the calibration temperature combination. A smaller span results in shorter heating and cooling times for the high and low temperature chambers, lower energy consumption, and higher calibration efficiency. Furthermore, the closer the temperature point is to room temperature, the less heating or cooling is required during calibration, the lower the equipment requirements, and the lower the calibration cost.

[0067] It should be noted that when the overall deviation of each candidate calibration temperature combination exceeds the preset deviation threshold, it indicates that none of the candidate calibration temperature combinations can meet the accuracy requirements. In this case, the generation parameters of the candidate calibration temperature combinations can be readjusted, such as reducing the temperature step size or expanding the rated operating temperature range, and the evaluation can be performed again. In this way, by providing multiple optimization strategies, a flexible balance between accuracy requirements and calibration costs can be achieved.

[0068] In summary, the method provided in the above embodiments overcomes the blindness of traditional calibration temperature point selection relying on experience by scientifically comparing and quantitatively screening multiple sets of candidate calibration temperature combinations. It ensures that the selected calibration temperature point has the best compensation accuracy or the best accuracy-cost balance in the entire temperature range, thereby effectively improving the full-temperature range measurement accuracy of the transmitter and improving calibration efficiency.

[0069] Based on the same inventive concept as the foregoing embodiments, the above method will be described in detail below through a specific example. In this example, the transmitter is a pressure transmitter, N is 3, and the upper limit reference output value is the output value of the highest pressure point.

[0070] The core steps of this method can be divided into pressure transmitter testing, establishing a temperature drift model, establishing a temperature compensation model, calculating candidate point outputs, determining compensation parameters, evaluating accuracy across the entire temperature range, selecting the optimal combination, and batch application, as detailed below: 1. Pressure Transmitter Testing: For pressure transmitters of the same model, since they use the same pressure core and electronic components, their temperature drift characteristics are basically the same across batches. Therefore, the characteristics of the entire batch can be reflected by testing a single pressure transmitter. In this example, zero-point output at different temperatures within the operating temperature range (i.e., the rated operating temperature range) is tested on an uncompensated pressure transmitter. Z (T and full-scale output S ( T To perform testing, if the operating temperature of a commonly used pressure transmitter is -40℃ to 125℃, the zero-point output of the pressure transmitter can be tested every 10℃ starting from -40℃. Z ( T and the highest pressure point output H ( T Full-scale output is S ( T )= H ( T )- Z ( T This allows us to obtain the measured data of the pressure transmitter.

[0071] 2. Establishing a Temperature Drift Model: Based on batch consistency, collect discrete temperature-output data of representative samples within the operating temperature range. Use polynomial fitting (e.g., cubic or quartic polynomials) to establish high-order nonlinear mathematical models, i.e., temperature drift models, characterizing the zero-point output, maximum pressure point output, and full-scale output as a function of temperature. The output value at any temperature can then be extrapolated from this model. The following explanation uses a quartic polynomial to establish the temperature drift model: (1) The fourth-order polynomial model is:

[0072]

[0073]

[0074] in, a 0、 a 1. a 2. a 3. a 4 is a quartic polynomial equation Z ( T The coefficients of each item, b 0、 b 1. b 2. b 3. b 4 is a quartic polynomial equation H ( T The coefficients of each item, T Indicates temperature.

[0075] (2) Construct a system of normal equations Taking the temperature drift polynomial at zero-point output as an example (the calculation of the temperature drift polynomial at the highest pressure point is the same), according to the least squares method, we need to minimize the sum of squared errors, that is:

[0076] in, T i Indicates the first i A temperature point, i Let be positive integers. By taking the partial derivatives with respect to the coefficients and setting them to 0, we obtain the system of equations.

[0077] (3) Solving the above system of equations will yield the coefficients of the polynomial.

[0078] 3. Establish a temperature compensation model: Construct a temperature compensation model that includes zero-point offset compensation coefficient, full-scale gain compensation coefficient, and high-order nonlinear compensation coefficient, and set an independent set of zero-point / full-scale temperature drift compensation parameters.

[0079] 1) Define variables Current temperature: T ; Current measured zero point: Z ( T ); Current highest measured pressure point: H ( T ); Measured full-scale output: S ( T ), S ( T )= H ( T )- Z ( T ); Zero-point output (with zero input): Z 1. Z 2. Z 3 (corresponding to respectively) T 1. T 2. T Output at time 3); Full-scale / maximum pressure output: H 1. H 2. H 3 (corresponding to respectively) T 1. T 2. T Output at time 3); Preset zero-point output value: Z set Preset upper limit baseline output value: H set The target range is S set = H set - Z set ; Yraw For any measured output value (i.e., calculated using the temperature drift model, also known as the target virtual output value), if it is a zero-point output, then Yraw for Z ( T If the output is at the highest point, then... Yraw for H ( T ); Ycal This is the output after temperature compensation calibration, also known as the compensated output value.

[0080] 2) Zero-point output fitting (quadratic polynomial) Zero-point output values ​​based on three selected temperature points ( T 1, Z 1) ( T 2, Z 2), ( T 3, Z 3), parsed out parameters c 0、 c 1. c 2.

[0081] 3) Fitting the output at the highest pressure point (quadratic polynomial) Output value based on the highest pressure point of the three selected temperature points ( T 1, H 1) ( T 2, H 2), ( T 3, H 3) Analyze the quadratic polynomial. parameters d 0、 d 1. d 2.

[0082] 4) Temperature compensation formula

[0083] 4. Screening candidate calibration temperature combinations: From the transmitter's rated operating temperature range, based on accuracy requirements, multiple candidate calibration temperature combinations are generated through a traversal / combination optimization algorithm (each group contains one temperature point each for low temperature T1, medium temperature T2, and high temperature T3).

[0084] 5. Calculate the output and compensation coefficients corresponding to each group of candidate calibration temperature combinations: Substitute the three temperature points in each group of candidate calibration temperature combinations into the temperature drift model, and calculate the corresponding zero-point output value respectively. T 1, Z 1) ( T 2, Z2), ( T 3, Z 3) and the output value at the highest pressure point ( T 1, H 1) ( T 2, H 2), ( T 3, H 3) Substitute the calculated zero-point output value and the maximum pressure point output value into the zero-point output fitting polynomial and the maximum pressure point output fitting polynomial in the above temperature compensation model, and determine the compensation coefficient of the candidate calibration temperature combination by solving the system of equations, that is, solve for the corresponding... c 0、 c 1. c 2 and d 0、 d 1. d 2.

[0085] 6. Evaluate the full-temperature range compensation accuracy: Calculate the compensated output of the full temperature range (i.e., the rated operating temperature range) using the calculated compensation coefficient through the temperature compensation model, and evaluate the zero-point output accuracy and the maximum pressure point output accuracy based on the residual between the theoretical output and the actual output.

[0086] 7. Select the optimal candidate calibration temperature point combination: Compare the accuracy evaluation results of all candidate calibration temperature combinations, and in combination with actual needs, select the candidate calibration temperature point combination with the best accuracy across the entire temperature range or the most economical calibration cost (such as selecting easily achievable temperature points) as the best calibration temperature point scheme.

[0087] 8. Batch application: Apply the optimal calibration temperature point scheme to all pressure transmitters of the same model.

[0088] It should be noted that the above solution can be further optimized based on actual needs, including: (1) Optimize the temperature drift model: If the transmitter's temperature drift nonlinearity is low, the high-order polynomial (cubic / quartic) can be replaced with a second-order polynomial to establish the temperature drift model, reducing the fitting and computational complexity. If the transmitter's temperature drift nonlinearity is high, and the fitting mathematical model of the high-order polynomial (cubic / quartic) has a large error with the measured data, the high-order polynomial (cubic / quartic) can be replaced with a high-order polynomial (cubic / quartic) divided by temperature range to establish the temperature drift model, increasing the fitting accuracy. Alternatively, lookup tables + linear interpolation, neural networks / machine learning, etc., can be used. The acquisition of the zero-point / full-scale output of the pressure transmitter can be integrated into an automatic testing system to automate data acquisition, fitting, and storage, and automatically establish the pressure transmitter model.

[0089] (2) Optimize the selection method: If the production efficiency requirement is high and the global optimum is not required, the global optimization algorithm such as traversal / combination optimization algorithm can be abandoned. Instead, candidate points can be generated by combining the preset typical temperature points (such as -40℃, -30℃, -20℃, 20℃, 25℃, 70℃, 85℃, 125℃) to reduce the amount of calculation. Alternatively, the appropriate calibration point combination can be automatically iterated and selected by the software according to the requirements.

[0090] (3) Number of calibration temperature points: The method of selecting calibration temperature points can also be applied to transmitters with 2 or more temperature points. Only the calibration algorithm of temperature compensation needs to be modified. If the accuracy requirement is not high, calibration with 2 temperature points can be used. If the accuracy requirement is very high, calibration with more than 3 temperature points can be used.

[0091] (4) Extended range of applicable transmitter types: Applicable to piezoresistive pressure transmitters such as diffused silicon type / ceramic piezoresistive type / sapphire type / sputtered thin film type / strain gauge type, and also applicable to other types of transmitters with nonlinear temperature drift of sensitive elements.

[0092] For example, five uncompensated pressure transmitters with a range of 0MPa to 1MPa and an output of 4mA to 20mA were randomly selected (numbered 1 to 5). The 0MPa output, 1MPa output, and full-scale output were tested at different temperatures. Figure 2 , Figure 3 and Figure 4 It can be seen that the overall output trend is relatively consistent. The output curve of zero-point output is relatively linear at different temperatures, but the output curve of full-scale output at different temperatures shows significant nonlinearity. Figures 2 to 4 Different colored curves are used to represent the outputs of products with different numbers. For example, a red curve represents the output of product number 2, and a green curve represents the output of product number 3.

[0093] In this example, pressure transmitter number 1 is selected as the calibration temperature point, as detailed below: First, obtain the 0MPa output, 1MPa output, and full-scale output of the pressure transmitter at 10℃ intervals, as shown in Table 1.

[0094] Table 1

[0095] Next, based on the 0MPa and 1MPa outputs of the pressure transmitter at 10℃ intervals, a temperature drift model is established (taking cubic polynomial fitting as an example); where, For 0MPa output, i.e., zero-point output, please refer to [link / reference]. Figure 5 The fit is: ; 1MPa output, i.e., the output at the highest pressure point, see reference. Figure 6 The fit is: .

[0096] Based on the temperature drift model described above, the output data of the pressure transmitter every 5°C can be calculated, as shown in Table 2.

[0097] Table 2

[0098] Next, candidate calibration temperature combinations were screened, as shown in Table 3.

[0099] Table 3

[0100] Next, temperature compensation is calculated.

[0101] Based on the temperature compensation model described above, three temperature points from each candidate calibration temperature combination are selected for temperature compensation, and the accuracy of the 0MPa and 1MPa outputs across the entire temperature range is calculated. For example, when selecting the candidate calibration temperature combination "-25℃, 35℃, 110℃" for temperature compensation, the corresponding compensation results are shown in Table 4. Simultaneously, based on the above compensation results, the output values ​​of the candidate calibration temperature combination at each compensated temperature point can be calculated accordingly, as shown in Table 5.

[0102] Table 4

[0103] Table 5

[0104] Next, select the optimal combination of calibration temperature points.

[0105] For the 15 candidate calibration temperature combinations selected above, the compensated 0MPa accuracy is as follows: Figure 7 As shown, and the accuracy of 1 MPa is as follows Figure 8 As shown.

[0106] Based on the temperature compensation results of the different candidate calibration temperature combinations above, if the required accuracy of the pressure transmitter within 0.5%FS is to be within -40℃ to 120℃, the temperature calibration point with the best accuracy according to the above figure is the combination of "-30℃, 35℃, 110℃", with the worst overall temperature accuracy being 0.343%FS; the temperature calibration point with the best cost is the combination of "-25℃, 35℃, 110℃", with the worst overall temperature accuracy being 0.401%FS. If the required accuracy of the pressure transmitter within 0.5%FS is to be within -40℃ to 85℃, the temperature calibration point with the best accuracy according to the above figure is the combination of "-30℃, 20℃, 75℃", with the worst overall temperature accuracy being 0.176%FS; the temperature calibration point with the best cost is the combination of "-10℃, 25℃, 50℃", with the worst overall temperature accuracy being 0.474%FS.

[0107] In summary, the method for selecting calibration temperature points for transmitter temperature compensation provided in the above embodiments achieves scientific, standardized and batch selection of calibration temperature points for pressure transmitter temperature compensation through model simulation, quantitative evaluation and traversal selection of core logic, and has the following technical effects: (1) Accuracy level: By fitting nonlinear temperature drift with high-order polynomials and independently compensating for zero / full-scale temperature drift, combined with scientific selection of calibration points, the residual after compensation in the whole temperature range is effectively reduced, and the zero / full-scale output accuracy and the comprehensive measurement accuracy of the whole temperature range are significantly improved. (2) Production level: Based on batch consistency modeling, only a small number of representative samples need to be tested to establish the temperature drift model of the pressure transmitter, and the cycle of debugging and testing without temperature points is transformed into "modeling-batch application", which greatly reduces the testing workload, improves calibration efficiency, and significantly reduces the calibration cost of batch production. (3) Engineering level: Simulation pre-evaluation of the accuracy effect of different calibration strategies can be carried out in the design / production preparation stage, providing a quantitative decision basis for the balance between accuracy requirements and calibration costs, and realizing customized calibration scheme design; at the same time, it supports remote configuration of compensation parameters, improving the automation and flexibility of industrial applications. (4) Quality level: Through the standardized calibration point selection method, the consistency and stability of the compensation accuracy of the same model of products are guaranteed, solving the problem of product accuracy dispersion caused by traditional experience-based point selection. (5) Adaptability level: It is not only applicable to various pressure transmitters such as piezoresistive MEMS, but also compatible with transmitters using piezoresistive / MEMS pressure cores. It is also applicable to other types of sensitive elements with temperature drift nonlinearity. Moreover, the model and algorithm can be simplified according to the application scenario, adapting to industrial scenarios with different accuracy requirements and production scales, and has strong versatility.

[0108] Based on the same inventive concept as the foregoing embodiments, this embodiment of the invention provides a computing device, such as... Figure 9 As shown, the device includes: a processor 310 and a memory 311 storing a computer program; wherein, Figure 9 The processor 310 shown in the diagram does not indicate that there is only one processor 310, but only indicates the positional relationship of the processor 310 relative to other devices. In practical applications, there can be one or more processors 310; similarly, Figure 9 The memory 311 shown in the diagram has the same meaning, that is, it is only used to indicate the positional relationship of memory 311 relative to other devices. In practical applications, there can be one or more memories 311. When the processor 310 runs the computer program, it implements the calibration temperature point selection method for the transmitter temperature compensation applied to the above-mentioned computing device.

[0109] The device may also include at least one network interface 312. The various components of the device are coupled together via a bus system 313. It is understood that the bus system 313 is used to implement communication between these components. In addition to a data bus, the bus system 313 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 9 The general designated all buses as Bus System 313.

[0110] The memory 311 may be volatile memory or non-volatile memory, or both. Non-volatile memory may be read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, magnetic random access memory, flash memory, magnetic surface memory, optical disk, or read-only optical disk; magnetic surface memory may be disk storage or magnetic tape storage. Volatile memory may be random access memory used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory, synchronous static random access memory, dynamic random access memory, synchronous dynamic random access memory, double data rate synchronous dynamic random access memory, enhanced synchronous dynamic random access memory, synchronous linked dynamic random access memory, and direct memory bus random access memory. The memory 311 described in this embodiment is intended to include, but is not limited to, these and any other suitable types of memory.

[0111] The memory 311 in this embodiment of the invention is used to store various types of data to support the operation of the device. Examples of this data include: any computer programs used to operate on the device, such as operating systems and applications; contact data; phonebook data; messages; pictures; videos, etc. The operating system includes various system programs, such as the framework layer, core library layer, driver layer, etc., used to implement various basic services and handle hardware-based tasks. Applications can include various applications, such as media players, browsers, etc., used to implement various application services. Here, the program implementing the method of this embodiment of the invention can be included in the application.

[0112] Based on the same inventive concept as the foregoing embodiments, this embodiment also provides a readable storage medium storing a computer program, which, when executed by a processor, implements the calibration temperature point selection method for transmitter temperature compensation as described above.

[0113] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. The above description is merely a specific embodiment of the present invention, but 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 protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims

1. A method for selecting calibration temperature points for transmitter temperature compensation, characterized in that, The method includes: Obtain the temperature drift model of the transmitter in the rated operating temperature range under uncompensated conditions. The temperature drift model is used to characterize the change of the zero-point output value and the upper limit reference output value of the transmitter with temperature. Based on the temperature drift model, the virtual zero-point output value and virtual upper limit reference output value corresponding to each temperature point in multiple candidate calibration temperature combinations are determined respectively; each candidate calibration temperature combination contains N temperature points, where N is an integer not less than 2, and the N temperature points are selected from the discretized temperature points within the rated operating temperature range. Based on the virtual zero-point output value and the virtual upper limit reference output value, determine the compensation coefficients corresponding to each group of candidate calibration temperature combinations; Using the compensation coefficient, output virtual compensation calculation is performed on each temperature point after discretization within the rated operating temperature range to obtain the compensated zero-point output value and the compensated upper limit reference output value for each group of candidate calibration temperature combinations with respect to each temperature point. Based on the first deviation between the compensated zero-point output value and the preset zero-point output value, and the second deviation between the compensated upper limit reference output value and the preset upper limit reference output value, the actual calibration temperature point is determined from the multiple sets of candidate calibration temperature combinations.

2. The method according to claim 1, characterized in that, The temperature drift model includes a zero-point output temperature drift sub-model for characterizing the change of the zero-point output value with temperature and an upper limit reference output temperature drift sub-model for characterizing the change of the upper limit reference output value with temperature. The process of obtaining the temperature drift model of the transmitter in its uncompensated state within the rated operating temperature range includes: The zero-point output measured value and the upper limit reference output measured value of the transmitter are obtained at multiple discretized temperature points within the rated operating temperature range. Based on the measured values ​​of the zero-point output and the measured values ​​of the upper limit benchmark output, the zero-point output temperature drift model and the upper limit benchmark output temperature drift model are established by fitting.

3. The method according to claim 1, characterized in that, The generation of the multiple candidate calibration temperature combinations includes at least one of the following methods: The rated operating temperature range is discretized using a set temperature step size. From the multiple discretized temperature points obtained, a traversal or combination optimization strategy is used to filter all combinations of N temperature points that meet the distribution requirements of the first, second, and third temperature points, generating the multiple sets of candidate calibration temperature combinations. The rated operating temperature range is divided into a first temperature range, a second temperature range, and a third temperature range in order of temperature value from low to high or from high to low. The first temperature point is selected from the first temperature range, the second temperature point is selected from the second temperature range, and the third temperature point is selected from the third temperature range. N temperature points are selected from a preset set of temperature points and combined to generate the multiple sets of candidate calibration temperature combinations.

4. The method according to any one of claims 1 to 3, characterized in that, The compensation coefficients include a zero-point compensation coefficient and an upper limit reference compensation coefficient; determining the compensation coefficients corresponding to each group of candidate calibration temperature combinations based on the virtual zero-point output value and the virtual upper limit reference output value includes: Based on the virtual zero-point output value and the virtual upper limit benchmark output value, fitting functions corresponding to each group of candidate calibration temperature combinations are constructed by interpolation or fitting, and the coefficients of the fitting functions are determined as the compensation coefficients; the fitting functions include the zero-point fitting function and the upper limit benchmark fitting function.

5. The method according to claim 4, characterized in that, The step of using the compensation coefficient to perform output virtual compensation calculations on each discretized temperature point within the rated operating temperature range, to obtain the compensated zero-point output value and the compensated upper limit reference output value for each group of candidate calibration temperature combinations with respect to each temperature point, includes: For any discretized temperature point within the rated operating temperature range, based on the compensation coefficient, the zero-point output value of the zero-point fitting function and the upper limit benchmark output value of the upper limit benchmark fitting function at the temperature point are obtained, as well as the target virtual output value of the temperature drift model at the temperature point; the target virtual output value includes the target virtual zero-point output value and the target virtual upper limit benchmark output value. Based on the fitted zero-point output value, the fitted upper limit benchmark output value, the target virtual output value, and the preset zero-point output value and preset upper limit benchmark output value, determine the compensation correction amount corresponding to the temperature point; The compensation correction amount is superimposed on the preset zero-point output value to obtain the compensated output value at the temperature point; the compensated output value includes the compensated zero-point output value and the compensated upper limit reference output value.

6. The method according to claim 5, characterized in that, The step of determining the compensation correction amount corresponding to the temperature point based on the fitted zero-point output value, the fitted upper limit benchmark output value, the target virtual output value, and the preset zero-point output value and preset upper limit benchmark output value includes: Obtain the offset of the target virtual output value relative to the fitted zero-point output value; The offset is scaled proportionally according to the ratio of the target range to the virtual range, and the scaled offset is determined as the compensation correction amount; the target range is the difference between the preset upper limit reference output value and the preset zero point output value, and the virtual range is the difference between the fitted upper limit reference output value and the fitted zero point output value.

7. The method according to claim 1, characterized in that, The step of determining the actual calibration temperature point from the multiple sets of candidate calibration temperature combinations includes: Determine the maximum first deviation and the maximum second deviation of the target candidate calibration temperature combination within the rated operating temperature range; the target candidate calibration temperature combination is any of the aforementioned candidate calibration temperature combinations. The larger of the maximum first deviation and the maximum second deviation is determined as the comprehensive deviation of the target candidate calibration temperature combination; Based on the overall deviation, the actual calibration temperature point is determined from the multiple candidate calibration temperature combinations.

8. The method according to claim 7, characterized in that, The step of determining the actual calibration temperature point from the multiple candidate calibration temperature combinations based on the comprehensive deviation includes at least one of the following: The candidate calibration temperature combination with the smallest overall deviation is determined as the actual calibration temperature point; The actual calibration temperature point is determined from the candidate calibration temperature combinations whose overall deviation is less than or equal to a preset deviation threshold, according to a preset cost optimization strategy.

9. A computing device, characterized in that, include: The device includes a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, implements the method for selecting calibration temperature points for transmitter temperature compensation as described in any one of claims 1 to 8.

10. A readable storage medium, characterized in that, The device contains a computer program that, when executed by a processor, implements the method for selecting calibration temperature points for transmitter temperature compensation as described in any one of claims 1 to 8.

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