Thin film thermocouple calibration precision improving method based on linear regression algorithm

Abstract

A method for improving calibration precision of a thin film thermocouple based on a linear regression algorithm belongs to the field of thin film thermocouples, and comprises the following steps: building a thin film thermocouple calibration system; starting to calibrate the thin film thermocouple by using the built thin film thermocouple calibration system; calculating a thermoelectric characteristic curve by using a linear regression algorithm; and obtaining a thermoelectric characteristic indexing table of the thin film thermocouple by utilizing linear interpolation. The film thermocouple calibration precision improving method based on the linear regression algorithm can effectively improve the calibration precision of the film thermocouple, can obtain a high-precision thermoelectric characteristic curve for the condition that the temperature of the output end of the film thermocouple cannot be accurately controlled, has the advantages of being simple, convenient and rapid in calculation, and is suitable for popularization and application. And meanwhile, the method has high universality and is suitable for dynamic / static calibration of thin film thermocouples of various sizes and various materials.

Description

Technical Field

[0001] The invention belongs to the technical field of thin film thermocouples, and in particular relates to a method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm. Background Art

[0002] Thin film thermocouples are small in size (thickness is about 1 μm) and have little interference with the measured temperature field, so they are used in fields such as turbine blade temperature measurement. The Seebeck effect is the basic working principle of thin film thermocouples. When a temperature difference occurs at both ends of the thin film thermocouple (the two ends generally refer to the hot node and the voltage output end), a voltage will be generated at the output end of the thin film thermocouple. The output voltage is related to the temperature at both ends of the thin film thermocouple, that is, V = f(T 热节点 , T 输出端 ). According to literature reports, the thermoelectric properties of thin film thermocouples are generally not consistent (there may be large differences in the same batch), so each thin film thermocouple needs to be calibrated before use.

[0003] The calibration process of thin-film thermocouples requires strict control of the temperature of the output end of the thin-film thermocouple to 0°C before the thermoelectric characteristics can be obtained. However, for small-sized thin-film thermocouples made on the surface of a hard substrate (such as ceramics), the output temperature cannot be accurately controlled at 0°C. This is because thin-film thermocouples are usually small in size (~10cm). When the calibration temperature is high (>1000°C), the heat near the hot node will be quickly transferred to the output end. According to the literature survey, the most commonly used traditional approach is to directly ignore the fluctuation of the temperature at the output end of the sensor, which will obviously lead to large errors in the obtained thermoelectric characteristics. At present, the calibration method of thin-film thermocouples cannot obtain thermoelectric characteristic curves with high accuracy. Summary of the invention

[0004] In order to solve the problem existing in the prior art, namely, obtaining a thermoelectric characteristic curve with higher accuracy, the present invention provides a method for improving the calibration accuracy of a thin film thermocouple based on a linear regression algorithm.

[0005] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0006] The present invention provides a method for improving the calibration accuracy of thin-film thermocouples based on a linear regression algorithm, comprising the following steps:

[0007] Step S1: Building a thin film thermocouple calibration system;

[0008] Step S2: using the constructed thin film thermocouple calibration system to start calibrating the thin film thermocouple;

[0009] Step S3: Calculate the thermoelectric characteristic curve using a linear regression algorithm;

[0010] Step S4: using linear interpolation to obtain a thermoelectric characteristic table of the thin film thermocouple.

[0011] Furthermore, the thin film thermocouple calibration system includes: a sintering furnace, a cooling device, leads, a voltage collection device, a thin film thermocouple, a substrate and a temperature sensor; the thin film thermocouple is integrated on the surface of the substrate; the sintering furnace is installed on one side of the thin film thermocouple; the cooling device is installed at the output end of the thin film thermocouple; the output end of the thin film thermocouple is connected to the voltage collection device through leads; and a temperature sensor is respectively installed at the hot node and the output end of the thin film thermocouple.

[0012] Furthermore, the voltage collection device adopts a voltmeter.

[0013] Furthermore, the temperature sensor adopts a K-type thermocouple.

[0014] Furthermore, during the calibration process, the sintering furnace temperature is raised to the calibration temperature, and the following data are recorded: hot node temperature T h , output temperature T l , the thin film thermocouple outputs V; continue to increase the sintering furnace temperature to the next calibration temperature and record the data until the corresponding data of the set calibration temperature point have been collected; turn off the sintering furnace, cool down naturally, and the calibration is completed.

[0015] Furthermore, the heating rate of the sintering furnace is 10-20°C / min, and the temperature is kept at a constant temperature for 30-60 minutes after reaching the designated temperature.

[0016] Furthermore, when the output temperature of the thin film thermocouple is fixed at 0°C, the polynomial Represents its thermoelectric characteristic curve. When the output of the thin film thermocouple is not fixed, the actual output of the thin film thermocouple is The coefficients A, B, and C of the thermoelectric characteristic polynomial are calculated using a linear regression algorithm, where T h represents the hot node temperature, T l represents the output end temperature, and V represents the output voltage of the thin film thermocouple.

[0017] Furthermore, the specific implementation process of step S3 is as follows:

[0018] Step S3.1: record the coefficients A, B, C of the thermoelectric characteristic polynomial as k(1,3)=[A, B, C]; record the data as y(1,n)=[V1,…,V n ], so y = kx;

[0019] Step S3.2: Use multiple linear regression to estimate the value of k Using the least squares method as the optimization objective, we have an estimated value Solve for coefficients A, B, and C;

[0020] Step S3.3: Substitute the coefficients A, B, and C of the thermoelectric characteristic polynomial into Obtain the thermoelectric characteristic curve.

[0021] Furthermore, the coefficients A, B, and C of the thermoelectric characteristic polynomial are substituted into Then, the polynomial is combined and the VT is recorded by linear interpolation. h The corresponding relationship between them is the corresponding relationship between the output of the thin film thermocouple and the output end temperature, forming a graduation table of the thermoelectric characteristics of the thin film thermocouple.

[0022] Furthermore, the specific implementation process of step S4 is as follows:

[0023] Step S4.1: Setting the temperature vector to be interpolated;

[0024] Step S4.2: Use the linear interpolation function interp1 in Matlab to interpolate with T as the interpolation point to obtain the corresponding voltage vector; combine the temperature vector and the voltage vector to form a thermoelectric characteristic graduation table of the thin film thermocouple.

[0025] The beneficial effects of the present invention are:

[0026] 1. The thin-film thermocouple calibration accuracy improvement method based on linear regression algorithm provided by the present invention can effectively improve the accuracy of its thermoelectric characteristic curve. In fact, the method of the present invention can obtain the thermoelectric characteristic curve of a true thin-film thermocouple (made on a hard substrate), which is the biggest difference from the traditional method. In the traditional thin-film thermocouple calibration scheme, the output temperature is assumed to be unchanged, and the δT-V data is directly used as the thermoelectric characteristic curve (δT = T h -T l ), which is strictly speaking not in compliance with regulations.

[0027] 2. The present invention provides a method for improving the calibration accuracy of thin-film thermocouples based on a linear regression algorithm, which has the advantages of simple and fast calculation. On the basis of calibration, only three sets of data (hot node temperature T h , output temperature T l , thin film thermocouple output V), the thermoelectric characteristic curve of the thin film thermocouple can be quickly obtained by using the pre-programmed program.

[0028] 3. The thin film thermocouple calibration accuracy improvement method based on linear regression algorithm provided by the present invention has high versatility and is suitable for dynamic / static calibration of thin film thermocouples of various sizes and materials made on the surface of a hard substrate. When the output temperature cannot be accurately controlled, the method of the present invention can obtain a thermoelectric characteristic curve with high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 Schematic diagram of thin film thermocouple calibration system.

[0030] Figure 2 The thermoelectric characteristic curve of the thin film thermocouple obtained by using the method for improving the calibration accuracy of the thin film thermocouple based on the linear regression algorithm provided by the present invention is compared with the thermoelectric characteristic curve of the thin film thermocouple obtained by the most commonly used traditional method. In the figure, a: the thermoelectric characteristic curve of the thin film thermocouple obtained by the most commonly used traditional method; b: the thermoelectric characteristic curve of the thin film thermocouple obtained by using the method for improving the calibration accuracy of the thin film thermocouple based on the linear regression algorithm provided by the present invention.

[0031] Figure 3 The present invention provides a method for improving the calibration accuracy of thin-film thermocouples based on a linear regression algorithm, and the results of the thermoelectric characteristic curve inversion of thin-film thermocouples are compared with the results of the thermoelectric characteristic curve inversion of thin-film thermocouples obtained by the most commonly used traditional method.

[0032] In the figure, sintering furnace 1, cooling device 2, lead wire 3, voltage collection device 4, thin film thermocouple 5,

[0033] Substrate 6, temperature sensor 7, hot node 8. DETAILED DESCRIPTION

[0034] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0035] The present invention provides a method for improving the calibration accuracy of thin-film thermocouples based on a linear regression algorithm, and the specific implementation steps are as follows:

[0036] Step S1: First, build a thin film thermocouple calibration system;

[0037] like Figure 1As shown, the thin film thermocouple calibration system constructed by the present invention mainly includes: a sintering furnace 1, a cooling device 2, a lead 3, a voltage collection device 4, a thin film thermocouple 5, a substrate 6 and a temperature sensor 7.

[0038] The specific implementation process is as follows:

[0039] Step S1.1: fabricating a thin film thermocouple 5 on the surface of a substrate 6 .

[0040] In the present invention, the material of the thin film thermocouple 5 can be ITO-In2O3. In actual operation, the specific material of the thin film thermocouple 5 is not limited.

[0041] In the present invention, the size of the thin film thermocouple 5 can be 150 mm*40 mm*1 mm. In actual operation, the specific size of the thin film thermocouple 5 is not limited.

[0042] In the present invention, the specific material of the substrate 6 can be ceramic material, and the specific material of the substrate 6 is not limited in actual operation.

[0043] Step S1.2: Use conductive glue to stick the lead wire 3 onto the output pin of the thin film thermocouple 5 , and then connect the output end of the thin film thermocouple 5 to the voltage collection device 4 through the lead wire 3 .

[0044] In the present invention, the voltage acquisition device 4 may specifically be a voltmeter, but is not limited thereto.

[0045] Step S1.3: A temperature sensor 7 is respectively fixed near the hot node 8 (measuring point) and the output end of the thin film thermocouple 5;

[0046] In the present invention, the temperature sensor 7 may be a K-type thermocouple, but is not limited thereto.

[0047] Step S1.4: A cooling device 2 is fixed near the output end of the thin film thermocouple 5 to keep the output end temperature of the thin film thermocouple 5 near room temperature. In laboratory conditions, the cooling device 2 is generally attached to the output end of the thin film thermocouple 5 .

[0048] Step S1.5: A sintering furnace 1 is fixed near the left side of the thin film thermocouple 5 to increase the temperature of the hot node 8 of the thin film thermocouple 5 .

[0049] Step S2: thin film thermocouple calibration;

[0050] Using the established thin film thermocouple calibration system, start the dynamic calibration process and the static calibration process. During the calibration process, the sintering furnace 1 needs to be turned on to increase the temperature at the hot node 8. At the same time, the cooling device 2 is turned on to reduce the output end temperature of the thin film thermocouple 5. During the calibration process, n groups of data are measured / recorded, which are: hot node temperature T h, output temperature T l , thin film thermocouple output V.

[0051] The specific implementation process is as follows:

[0052] Step S2.1: Raise the temperature of the sintering furnace 1 to the calibration temperature, wherein the heating rate is preferably 10-20°C / min, and keep the temperature for 30-60min after reaching the calibration temperature. At the same time, record the following data: hot node temperature T h , output temperature T l , the thin film thermocouple outputs V, wherein the data acquisition frequency is preferably 0.1-1 group / s;

[0053] Step S2.2: Continue to increase the temperature of the sintering furnace 1 to the next calibration temperature, and repeat step S2.1 until the data corresponding to the set calibration temperature point have been collected;

[0054] Step S2.3: Turn off the sintering furnace 1, cool it down naturally, and the calibration is completed.

[0055] Step S3: Calculate the thermoelectric characteristic curve using a linear regression algorithm;

[0056] The thermoelectric characteristic curve of the thin film thermocouple 5 is calculated using a linear regression algorithm. When the output end temperature of the thin film thermocouple 5 is fixed at 0°C, the thermoelectric characteristic curve can be expressed by a polynomial It means that when the output of the thin film thermocouple 5 is not fixed, the actual output of the thin film thermocouple 5 is A linear regression algorithm is needed to calculate the coefficients A, B, and C of the thermoelectric characteristic polynomial.

[0057] The specific implementation process is as follows:

[0058] Step S3.1: record the coefficients A, B, C of the thermoelectric characteristic polynomial as k(1,3)=[A, B, C]; record the data as y(1,n)=[V1,…,V n ]. So we have y = kx;

[0059] Step S3.2: Use multiple linear regression to estimate the value of k Using the least squares method as the optimization objective, we have an estimated value Solve for coefficients A, B, and C;

[0060] Step S3.3: Substitute the coefficients A, B, and C of the thermoelectric characteristic polynomial into Obtain the thermoelectric characteristic curve.

[0061] Step S4: using linear interpolation to obtain a thermoelectric characteristic graduation table of the thin film thermocouple 5;

[0062] Substitute the coefficients A, B, and C of the thermoelectric characteristic polynomial into After that, the VT can be recorded by linear interpolation in combination with the thermoelectric characteristic polynomial. h The corresponding relationship between them, that is, the corresponding relationship between the output of the thin film thermocouple 5 and the output end temperature, forms a thermoelectric characteristic graduation table of the thin film thermocouple 5.

[0063] The specific implementation process is as follows:

[0064] Step S4.1: Set the temperature vector to be interpolated, such as T = [0, 1, 2, 3....., 1000]. It can be set arbitrarily within the temperature range, but according to the usual requirements of the thermoelectric characteristic graduation table, it is generally an arithmetic progression.

[0065] Step S4.2: Use the linear interpolation function interp1 in Matlab to interpolate with T as the interpolation point to obtain the corresponding voltage vector; combine the temperature vector and the voltage vector to form a thermoelectric characteristic graduation table of the thin film thermocouple 5, see Table 1.

[0066] Table 1 Thin film thermocouple graduation table obtained using the method of the present invention

[0067]

[0068]

[0069] The core innovation of the thin film thermocouple calibration accuracy improvement method based on linear regression algorithm of the present invention is to first use the established thin film thermocouple calibration system to obtain the output of the thin film thermocouple and the temperature at both ends and other data. Then, the linear regression algorithm is used to calculate the thermoelectric characteristic curve of the thin film thermocouple (mainly calculating the coefficients of the polynomial).

[0070] The comparison results of the thermoelectric characteristic curve of the thin film thermocouple 5 obtained by the method for improving the calibration accuracy of the thin film thermocouple based on the linear regression algorithm provided by the present invention and the thermoelectric characteristic curve of the thin film thermocouple 5 obtained by the most commonly used traditional method are as follows: Figure 2 The most commonly used traditional approach is to directly use V = A*

[0071] (T h -T l ) 3 +B*(T h -T l ) 2 +C*(T h -T l ) acts as the thermoelectric characteristic curve.

[0072] like Figure 3 As shown, the error of the thermoelectric characteristic curve of the thin film thermocouple obtained by the method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm provided by the present invention is compared with the thermoelectric characteristic curve of the thin film thermocouple obtained by the most commonly used traditional method. The thermoelectric characteristic curve of the thin film thermocouple obtained by the method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm provided by the present invention is completely consistent with the output of the thin film thermocouple 5, the consistency is good, and the accuracy is high, while the thermoelectric characteristic curve (δT-V curve) of the thin film thermocouple obtained by the most commonly used traditional method cannot be consistent with the output of the thin film thermocouple 5, and the accuracy is poor. The comparison results show that the method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm provided by the present invention can effectively obtain a high-precision thermoelectric characteristic curve.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein, but these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm, characterized in that: The following steps are involved: Step S1: Building a thin film thermocouple calibration system; Step S2: using the constructed thin film thermocouple calibration system to start calibrating the thin film thermocouple; Step S3: Calculate the thermoelectric characteristic curve using a linear regression algorithm; Step S4: using linear interpolation to obtain a thermoelectric characteristic table of the thin film thermocouple.

2. The method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm according to claim 1, characterized in that: The thin film thermocouple calibration system includes: a sintering furnace, a cooling device, leads, a voltage collection device, a thin film thermocouple, a substrate and a temperature sensor; the thin film thermocouple is integrated on the surface of the substrate; the sintering furnace is installed on one side of the thin film thermocouple; the cooling device is installed at the output end of the thin film thermocouple; the output end of the thin film thermocouple is connected to the voltage collection device through leads; a temperature sensor is installed at the hot node and the output end of the thin film thermocouple respectively.

3. The method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm according to claim 2, characterized in that: The voltage collection device adopts a voltmeter.

4. The method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm according to claim 2, characterized in that: The temperature sensor adopts K-type thermocouple.

5. The method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm according to claim 1, characterized in that: During the calibration process, the sintering furnace temperature is raised to the calibration temperature, and the following data are recorded: hot node temperature T h , output temperature T l , thin film thermocouple output V; Continue to increase the sintering furnace temperature to the next calibration temperature and record the data until the corresponding data of the set calibration temperature point have been collected; turn off the sintering furnace, cool it down naturally, and the calibration is completed.

6. The method for improving the calibration accuracy of thin-film thermocouples based on a linear regression algorithm according to claim 5, characterized in that: The heating rate of the sintering furnace is 10-20°C / min, and the temperature is kept for 30-60 minutes after reaching the designated temperature.

7. The method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm according to claim 1, characterized in that: Furthermore, when the output temperature of the thin film thermocouple is fixed at 0°C, the polynomial Represents its thermoelectric characteristic curve. When the output of the thin film thermocouple is not fixed, the actual output of the thin film thermocouple is The coefficients A, B, and C of the thermoelectric characteristic polynomial are calculated using a linear regression algorithm, where T h represents the hot node temperature, T l represents the output end temperature, and V represents the output voltage of the thin film thermocouple.

8. The method for improving the calibration accuracy of thin-film thermocouples based on a linear regression algorithm according to claim 7, characterized in that: The specific implementation process of step S3 is as follows: Step S3.1: record the coefficients A, B, C of the thermoelectric characteristic polynomial as k(1,3)=[A, B, C]; record the data as y(1,n)=[V1,…,V n ], so y = kx; Step S3.2: Use multiple linear regression to find the estimated value of k Using the least squares method as the optimization objective, we have an estimated value Solve for coefficients A, B, and C; Step S3.3: Substitute the coefficients A, B, and C of the thermoelectric characteristic polynomial into Obtain the thermoelectric characteristic curve.

9. The method for improving the calibration accuracy of thin-film thermocouples based on a linear regression algorithm according to claim 8, characterized in that: Substitute the coefficients A, B, and C of the thermoelectric characteristic polynomial into Then, the polynomial is combined and the VT is recorded by linear interpolation. h The corresponding relationship between them is the corresponding relationship between the output of the thin film thermocouple and the output end temperature, forming a graduation table of the thermoelectric characteristics of the thin film thermocouple.

10. The method for improving the calibration accuracy of thin film thermocouples based on a linear regression algorithm according to claim 9, characterized in that: The specific implementation process of step S4 is as follows: Step S4.1: Setting the temperature vector to be interpolated; Step S4.2: Use the linear interpolation function interp1 in Matlab to interpolate with T as the interpolation point to obtain the corresponding voltage vector; combine the temperature vector and the voltage vector to form a thermoelectric characteristic graduation table of the thin film thermocouple.

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