Temperature measurement calibration method and system of infrared temperature measurement thermal imager, medium and product

Abstract

The invention discloses a temperature measurement calibration method and system for an infrared temperature measurement thermal imager, a medium and a product, and the method comprises the steps: uniformly selecting a plurality of temperature points in a temperature measurement range, and building a first mapping relation between a response value and a temperature measurement value of the infrared temperature measurement thermal imager through a least square method; based on the acquired environment temperature, establishing a first correlation function of the shutter response value and the environment temperature; based on the environment temperature, establishing a second correlation function of the blackbody response value of the middle reference temperature and the environment temperature; on the basis of a preset three-item calibration model, the first correlation function and the second correlation function are combined, and the response value of the temperature measurement thermal imager is calibrated; based on the calibrated response value of the temperature measurement thermal imager and the first mapping relation, temperature data after pixel difference calibration, temperature drift calibration and additional radiation calibration are calculated; according to the invention, the temperature measurement precision of the infrared temperature measurement thermal imager is improved, the calibration process is simplified, the implementation difficulty is reduced, and the calibration cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of infrared temperature measurement data processing, in particular to an infrared temperature measurement thermal imager temperature measurement calibration method, system, medium and product. BACKGROUND

[0002] Infrared thermal imagers are increasingly widely used in temperature measurement. Infrared temperature measurement thermal imagers not only can thermal imaging, but also can obtain the temperature field distribution of the observed scene because all the pixels of the sensor can obtain temperature data. Therefore, infrared temperature measurement thermal imagers have been widely used in the field of temperature measurement in recent years, especially in non-contact and real-time regional monitoring scenarios, infrared temperature measurement thermal imagers more embody the advantages compared with traditional temperature measurement equipment.

[0003] In order to achieve accurate temperature measurement, the infrared temperature measurement thermal imager needs to be calibrated (calibrated) in the following three aspects. The first aspect is to calibrate the difference between each pixel. The response of each pixel to temperature is inconsistent, and the difference between each pixel needs to be calibrated. The second aspect is to calibrate the temperature drift. The infrared thermal imager is not only sensitive to the target temperature, but also sensitive to the environment temperature. Different environment temperatures cause the output data of the infrared temperature measurement thermal imager to deviate, which can be simply referred to as "temperature drift". In order to accurately measure the temperature, the temperature drift caused by the change of the environment temperature needs to be calibrated. The third aspect is to calibrate the additional radiation (such as interference radiation).

[0004] The existing mainstream temperature drift calibration method is to sample the actual response data (temperature drift data) under different environment temperatures and find the functional relationship between the data and the calibration data. The relationship between the two is approximately linear. Through a linear function, the temperature drift data of a certain environment temperature can be calibrated. In order to obtain better temperature measurement accuracy, fine temperature drift data needs to be collected. The more data collected, the higher the temperature measurement accuracy. For example, collecting every 5 degrees Celsius is more accurate than collecting every 10 degrees Celsius. At the same time, due to the difference in response characteristics and temperature drift characteristics of each device, comprehensive calibration needs to be performed on each pixel of each device. This calibration algorithm not only has a complex calibration process, but also involves a large amount of data storage, so there is room for improvement. SUMMARY

[0005] In order to solve the defects of the prior art, provide a temperature measurement calibration method that can improve the temperature measurement accuracy of the infrared temperature measurement thermal imager, simplify the calibration process, reduce the implementation difficulty, and reduce the calibration cost of the infrared temperature measurement thermal imager, the present application provides an infrared temperature measurement thermal imager temperature measurement calibration method, system, medium and product.

[0006] In the first aspect, the application aims to achieve the following technical solutions: An infrared temperature measurement thermal imager temperature measurement calibration method, comprising: Multiple temperature points are uniformly selected within the temperature measurement range, and the first mapping relationship between the infrared thermal imager response value and the temperature measurement value is established by the least squares method. Based on the acquired ambient temperature, a first correlation function between the shutter response value and the ambient temperature is established; based on the ambient temperature, a second correlation function between the blackbody response value at an intermediate reference temperature and the ambient temperature is established. Based on three preset calibration models, the response value of the temperature measuring thermal imager is calibrated by combining the first correlation function and the second correlation function; Based on the calibrated thermal imager response value and the first mapping relationship, the temperature data after pixel difference calibration, temperature drift calibration and additional radiation calibration are calculated.

[0007] By adopting the above technical solution, the first mapping relationship is established between the response value of the infrared thermal imager and the temperature. This is achieved through shutter calibration, specifically through one of the three calibration formulas. This method can eliminate the differences between pixels of the detector. Additional radiation is eliminated through a first correlation function, and temperature drift is eliminated through a second correlation function. The response values ​​involved in the first mapping function, the first correlation function, and the second correlation function are the average of the response values ​​of the middle 64 pixels of a given infrared thermal imager. All infrared thermal imagers under the same product can share the above three functions, eliminating the need for separate calibration for each imager. Therefore, it greatly reduces the calibration complexity and data volume of infrared temperature measurement thermal imagers. Thus, this application provides a temperature calibration method that improves the temperature measurement accuracy of infrared temperature measurement thermal imagers, simplifies the calibration process, reduces implementation difficulty, and lowers the calibration cost.

[0008] In a preferred embodiment of this application: the step of uniformly selecting multiple temperature points within the temperature measurement range and establishing a first mapping relationship between the infrared thermal imager response value and the temperature measurement value using the least squares method includes: Select 8×8 pixels in the central area of ​​the infrared thermal imager and obtain the average value of the response values ​​of 64 pixels to determine the response value of the infrared thermal imager. Within the temperature measurement range of the infrared thermal imager, N temperatures are evenly spaced. The average response of 64 pixels to each of the N blackbody temperatures is measured, and the response value of the blackbody at the intermediate temperature is recorded. Using the infrared thermal imager response value D as the independent variable and the temperature measurement value T as the dependent variable, a polynomial function is fitted using the least squares method: in, This is a temperature measurement value. This is the corrected response value of the infrared thermal imager. This is a temperature mapping function.

[0009] By adopting the technical scheme, the 8*8 pixel array mean value method is adopted to effectively suppress the discrete noise between the detector pixels of the infrared temperature measurement thermal imager, further reduce the spatial response consistency error, and improve the spatial response uniformity. This is beneficial to improve the reliability of the calibration data.

[0010] In a preferred example of the present application, the first correlation function of the shutter response value and the environment temperature is established based on the obtained environment temperature, including: obtaining the shutter response value of the temperature measurement thermal imager under different environment temperatures to obtain the shutter response value of the temperature measurement thermal imager under different environment temperatures ; taking the environment temperature as the independent variable and the shutter response value as the dependent variable, fitting a polynomial function by the least square method: wherein, the environment temperature, the shutter response value of the temperature measurement thermal imager under different environment temperatures, the first correlation function of the shutter response value and the environment temperature.

[0011] By adopting the technical scheme, the first correlation function is also called the shutter response function, which records the information of the additional radiation under different environment temperatures, and the detector response deviation caused by the additional radiation can be calibrated through the three calibration models.

[0012] In a preferred example of the present application, the second correlation function of the blackbody response value of the intermediate reference temperature and the environment temperature is established based on the environment temperature, specifically including: obtaining the response value of the temperature measurement thermal imager to the intermediate reference temperature blackbody under different environment temperatures to obtain the blackbody response value of the intermediate reference temperature, and the intermediate reference temperature is the middle value of the temperature measurement range; taking the environment temperature as the independent variable and the blackbody response value of the intermediate reference temperature as the dependent variable, fitting a polynomial function by the least square method: wherein, the environment temperature, the blackbody response value of the temperature measurement thermal imager to the intermediate reference temperature under different environment temperatures, the second correlation function of the blackbody response value of the intermediate reference temperature and the environment temperature.

[0013] By adopting the above technical solution, the second correlation function is also called an intermediate reference temperature response function. The function records the temperature drift information at different ambient temperatures with the center temperature of the temperature measurement range as the reference, and the response deviation of the detector caused by the temperature drift can be calibrated through the three-item calibration model.

[0014] In a preferred example of the present application, the response value of the temperature measurement thermal imager is calibrated based on the preset three-item calibration model, combined with the first correlation function and the second correlation function, including: The preset three-item calibration model adopts the following formula: wherein D is the actual response value of each pixel of the temperature measurement thermal imager, is the response value of each pixel of the temperature measurement thermal imager to the shutter, is the response value of the temperature measurement thermal imager to the shutter at different ambient temperatures, is the blackbody response value of the temperature measurement thermal imager to the intermediate reference temperature at different ambient temperatures, and is fitted from the average value of 64 pixel responses, is the response value of the infrared temperature measurement thermal imager after pixel difference calibration, temperature drift calibration and additional radiation correction.

[0015] By adopting the above technical solution, when the actual temperature measurement calibration is performed, the temperature measurement range can be set as [0℃, 120℃] and the intermediate reference temperature is 60℃. The joint correction of the pixel difference, the temperature drift effect and the additional radiation interference is realized, the comprehensive error is reduced compared with the single calibration mode, the dynamic reference value correction mechanism is established by taking the median temperature (60℃) of the temperature measurement range as the reference point and using the three-item calibration model, so that the temperature measurement error of the intermediate temperature is controlled within ±0.5℃.

[0016] In a preferred example of the present application, the method further includes: In the low-temperature environment, the first low-temperature blackbody actual measurement deviation value and the first high-temperature blackbody actual measurement deviation value are obtained by comparing the standard temperature value; in the high-temperature environment, the second low-temperature blackbody actual measurement deviation value and the second high-temperature blackbody actual measurement deviation value are obtained by comparing the standard temperature value; Based on the temperature difference between the high-temperature environment and the low-temperature environment, the low-temperature deviation value and the high-temperature deviation value at the current ambient temperature are calculated through a linear interpolation formula; The four-point calibration calculation formula is adopted to perform temperature measurement compensation based on the calibrated temperature data to obtain the final calibrated temperature.

[0017] By adopting the technical scheme, on the basis of the three calibrations, a four-point calibration mechanism is introduced, the measured deviation values of the low-temperature black body (such as 20 DEG C) and the high-temperature black body (such as 100 DEG C) are measured in the low-temperature environment (such as 10 DEG C) and the high-temperature environment (such as 50 DEG C) respectively, and linear interpolation is carried out based on the environmental temperature, so that the systematic error of the edge region of the temperature measurement interval is dynamically compensated. The problem that the precision of the medium-temperature region is high and the precision of the high-temperature and low-temperature ends is low after the three calibrations is effectively solved, and a global error correction model is constructed by using limited four-point deviation data. The innovation lies in that the complex nonlinear error in the whole temperature range is simplified as linear interpolation compensation of the end-point deviation, the amount of data required for high-precision calibration is greatly reduced, the uniform precision distribution in the whole temperature measurement range is ensured, and the measurement reliability and consistency of the infrared thermal imager in the wide temperature range application scene are significantly improved.

[0018] In a preferred example of the present application: the method comprises: The low-temperature deviation value and the high-temperature deviation value at the current environmental temperature are calculated by a linear interpolation formula based on the temperature difference between the high-temperature environment and the low-temperature environment, comprising: The calculation formula of the low-temperature deviation value is: Wherein, is a first low-temperature black body measured deviation value, , is a measured value of the 20 DEG C black body in the low-temperature environment; is a second low-temperature black body measured deviation value, , is a measured value of the 20 DEG C black body in the high-temperature environment; is a high-temperature environmental temperature, is a low-temperature environmental temperature; is a current environmental temperature; The calculation formula of the high-temperature deviation value is: Wherein, is a first high-temperature black body measured deviation value, , is a measured value of the 100 DEG C black body in the low-temperature environment; is a second high-temperature black body measured deviation value, , is a measured value of the 100 DEG C black body in the high-temperature environment; The four-point calibration calculation formula is used to carry out measurement temperature compensation based on the calibrated temperature data to obtain the final calibration temperature, and the calculation formula is as follows: Wherein, is a measurement temperature after three compensations based on a preset three-calibration model, is a measurement temperature after four compensations.

[0019] By adopting the technical solutions, explicit calculation formulas of low-temperature deviation value, high-temperature deviation value and final temperature compensation are given, the accuracy and implementability of the four-point calibration algorithm are realized, the compensation process has clear mathematical basis and engineering operability, and the uncertainty caused by empirical adjustment is avoided. The full-range temperature measurement accuracy is improved at a very low data cost (only four frames of deviation data are required).

[0020] In a second aspect, the application aims to achieve the following technical solutions: An infrared temperature measurement thermal imager temperature calibration system for performing the infrared temperature measurement thermal imager temperature calibration method described above, the system comprising: A temperature point selection module for uniformly selecting a plurality of temperature points in a temperature measurement range and establishing a first mapping relationship between the response value of the infrared temperature measurement thermal imager and the temperature measurement value by the least square method; An environment correlation modeling module for establishing a first correlation function between the shutter response value and the environment temperature based on the obtained environment temperature, and establishing a second correlation function between the blackbody response value of the intermediate reference temperature and the environment temperature; A response calibration module for calibrating the temperature measurement thermal imager response value based on the first correlation function and the second correlation function according to the preset three-item calibration model; A temperature calculation module for calculating the temperature data after pixel difference calibration, temperature drift calibration and additional radiation calibration based on the calibrated temperature measurement thermal imager response value and the first mapping relationship.

[0021] In a third aspect, the application aims to achieve the following technical solutions: A computer readable storage medium storing a computer program, the computer program being executed by a processor to implement the steps of the above-mentioned infrared temperature measurement thermal imager temperature calibration method.

[0022] In a fourth aspect, the application aims to achieve the following technical solutions: A computer program product comprising a computer program / instruction, the computer program / instruction being executed by a processor to implement the steps of the above-mentioned infrared temperature measurement thermal imager temperature calibration method.

[0023] In summary, the present application has at least one of the following beneficial technical effects: 1. Through the three-dimensional calibration framework of "pixel difference calibration, temperature drift calibration and additional radiation calibration", the inherent errors of the infrared thermal imager in spatial response consistency, environmental adaptability and radiation interference are systematically eliminated, and full-link error compensation is realized. 2. On the basis of the above three calibrations, a four-point calibration mechanism is introduced, by measuring the measured deviation values of low-temperature black body (such as 20℃) and high-temperature black body (such as 100℃) respectively under low-temperature environment (such as 10℃) and high-temperature environment (such as 50℃), and based on the environmental temperature, linear interpolation is carried out, which realizes the dynamic compensation of systematic error in the edge area of the temperature measurement interval. Effectively solve the problem of high precision in the middle temperature area and low precision in the high and low temperature ends after three calibrations, and through limited four-point deviation data, a global error correction model is constructed. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 is a flowchart of a temperature calibration method of an infrared temperature measurement thermal imager in an embodiment of the present application; Figure 2 is another flowchart of a temperature calibration method of an infrared temperature measurement thermal imager in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The present application will be further described in detail below with reference to the accompanying drawings.

[0026] In order to facilitate the understanding or improvement of the technical solutions of the present application, the existing mainstream infrared temperature measurement thermal imager temperature calibration method will be described first: The specific steps of the existing mainstream technical solution are as follows: S1: Obtain the temperature response curve of the infrared temperature measurement thermal imager.

[0027] The specific process is: S11, select a group of data with certain temperature interval in the temperature range measured by the detector; S12, obtain the response value array of the infrared temperature measurement thermal imager to the black body radiation source with the temperature corresponding to the above group of data when the environmental temperature is T0; S13, obtain the relationship curve T=f(Y) of the response value Y (independent variable) and the temperature T (dependent variable) by least square method according to the obtained response value array, and the specific relationship curve can be a fourth order function; S14, record the environmental temperature T0.

[0028] S2: Obtain the temperature drift curve.

[0029] The specific process is: S21, select higher temperature value Th and lower temperature value Tl with larger temperature interval in the temperature range measured by the detector; S22: Through step S1, obtain the response values and corresponding to temperatures Th and Tl when the environmental temperature is T0; S23: Obtain the response values corresponding to temperatures Th and Tl under different environmental temperatures Ti and ; S24: temperature drift compensation is performed, and a relationship between the original response and the corrected response value is established.

[0030] wherein, is the corrected response value at Ti ambient temperature, is the original response value at Ti ambient temperature,

[0031]

[0032] By collecting the response values corresponding to temperatures Th and Tl at different ambient temperatures Ti and , and and obtained in S1, the temperature drift correction function at the ambient temperature can be obtained .

[0033] S3: obtaining the calibrated temperature.

[0034] The specific process is as follows: S31, obtaining the ambient temperature Ti by a temperature sensor, and calling corresponding data according to the ambient temperature , , and , and calculating the temperature drift correction function corresponding to the ambient temperature Ti .

[0035] S32, bringing the original response value into the temperature drift correction function to obtain the corrected response value .

[0036] S33, bringing the corrected response value into the temperature response curve T=f(Y) to obtain the calibrated temperature.

[0037] The defects of the prior art are that the prior scheme needs to calibrate the temperature drift data caused by the change of the ambient temperature, and the way is to sample the actual response data (the data after temperature drift) under different ambient temperatures and find the functional relationship between the data and the calibration data. The relationship between the two is approximately linear. The temperature drift data of a certain ambient temperature can be calibrated by a linear function. In order to obtain better temperature measurement accuracy, fine temperature drift data needs to be collected. The more data collected, the higher the temperature measurement accuracy. For example, collecting every 5 degrees Celsius is more accurate than collecting every 10 degrees Celsius. At the same time, due to the difference in response characteristics and temperature drift characteristics of each device, comprehensive calibration needs to be performed on each pixel of each device. Therefore, this calibration algorithm not only has complex calibration process, but also involves a large amount of data storage, which increases the labor cost, management cost of product production, and the complexity of software and hardware of the system, and also increases the hardware cost.

[0038] In an embodiment, as shown in Figure 1 The present application discloses an infrared temperature measurement thermal imager temperature calibration method, specifically comprising the following steps: S1: uniformly selecting a plurality of temperature points in the temperature measurement range, and establishing a first mapping relationship between the response value of the infrared temperature measurement thermal imager and the temperature measurement value by the least square method.

[0039] In this embodiment, the principle of temperature measurement of the infrared temperature measurement thermal imager: any object with a temperature higher than absolute zero will radiate infrared rays, and the energy of the radiation is related to the temperature of the object. The higher the temperature, the stronger the infrared energy. By finding the relationship between the output of the detector and the target temperature, temperature measurement can be performed. In the actual temperature measurement process, the output of the detector is related to three variables: target radiation, additional radiation and ambient temperature.

[0040] Specifically, the present application calibrates the response difference, temperature drift and additional radiation of the detector by recording the response value of the detector to the shutter and the center temperature black body (for example, the temperature measurement interval of 0-120℃, and the center temperature is 60℃) under different ambient temperatures, which is called three calibrations. After three calibrations, the temperature measurement accuracy of the center temperature point can meet the requirements.

[0041] For example, the temperature measurement range of the infrared temperature measurement thermal imager is 0-120℃, N=13 temperature points (such as 0℃, 10℃, 20℃…120℃) are uniformly selected in the temperature measurement range [0℃, 120℃], and a high-precision black body is used as a standard temperature source. In the center of the target field of view of the thermal imager, 8x8 pixel regions are selected, and a total of 64 pixels are obtained.

[0042] Specifically, step S1 comprises: Select 8x8 pixels in the center region of the infrared temperature measurement thermal imager, and obtain the average value of 64 pixel response values , to determine the infrared thermal imaging thermometer response value, that is, to form 64 sets of response value data , where i = 1 ~ 64.

[0043] N temperature points are uniformly and evenly spaced within the temperature measurement range of the infrared thermal imaging thermometer, and the average response of the 64 pixels to the N blackbody temperatures is measured, and the response value of the intermediate temperature blackbody is recorded (if the temperature measurement range is 0℃ to 120℃, the response value is ), taking the infrared thermal imaging thermometer response value D as the independent variable and the temperature measurement value T as the dependent variable, and fitting a polynomial function by the least square method: , where is the temperature measurement value, in degrees Celsius ℃; is the corrected response value of the infrared thermal imaging thermometer, is the temperature mapping function.

[0044] Specifically, taking the temperature T as the dependent variable and the response value as the independent variable, a polynomial regression model is constructed: , where n is a 3~5th order polynomial, the optimal order is determined by cross-validation, and the goodness of fit ≥0.995. The temperature mapping function is obtained, and it should be noted that is the corrected value of the single-pixel response value after subsequent calibration.

[0045] In this embodiment, the median temperature of the temperature measurement range =60℃ is set as the reference temperature point, and the response value of the 60℃ blackbody is measured .

[0046] S2: based on the obtained ambient temperature, a first correlation function of shutter response value and ambient temperature is established; based on the ambient temperature, a second correlation function of blackbody response value of intermediate reference temperature and ambient temperature is established.

[0047] In this embodiment, based on the obtained ambient temperature, a first correlation function of shutter response value and ambient temperature is established, including: obtaining the response value of the temperature measurement thermometer to the shutter (known constant reflectivity) under different ambient temperatures, to obtain the shutter response value of the temperature measurement thermometer under different ambient temperatures ; taking the ambient temperature as the independent variable and the shutter response value as the dependent variable, fitting a polynomial function by the least square method: , where is an ambient temperature, is a first correlation function of the shutter response value and the ambient temperature.

[0048] For example, a plurality of ambient temperature points are selected in the working temperature range of the thermal imaging camera, and the response value of the shutter is measured at each ambient temperature (64-pixel average value), and a polynomial function is constructed:

[0049] where m is a 2-3 order polynomial fitted by the least square method.

[0050] In this embodiment, a second correlation function of the blackbody response value of the intermediate reference temperature and the ambient temperature is established based on the ambient temperature, and specifically includes: The response value of the thermal imaging camera to the blackbody of the intermediate reference temperature is obtained at different ambient temperatures, and the 64-pixel average value of the intermediate reference temperature is obtained, and the intermediate reference temperature is the middle value of the temperature measurement range; the ambient temperature is an independent variable, and the blackbody response value of the intermediate reference temperature is a dependent variable, and a polynomial function is fitted by the least square method: wherein, is an ambient temperature, is the blackbody response value of the intermediate reference temperature of the thermal imaging camera at different ambient temperatures, is a second correlation function of the blackbody response value of the intermediate reference temperature and the ambient temperature.

[0051] Specifically, the response value of the 60℃ blackbody at different ambient temperatures is measured , and a polynomial function is constructed: , n is a 3-5 order polynomial, the optimal order is determined by cross-validation, and and are stored as the ambient temperature compensation model.

[0052] S3: Based on the preset three-term calibration model, the response value of the thermal imaging camera is calibrated in combination with the first correlation function and the second correlation function.

[0053] In this embodiment, the shutter response correction value is calculated according to ; the intermediate reference temperature (60℃ is taken as an example in this embodiment) is calculated according to ; based on the preset three-term calibration model, the response value of the thermal imaging camera is calibrated in combination with the first correlation function and the second correlation function, including: The preset three-term calibration model adopts the following formula:

[0054] wherein D is the actual response value of each pixel of the temperature measurement thermal imager, is the response value of each pixel of the temperature measurement thermal imager to the shutter, is the response value of the temperature measurement thermal imager to the shutter at different ambient temperatures, is the response value of the temperature measurement thermal imager to the shutter at different ambient temperatures, Intermediate reference temperature is the blackbody response value of the temperature measurement thermal imager at different ambient temperatures, and is fitted by the average value of the responses of 64 pixels, is the response value of the infrared temperature measurement thermal imager after pixel difference calibration, temperature drift calibration and additional radiation correction.

[0055] The temperature measurement range of the present embodiment is [0℃, 120℃], and the intermediate reference temperature is 60℃ for illustration; the formula of the preset three calibration models is: wherein is the blackbody response value of the temperature measurement thermal imager to 60℃ at different ambient temperatures, and is fitted by the average value of the responses of 64 pixels.

[0056] S4: based on the calibrated temperature measurement thermal imager response value and the first mapping relationship, the temperature data after pixel difference calibration, temperature drift calibration and additional radiation calibration is calculated.

[0057] In the present embodiment, the calibrated response value is substituted into the mapping function of step S1 to calculate the calibration temperature : . Thus, the temperature data after pixel difference calibration, temperature drift calibration and additional radiation calibration is output, and the real-time calibration of a single frame image is completed. The average value of the response values of the central region 8x8 pixels (64 pixels) is calculated to eliminate the random noise of a single pixel, the shutter calibration is performed, i.e. the difference between the pixels of the detector is eliminated through in the three calibration formulas. The additional radiation is eliminated through the first correlation function, and the temperature drift is eliminated through the second correlation function.

[0058] In an embodiment, as shown in Figure 2 , an infrared temperature measurement thermal imager temperature calibration method further comprises: S5: in a low-temperature environment, the first low-temperature blackbody measured deviation value and the first high-temperature blackbody measured deviation value are obtained by comparing the standard temperature value; in a high-temperature environment, the second low-temperature blackbody measured deviation value and the second high-temperature blackbody measured deviation value are obtained by comparing the standard temperature value.

[0059] In the embodiment, the four-point calibration mechanism is further introduced in the three-item calibration technology; since the temperature measurement accuracy of the center temperature point after the three-item calibration can meet the requirements, the temperature measurement error of the temperature area far from the center point will increase with the distance from the center point, and the four-point calibration algorithm can reduce the error to the required range. By measuring the actual measurement deviation values of the low-temperature black body (such as 20℃) and the high-temperature black body (such as 100℃) in the low-temperature environment (such as 10℃) and the high-temperature environment (such as 50℃) respectively, and performing linear interpolation based on the environmental temperature, the systematic error of the edge area of the temperature measurement interval is dynamically compensated. The problem that the accuracy of the medium-temperature area is high after the three-item calibration, but the accuracy of the high-temperature and low-temperature ends is low is effectively solved, and a global error correction model is constructed by using limited four-point deviation data.

[0060] Specifically, the low-temperature environment is 10℃ and the high-temperature environment is 50℃ in the embodiment, and other temperature measurement ranges are also applicable to the four-point calibration process of the application, and the purpose is to make the temperature measurement accuracy of the whole temperature measurement area meet the requirements.

[0061] S6: Based on the temperature difference between the high-temperature environment and the low-temperature environment, the low-temperature deviation value and the high-temperature deviation value under the current environmental temperature are calculated by a linear interpolation formula.

[0062] In the embodiment, the calculation formula of the low-temperature deviation value is: wherein, is the first low-temperature black body actual measurement deviation value, , is the measurement value of the 20℃ black body in the low-temperature environment; is the second low-temperature black body actual measurement deviation value, , is the measurement value of the 20℃ black body in the high-temperature environment; is the high-temperature environment temperature, is the low-temperature environment temperature; is the current environmental temperature; The calculation formula of the high-temperature deviation value is: wherein, is the first high-temperature black body actual measurement deviation value, , is the measurement value of the 100℃ black body in the low-temperature environment; is the second high-temperature black body actual measurement deviation value, , is the measurement value of the 100℃ black body in the high-temperature environment.

[0063] Further, when the target temperature measurement range is different, the calculation formula is: the first low-temperature black body actual measurement deviation value ; the second low-temperature black body actual measurement deviation value ; first high-temperature blackbody measured deviation value ; second high-temperature blackbody measured deviation value .

[0064] S7: using a four-point calibration calculation formula, performing measurement temperature compensation based on the calibrated temperature data to obtain a final calibration temperature.

[0065] In the embodiment, the calculation formula of the final calibration temperature is as follows: wherein, is the measurement temperature after three-item compensation based on the preset three-item calibration model, is the measurement temperature after four-point compensation.

[0066] Further, when the target temperature measurement range is different, the calculation formula of the final calibration temperature is as follows: Specifically, the present application can simplify the calibration of the infrared temperature measurement thermal imager. While ensuring high temperature measurement accuracy, the calibration process is much simpler. In the case of unchanged lens, the three-item calibration data can be shared between different temperature measurement thermal imagers (of the same model), and only one set of three-item calibration data needs to be collected. Each infrared temperature measurement thermal imager only needs to perform four-point calibration after using the shared three-item calibration data to meet the temperature measurement accuracy requirements. The three-item calibration data is only single-point data (collecting data on the average response of the center 64 pixels), and the data volume is very small. The four-point calibration data is four frames of data, and the data volume is also greatly reduced. In the calibration process, the data of the three-item calibration part can be shared (only needs to be calibrated once, greatly reducing the use of high and low temperature boxes, blackbodies, etc.), which leads to a reduction in the cost of equipment required for the calibration process (such as fewer blackbodies, fewer high and low temperature boxes, and smaller volume), less energy consumption generated by calibration (because each temperature measurement thermal imager needs to consume a large amount of electric energy if it needs to collect data at each temperature segment in the high and low temperature box), lower labor cost required for calibration, and lower management cost required for production process, thereby reducing the comprehensive calibration cost of the infrared temperature measurement thermal imager.

[0067] Therefore, the present application can greatly simplify the calibration process of the infrared temperature measurement thermal imager, and the temperature calibration data used is limited. The labor cost and management cost generated during calibration can be greatly reduced, and the hardware cost can also be reduced.

[0068] It should be understood that the sequence numbers of the steps in the above embodiments do not mean the order of execution, and the execution order of the processes should be determined according to their functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0069] In an embodiment, an infrared thermal imaging thermometer temperature calibration system is provided, which corresponds to the infrared thermal imaging thermometer temperature calibration method in the above embodiment.

[0070] An infrared thermal imaging thermometer temperature calibration system comprises a temperature point selection module, a reference benchmark determination module, an environment correlation modeling module, a response calibration module and a temperature calculation module. The detailed description of each functional module is as follows: The temperature point selection module is configured to uniformly select a plurality of temperature points in a temperature measurement range and establish a first mapping relationship between the response value of the infrared thermal imaging thermometer and the temperature measurement value by using the least square method. The environment correlation modeling module is configured to establish a first correlation function between the shutter response value and the environment temperature based on the obtained environment temperature, and establish a second correlation function between the blackbody response value of the intermediate reference temperature and the environment temperature. The response calibration module is configured to calibrate the response value of the temperature measurement thermometer based on the preset three-item calibration model and in combination with the first correlation function and the second correlation function. The temperature calculation module is configured to calculate the temperature data after the pixel difference calibration, the temperature drift calibration and the additional radiation calibration based on the calibrated response value of the temperature measurement thermometer and the first mapping relationship.

[0071] The specific limitations of the infrared thermal imaging thermometer temperature calibration system can be referred to the limitations of the infrared thermal imaging thermometer temperature calibration method in the above embodiment, which will not be described herein again. Each module in the infrared thermal imaging thermometer temperature calibration system can be realized by software, hardware or a combination thereof. Each module can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to each module.

[0072] In an embodiment, a computer readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the following steps are implemented: S1: uniformly selecting a plurality of temperature points in a temperature measurement range and establishing a first mapping relationship between the response value of the infrared thermal imaging thermometer and the temperature measurement value by using the least square method. S2: establishing a first correlation function between the shutter response value and the environment temperature based on the obtained environment temperature, and establishing a second correlation function between the blackbody response value of the intermediate reference temperature and the environment temperature based on the environment temperature. S3: calibrating the response value of the temperature measurement thermometer based on the preset three-item calibration model and in combination with the first correlation function and the second correlation function. S4: based on the calibrated temperature measurement thermal imager response value and the first mapping relationship, the temperature data after pixel difference calibration, temperature drift calibration and additional radiation calibration is calculated.

[0073] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, database or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM) and the like.

[0074] In one embodiment, in particular, according to the embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, the embodiments of the present application include a computer program product including computer programs / instructions that, when executed by a processor, implement the steps of the infrared temperature measurement thermal imager temperature calibration method as described. In such embodiments, the computer program can be downloaded and installed from a network through a communication module, and / or installed from a detachable medium. When the computer program is executed by a central processing unit (CPU), various functions defined in the present application are performed.

[0075] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of functional units and modules is exemplified. In actual applications, the above-mentioned functions can be completed by different functional units and modules according to needs, i.e. the internal structure of the device is divided into different functional units or modules to complete all or part of the above-described functions.

[0076] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand; it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the features; and 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 application, and should be included in the protection scope of the present application.

Claims

1. A method for calibrating an infrared thermal imager, characterized in that, include: Multiple temperature points are uniformly selected within the temperature measurement range, and the first mapping relationship between the infrared thermal imager response value and the temperature measurement value is established by the least squares method. Based on the acquired ambient temperature, a first correlation function between the shutter response value and the ambient temperature is established; based on the ambient temperature, a second correlation function between the blackbody response value at an intermediate reference temperature and the ambient temperature is established. Based on three preset calibration models, the response value of the temperature measuring thermal imager is calibrated by combining the first correlation function and the second correlation function; Based on the calibrated thermal imager response value and the first mapping relationship, the temperature data after pixel difference calibration, temperature drift calibration and additional radiation calibration are calculated.

2. The infrared thermal imager temperature measurement calibration method according to claim 1, characterized in that, The step of uniformly selecting multiple temperature points within the temperature measurement range and establishing a first mapping relationship between the infrared thermal imager response value and the temperature measurement value using the least squares method includes: Select 8×8 pixels in the central area of ​​the infrared thermal imager and obtain the average value of the response values ​​of 64 pixels to determine the response value of the infrared thermal imager. Within the temperature measurement range of the infrared thermal imager, N temperatures are evenly spaced. The average response of 64 pixels to each of the N blackbody temperatures is measured, and the response value of the blackbody at the intermediate temperature is recorded. Using the infrared thermal imager response value D as the independent variable and the temperature measurement value T as the dependent variable, a polynomial function is fitted using the least squares method: in, This is a temperature measurement value. This is the corrected response value of the infrared thermal imager. This is a temperature mapping function.

3. The infrared thermal imager temperature measurement calibration method according to claim 2, characterized in that, The step of establishing a first correlation function between the shutter response value and the ambient temperature based on the acquired ambient temperature includes: The shutter response values ​​of the thermal imager under different ambient temperatures were obtained, thus yielding the shutter response values ​​of the thermal imager under different ambient temperatures. ; Based on ambient temperature As the independent variable, the shutter response value As the dependent variable, fit a polynomial function using the least squares method: in, For ambient temperature, The shutter response values ​​of the thermal imager under different ambient temperatures are shown. This is the first correlation function between the shutter response value and the ambient temperature.

4. The infrared thermal imager temperature measurement calibration method according to claim 3, characterized in that, The establishment of a second correlation function between the blackbody response value at an intermediate reference temperature and the ambient temperature, based on the ambient temperature, specifically includes: The response values ​​of the thermal imager to the intermediate reference temperature blackbody under different ambient temperatures are obtained, and the blackbody response value of the intermediate reference temperature is obtained. The intermediate reference temperature is the median value of the temperature measurement range. Based on ambient temperature Using the blackbody response at the intermediate reference temperature as the independent variable and the blackbody response at the intermediate reference temperature as the dependent variable, a polynomial function is fitted using the least squares method: in, For ambient temperature, The blackbody response values ​​of the thermal imager to the intermediate reference temperature under different ambient temperatures are given. This is a second correlation function between the blackbody response value at the intermediate reference temperature and the ambient temperature.

5. The infrared thermal imager temperature measurement calibration method according to claim 4, characterized in that, The calibration of the thermal imager response value based on the preset three-item calibration model, combined with the first correlation function and the second correlation function, includes: The three preset calibration models are based on the following formulas: Where D is the actual response value acquired by each pixel of the thermal imager. To measure the shutter response values ​​of each pixel in the thermal imager, The shutter response values ​​of the thermal imager under different ambient temperatures are shown. The blackbody response values ​​of the thermal imager to the intermediate reference temperature under different ambient temperatures are given. and It was obtained by fitting the average response of 64 pixels. The response value of the infrared thermal imager after pixel difference calibration, temperature drift calibration, and additional radiation correction.

6. A temperature measurement calibration method for an infrared thermal imager according to claim 1 or 5, characterized in that, The method also includes: In low-temperature environments, the measured deviation values ​​of the first low-temperature blackbody and the first high-temperature blackbody are obtained by comparing with standard temperature values; in high-temperature environments, the measured deviation values ​​of the second low-temperature blackbody and the second high-temperature blackbody are obtained by comparing with standard temperature values. Based on the temperature difference between the high-temperature environment and the low-temperature environment, the low-temperature deviation value and the high-temperature deviation value at the current ambient temperature are calculated using a linear interpolation formula; The four-point calibration calculation formula is used to perform measurement temperature compensation based on the calibrated temperature data to obtain the final calibration temperature.

7. The infrared thermal imager temperature measurement calibration method according to claim 6, characterized in that, The methods include: The calculation of the low-temperature deviation and high-temperature deviation values ​​at the current ambient temperature based on the temperature difference between the high-temperature environment and the low-temperature environment using a linear interpolation formula includes: The formula for calculating the low-temperature deviation value is: in, This represents the measured deviation value for the first low-temperature blackbody. , The values ​​are measured for a blackbody at 20℃ under low-temperature conditions. This is the measured deviation value of the second low-temperature blackbody. , The values ​​are measured for a blackbody at 20℃ under high-temperature conditions. For high temperature environments, The ambient temperature is low. The current ambient temperature; The formula for calculating the high temperature deviation value is: in, This represents the measured deviation value for the first high-temperature blackbody. , The values ​​are measured for a blackbody at 100℃ under low-temperature conditions. This represents the measured deviation value for the second high-temperature blackbody. , The measured value is for a blackbody at 100℃ under high temperature conditions; The four-point calibration calculation formula is used to perform temperature compensation based on the calibrated temperature data to obtain the final calibration temperature. The calculation formula is as follows: in, The measured temperature is based on a preset three-calibration model with three-factor compensation. The measured temperature is after four-point compensation.

8. A temperature measurement calibration system for an infrared thermal imager, characterized in that, The system is used to perform the infrared thermal imager temperature measurement calibration method as described in any one of claims 1 to 7, the system comprising: The temperature point selection module is used to uniformly select multiple temperature points within the temperature measurement range and establish the first mapping relationship between the infrared thermal imager response value and the temperature measurement value using the least squares method. The environmental correlation modeling module is used to establish a first correlation function between the shutter response value and the ambient temperature based on the acquired ambient temperature, and to establish a second correlation function between the blackbody response value of the intermediate reference temperature and the ambient temperature. The response calibration module is used to calibrate the response value of the thermal imager based on three preset calibration models, combined with the first correlation function and the second correlation function; The temperature calculation module is used to calculate the temperature data after pixel difference calibration, temperature drift calibration and additional radiation calibration based on the calibrated thermal imager response value and the first mapping relationship.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the infrared thermal imager temperature measurement calibration method as described in any one of claims 1 to 7.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the infrared thermal imager temperature measurement calibration method as described in any one of claims 1 to 7.

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