Infrared Target Temperature Uniformity Correction and Temperature Control Method Based on Temperature Characteristics

Abstract

The present application relates to an infrared target temperature uniformity correction and temperature control method, device, computer equipment, storage medium and computer program product based on temperature characteristics. The method includes: performing temperature uniformity correction on the infrared target to obtain a corrected gray matrix at each temperature; controlling the infrared target to generate heat based on the corrected gray matrix at the target temperature; when the temperature difference between the target temperature and the actual temperature is greater than or equal to a preset deviation threshold, determining a gray deviation matrix according to the corrected gray matrix corresponding to the target temperature and the gray matrix corresponding to the actual temperature; adjusting the corrected gray matrix based on the gray deviation matrix to obtain an adjusted gray matrix; taking the adjusted gray matrix as the corrected gray matrix corresponding to the new target temperature, and returning to the step of controlling the infrared target to generate heat based on the corrected gray matrix at the target temperature until the temperature difference is less than the preset deviation threshold. Using this method can accurately and stably control the temperature of the infrared target.

Description

Technical Field

[0001] The present application relates to the technical field of infrared targets, and in particular, to a method, device, computer device, storage medium, and computer program product for infrared target temperature uniformity correction and temperature control based on temperature characteristics. Background Art

[0002] The temperature control system of an infrared target is used to maintain the temperature of the infrared target at a set value and keep the uniformity.

[0003] For the existing infrared targets, if the surface temperature of the infrared target is uneven, for example, the temperature in the middle is high and the temperature at the edge is low, then when measured with an infrared device, the readings at different positions will be different, resulting in inaccurate calibration. When it is necessary to keep the temperature of the infrared target at 50 °C, if the system fluctuates greatly, the actual temperature of the infrared target may vary between 48 and 52, which easily affects the reliability of the measurement results. Moreover, the temperature control performance of the temperature control system of the existing infrared targets deteriorates in a complex environment (such as wind speed change), and the adaptability is insufficient. For example, it cannot sense the wind speed in real time and adjust the heating power, resulting in temperature fluctuations.

[0004] Therefore, there is a problem in the traditional technology that the temperature uniformity correction and temperature stable control of the infrared target cannot be accurately performed. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a method, device, computer device, computer-readable storage medium, and computer program product for infrared target temperature uniformity correction and temperature control based on temperature characteristics that can accurately perform temperature uniformity correction and temperature stable control on the infrared target.

[0006] A method for infrared target temperature uniformity correction and temperature control based on temperature characteristics, the method includes: at each temperature, based on the initial gray matrix corresponding to each temperature, performing temperature uniformity correction on the infrared target to obtain the corrected gray matrix of the infrared target at each temperature; determining the target temperature that the infrared target needs to maintain, based on the corrected gray matrix corresponding to the target temperature, controlling the infrared target to generate heat, and measuring the actual temperature of the infrared target through a temperature sensor; in the case where the temperature difference between the target temperature and the actual temperature is greater than or equal to a preset deviation threshold, determining a gray deviation matrix according to the corrected gray matrix corresponding to the target temperature and the gray matrix corresponding to the actual temperature; based on the gray deviation matrix, adjusting the corrected gray matrix corresponding to the target temperature to obtain the adjusted gray matrix corresponding to the target temperature; taking the adjusted gray matrix corresponding to the target temperature as the corrected gray matrix corresponding to the new target temperature, and returning to the step of controlling the infrared target to generate heat based on the corrected gray matrix corresponding to the target temperature, until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold.

[0007] In one embodiment, based on the initial gray matrix corresponding to each temperature, temperature uniformity correction is performed on the infrared target to obtain the corrected gray matrix of the infrared target at each temperature, including: for any temperature, based on the initial gray matrix corresponding to the temperature, control the infrared target to generate heat, and use an infrared thermal imager to obtain the infrared image of the infrared target, and extract the actual temperature matrix from the infrared image; according to the actual temperature matrix, determine the standard deviation of temperature uniformity; in the case where the standard deviation of temperature uniformity is greater than or equal to the preset standard deviation threshold, based on the pre-constructed temperature-gray relationship model, determine the actual gray matrix corresponding to the actual temperature matrix; the temperature-gray relationship model represents the corresponding relationship between temperature and gray; use the gray matrix iteration model to iterate the actual gray matrix to obtain the iterated gray matrix corresponding to the actual gray matrix; use the iterated gray matrix as the initial gray matrix, and return to the step of controlling the infrared target to generate heat based on the initial gray matrix corresponding to the temperature until the standard deviation of temperature uniformity is less than the preset standard deviation threshold; use the iterated gray matrix as the corrected gray matrix.

[0008] In one embodiment, using the gray matrix iteration model to iterate the actual gray matrix to obtain the iterated gray matrix corresponding to the actual gray matrix, including: according to the actual gray matrix and the initial gray matrix, determine the deviation matrix of the current iteration round; obtain the calibration weight matrix corresponding to the current iteration round, and use the calibration weight matrix corresponding to the current iteration round to adjust the deviation matrix of the current iteration round to obtain the adjustment information of the current iteration round for the initial gray matrix; use the adjustment information of the current iteration round for the initial gray matrix to adjust the initial gray matrix to obtain the iterated gray matrix.

[0009] In one embodiment, the calibration weight matrix includes the calibration weights for each target position point in the infrared target; obtaining the calibration weight matrix corresponding to the current iteration round includes: obtaining the deviation change direction information, deviation change amplitude information, and deviation change trend information corresponding to each target position point in the current iteration round; based on the deviation change direction information, deviation change amplitude information, and deviation change trend information corresponding to each target position point, generate the iteration state vector corresponding to each target position point; use the iteration state vector corresponding to each target position point as an index to query the calibration weights matching each target position point in the pre-constructed calibration weight table; based on the calibration weights matching each target position point, generate the calibration weight matrix corresponding to the current iteration round.

[0010] In one embodiment, after the step of performing temperature uniformity correction on the infrared target based on the initial gray-scale matrix corresponding to each temperature to obtain the corrected gray-scale matrix of the infrared target at each temperature, the method further includes: determining the gray-scale fitting coefficient matrix corresponding to each temperature according to the initial gray-scale matrix and the corrected gray-scale matrix corresponding to each temperature; constructing a mapping model according to each temperature and the gray-scale fitting coefficient matrix corresponding to each temperature; the mapping model represents the mapping relationship between the temperature and the gray-scale fitting coefficient matrix.

[0011] In one embodiment, adjusting the corrected gray-scale matrix corresponding to the target temperature based on the gray-scale deviation matrix to obtain the adjusted gray-scale matrix corresponding to the target temperature includes: determining the gray-scale fitting coefficient matrix for the target temperature based on the mapping model; adjusting the gray-scale deviation matrix using the gray-scale fitting coefficient matrix to obtain the adjustment information for the corrected gray-scale matrix corresponding to the target temperature; adjusting the corrected gray-scale matrix corresponding to the target temperature using the adjustment information to obtain the adjusted gray-scale matrix corresponding to the target temperature.

[0012] An infrared target temperature uniformity correction and temperature control device based on temperature characteristics, the device includes: a temperature uniformity correction module, configured to perform temperature uniformity correction on the infrared target based on the initial gray-scale matrix corresponding to each temperature at each temperature to obtain the corrected gray-scale matrix of the infrared target at each temperature; a temperature measurement module, configured to determine the target temperature that the infrared target needs to maintain, control the infrared target to generate heat based on the corrected gray-scale matrix corresponding to the target temperature, and measure the actual temperature of the infrared target through a temperature sensor; a temperature determination module, configured to determine the gray-scale deviation matrix according to the corrected gray-scale matrix corresponding to the target temperature and the gray-scale matrix corresponding to the actual temperature when the temperature difference between the target temperature and the actual temperature is greater than or equal to a preset deviation threshold; a gray-scale adjustment module, configured to adjust the corrected gray-scale matrix corresponding to the target temperature based on the gray-scale deviation matrix to obtain the adjusted gray-scale matrix corresponding to the target temperature; a temperature control module, configured to use the adjusted gray-scale matrix corresponding to the target temperature as the corrected gray-scale matrix corresponding to the new target temperature, and return to the step of controlling the infrared target to generate heat based on the corrected gray-scale matrix corresponding to the target temperature until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold.

[0013] A computer device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0014] A computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0015] A computer program product includes a computer program which, when executed by a processor, implements the steps of the above-mentioned method.

[0016] The above-mentioned infrared target temperature uniformity correction and temperature control method, device, computer device, storage medium and computer program product based on temperature characteristics perform temperature uniformity correction on the infrared target based on the initial gray matrix corresponding to each temperature at each temperature, and obtain the corrected gray matrix of the infrared target at each temperature; determine the target temperature that the infrared target needs to maintain, control the infrared target to generate heat based on the corrected gray matrix corresponding to the target temperature, and measure the actual temperature of the infrared target through a temperature sensor; when the temperature difference between the target temperature and the actual temperature is greater than or equal to a preset deviation threshold, determine the gray deviation matrix according to the corrected gray matrix corresponding to the target temperature and the gray matrix corresponding to the actual temperature; based on the gray deviation matrix, adjust the corrected gray matrix corresponding to the target temperature to obtain the adjusted gray matrix corresponding to the target temperature; use the adjusted gray matrix corresponding to the target temperature as the corrected gray matrix corresponding to the new target temperature, and return to the step of controlling the infrared target to generate heat based on the corrected gray matrix corresponding to the target temperature until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold; in this way, the temperature uniformity of the infrared target can be corrected first to obtain the corrected gray matrix of the infrared target at each temperature. After the temperature uniformity correction is completed, if it is necessary to maintain the temperature of the infrared target at the target temperature, the correction of the gray matrix can be triggered when the temperature difference between the target temperature and the actual temperature is greater than or equal to the preset deviation threshold, and the gray deviation matrix determined based on the corrected gray matrix corresponding to the target temperature and the gray matrix corresponding to the actual temperature is used to quickly correct the corrected gray matrix of the target temperature, so that the temperature of the infrared target can be accurately controlled near the target temperature, improving the temperature stability of the infrared target and solving the problems in the prior art that the temperature of the infrared target cannot be accurately controlled and the temperature of the infrared target cannot be maintained stable. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a schematic flowchart of a method for infrared target temperature uniformity correction and temperature control based on temperature characteristics in an embodiment.

[0019] Figure 2Schematic diagram of the temperature uniformity correction process of an infrared target in an embodiment;

[0020] Figure 3 Schematic diagram of the temperature control process of an infrared target in an embodiment;

[0021] Figure 4 Calibration principle of an infrared target in an embodiment;

[0022] Figure 5 Schematic diagram of the relationship between input gray level and the average temperature of an infrared target in an embodiment;

[0023] Figure 6 Schematic diagram of the relationship between input gray level and the increased temperature of an infrared target in an embodiment;

[0024] Figure 7 Comparison chart of temperature uniformity before and after correction of an infrared target in an embodiment;

[0025] Figure 8 Schematic diagram of the frequency distribution of temperature values of an infrared target before and after correction in an embodiment;

[0026] Figure 9 Schematic diagram of the comparison of pixel temperature uniformity in the X-axis direction and Y-axis direction of an infrared target before and after correction in an embodiment;

[0027] Figure 10 Three-dimensional scatter plot corresponding to the gray level fitting coefficient matrix at different gray levels in an embodiment;

[0028] Figure 11 Schematic diagram of the corresponding relationship between temperature, gray level and gray level fitting coefficient in an embodiment;

[0029] Figure 12 Schematic diagram of the infrared images of 6 targets before correction in an embodiment;

[0030] Figure 13 Schematic diagram of the three-dimensional infrared images of 6 targets in an embodiment;

[0031] Figure 14 Schematic diagram of the process of the temperature uniformity correction and temperature control method of an infrared target based on temperature characteristics in another embodiment;

[0032] Figure 15 Structural block diagram of a device for temperature uniformity correction and temperature control of an infrared target based on temperature characteristics in an embodiment;

[0033] Figure 16 Internal structure diagram of a computer device in an embodiment. Detailed implementation mode

[0034] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0035] The infrared target temperature uniformity correction and temperature control method based on temperature characteristics provided by the embodiments of the present application can be applied to the controller of the infrared target. Among them, the infrared target includes a plurality of heating units arranged in an array board. The plurality of heating units of the infrared target are connected to the output end of the power supply circuit, and the control end of the power supply circuit is connected to the controller. The controller adjusts the temperature of the infrared target by regulating the power supply voltage output by the power supply circuit to the plurality of heating units of the infrared target.

[0036] In an exemplary embodiment, as Figure 1 shown, a method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics is provided. Taking the application of this method to the controller of the infrared target as an example, the following steps S102 to step S110 are included. Among them:

[0037] Step S102, at each temperature, based on the initial gray matrix corresponding to each temperature, perform temperature uniformity correction on the infrared target to obtain the corrected gray matrix of the infrared target at each temperature.

[0038] Among them, each temperature can be the temperature required for temperature uniformity correction. In practical applications, the temperature can be set to 25°C, 27.5°C, 30°C or any other temperature, which can be determined according to actual needs.

[0039] Among them, the initial gray matrix corresponding to each temperature can be the gray matrix that has not undergone temperature uniformity correction corresponding to each temperature.

[0040] Among them, the corrected gray matrix of the infrared target at each temperature can be the gray matrix obtained by performing temperature uniformity correction on the initial gray matrix of the infrared target at different temperatures.

[0041] Optionally, the controller controls the infrared target to generate heat at each temperature based on the initial gray matrix corresponding to each temperature, so as to perform temperature uniformity correction on the infrared target to obtain the corrected gray matrix of the infrared target at each temperature.

[0042] Step S104, determine the target temperature that the infrared target needs to maintain, based on the corrected gray matrix corresponding to the target temperature, control the infrared target to generate heat, and measure the actual temperature of the infrared target through a temperature sensor.

[0043] Among them, the target temperature can be represented by the temperature T.

[0044] It should be noted that the temperature involved in step S102 refers to the temperature corresponding to the temperature uniformity correction of the infrared target, and the target temperature involved in step S104 refers to the temperature that the infrared target needs to maintain when the temperature of the infrared target is stably controlled. In practical applications, the target temperature involved in step S104 is within the temperature range formed by the temperatures involved in step S102. For example, if step S102 performs temperature uniformity correction on the infrared target at temperatures of 25°C, 27.5°C, and 30°C, then the target temperature T in the subsequent step S104 should be any temperature between 25°C and 30°C.

[0045] It should also be noted that the gray values of the elements in the initial gray matrix corresponding to each temperature can be the same, that is, the gray values of the elements in the initial gray matrix of each temperature can all be the gray values corresponding to each temperature, while the gray values of the elements in the corrected gray matrix corresponding to each temperature can be different, that is, the gray values of the elements in the corrected gray matrix corresponding to each temperature are not necessarily all the gray values corresponding to each temperature.

[0046] Among them, the actual temperature can be obtained by controlling the infrared target to generate heat according to the corrected gray matrix corresponding to the target temperature T, and measuring the temperature of the infrared target with a temperature sensor after the temperature is stable. 。

[0047] In practical applications, after the infrared target generates heat according to the corrected gray matrix corresponding to the target temperature T, the measured actual temperature of the infrared target may be different from the preset temperature T. If it is necessary to control the actual temperature of the infrared target within a certain temperature range, the technical solution of the present application can be adopted to achieve precise and stable control of the temperature of the infrared target.

[0048] Optionally, when it is determined that the temperature of the infrared target needs to be maintained at the target temperature T, the corrected gray matrix corresponding to the target temperature T is determined , and the corrected gray matrix corresponding to the target temperature T is input to the host computer, and the host computer sends the corrected gray matrix corresponding to the target temperature T to the controller of the infrared target. The controller of the infrared target controls the infrared target to generate heat according to the corrected gray matrix corresponding to the target temperature T , and after the heat generation is stable, the actual temperature of the infrared target is measured with a temperature sensor 。

[0049] Step S106, when the temperature difference between the target temperature and the actual temperature is greater than or equal to a preset deviation threshold, determine a grayscale deviation matrix according to the corrected grayscale matrix corresponding to the target temperature and the grayscale matrix corresponding to the actual temperature.

[0050] Among them, the temperature difference can be the temperature difference value between the target temperature T and the actual temperature between them.

[0051] Among them, the preset deviation threshold can be a threshold preset for the temperature difference. Only when the temperature deviation between the target temperature and the actual temperature is less than the preset deviation threshold, can it be determined that the temperature of the infrared target is maintained relatively stable near the target temperature T, so as to achieve the effect of stably controlling the temperature of the infrared target at the target temperature T. In practical applications, the preset deviation threshold can be set to 0.2 °C, or can be freely set according to the actual temperature stability requirements.

[0052] Among them, the grayscale deviation matrix can be a matrix obtained by subtracting the corrected grayscale matrix corresponding to the target temperature from the grayscale matrix corresponding to the actual temperature.

[0053] Optionally, the controller determines the temperature difference according to the actual temperature of the infrared target and the target temperature T, and then, when the temperature deviation is greater than or equal to the preset deviation threshold of 0.2 °C, according to the grayscale matrix corresponding to the target temperature T and the grayscale matrix corresponding to the actual temperature - .

[0054] In practical applications, if the temperature difference is less than the preset deviation threshold of 0.2 °C, it means that the temperature of the infrared target is maintained relatively stable near the target temperature T at this time, and there is no need to adjust the corrected grayscale matrix corresponding to the target temperature, that is, there is no need to execute the following steps S108 to S110.

[0055] Step S108, based on the grayscale deviation matrix, adjust the corrected grayscale matrix corresponding to the target temperature to obtain an adjusted grayscale matrix corresponding to the target temperature.

[0056] Among them, the adjusted grayscale matrix corresponding to the target temperature can be a matrix obtained by adjusting the corrected grayscale matrix corresponding to the target temperature T, and the adjusted grayscale matrix corresponding to the target temperature can be expressed as .

[0057] Optionally, the controller is based on the gray deviation matrix - , to adjust the corrected gray matrix corresponding to the target temperature T , and obtain the adjusted gray matrix corresponding to the target temperature T .

[0058] Step S110, use the adjusted gray matrix corresponding to the target temperature as the corrected gray matrix corresponding to the new target temperature, and return to the step of controlling the infrared target to generate heat based on the corrected gray matrix corresponding to the target temperature until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold.

[0059] Optionally, the controller uses the adjusted gray matrix corresponding to the target temperature T as the corrected gray matrix at the new target temperature T, and returns to step S102 until the temperature difference between the target temperature T and the actual temperature is less than the preset deviation threshold of 0.2°C.

[0060] In the above infrared target temperature uniformity correction and temperature control method based on temperature characteristics, at each temperature, based on the initial gray matrix corresponding to each temperature, the temperature uniformity of the infrared target is corrected to obtain the corrected gray matrix of the infrared target at each temperature; the target temperature to be maintained by the infrared target is determined, and based on the corrected gray matrix corresponding to the target temperature, the infrared target is controlled to generate heat, and the actual temperature of the infrared target is measured by a temperature sensor; when the temperature difference between the target temperature and the actual temperature is greater than or equal to a preset deviation threshold, according to the corrected gray matrix corresponding to the target temperature and the gray matrix corresponding to the actual temperature, a gray deviation matrix is determined; based on the gray deviation matrix, the corrected gray matrix corresponding to the target temperature is adjusted to obtain the adjusted gray matrix corresponding to the target temperature; the adjusted gray matrix corresponding to the target temperature is used as the corrected gray matrix corresponding to the new target temperature, and the step of controlling the infrared target to generate heat based on the corrected gray matrix corresponding to the target temperature is returned until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold; in this way, the temperature uniformity of the infrared target can be corrected first to obtain the corrected gray matrix of the infrared target at each temperature. After the temperature uniformity correction is completed, if it is necessary to maintain the temperature of the infrared target at the target temperature, the correction of the gray matrix can be triggered when the temperature difference between the target temperature and the actual temperature is greater than or equal to the preset deviation threshold, and based on the gray deviation matrix determined by the corrected gray matrix corresponding to the target temperature and the gray matrix corresponding to the actual temperature, the corrected gray matrix of the target temperature can be quickly corrected, and the temperature of the infrared target can be accurately controlled near the target temperature, improving the temperature stability of the infrared target and solving the problems in the prior art that the temperature of the infrared target cannot be accurately controlled and the temperature of the infrared target cannot be maintained stable.

[0061] In an exemplary embodiment, based on the initial gray matrix corresponding to each temperature, correcting the temperature uniformity of the infrared target to obtain the corrected gray matrix of the infrared target at each temperature includes: for any temperature, based on the initial gray matrix corresponding to the temperature, controlling the infrared target to generate heat, and using an infrared thermal imager to obtain the infrared image of the infrared target, and extracting the actual temperature matrix from the infrared image; according to the actual temperature matrix, determining the temperature uniformity standard deviation; when the temperature uniformity standard deviation is greater than or equal to a preset standard deviation threshold, based on the pre-constructed temperature-gray relationship model, determining the actual gray matrix corresponding to the actual temperature matrix; the temperature-gray relationship model represents the corresponding relationship between temperature and gray; using the gray matrix iteration model to iterate the actual gray matrix to obtain the iterated gray matrix corresponding to the actual gray matrix; using the iterated gray matrix as the initial gray matrix, and returning the step of controlling the infrared target to generate heat based on the initial gray matrix corresponding to the temperature until the temperature uniformity standard deviation is less than the preset standard deviation threshold; using the iterated gray matrix as the corrected gray matrix.

[0062] Among them, the actual temperature matrix can be composed of the actual temperatures corresponding to each target position point in the infrared target. In practical applications, it is necessary to use an infrared thermal imager to obtain the infrared image of the infrared target, and then convert the infrared image into a grayscale image, and determine the actual temperature matrix based on the grayscale image.

[0063] Among them, the calculation method of the standard deviation of temperature uniformity can be expressed as:

[0064] ;

[0065] σ represents the standard deviation, N represents the number of target position points, represents the actual temperature of the i-th target position point, is the average value of the actual temperatures of all target position points.

[0066] Among them, the preset standard deviation threshold can be a threshold set in advance for the standard deviation of temperature uniformity. When the standard deviation of temperature uniformity is less than the preset standard deviation threshold, it can be determined that the temperature uniformity of the infrared target meets the standard. When the standard deviation of temperature uniformity is greater than or equal to the preset standard deviation threshold, it can be determined that the temperature uniformity of the infrared target does not meet the standard. In practical applications, the preset standard deviation threshold can be set to 0.4, or it can be freely set according to the actual temperature uniformity requirements.

[0067] Among them, the pre-constructed temperature-grayscale relationship model can be a model that characterizes the correlation between temperature and grayscale. The correlation between temperature and grayscale can be expressed as , where T is the temperature value and DN is the grayscale.

[0068] Among them, the grayscale matrix iteration model can be expressed as:

[0069] ,

[0070] In the formula, = DN, DN is the unified grayscale input for the first time, ε is the correction weight, and the initial value is set to 1.

[0071] Among them, the iterated grayscale matrix corresponding to the actual grayscale matrix can be expressed as , and the actual grayscale matrix can be expressed as .

[0072] Optionally, for any temperature, an initial grayscale matrix corresponding to the temperature can be input into the host computer, and then, after receiving the initial grayscale matrix of the temperature, the controller controls the infrared target to generate heat according to the initial grayscale matrix corresponding to the temperature, and after the infrared target is stably heated, an infrared thermal imager is used to measure the infrared target to obtain an infrared image, and the actual temperature matrix is ​​determined based on the infrared image; then, according to the actual temperature matrix, the temperature uniformity standard deviation STD is determined; then, when the temperature uniformity standard deviation STD is less than a preset standard deviation threshold of 0.4, the initial grayscale matrix is ​​used as the corrected grayscale matrix, and when the temperature uniformity standard deviation STD is greater than or equal to the preset standard deviation threshold of 0.4, the controller uses the pre-constructed temperature grayscale relationship model to calculate the corrected grayscale matrix. , determine the actual grayscale matrix corresponding to the actual temperature matrix, and then iterate the model based on the grayscale matrix For the actual gray matrix Iterate to obtain the iterated grayscale matrix corresponding to the actual grayscale matrix , the gray matrix after iteration As the initial grayscale matrix, the initial grayscale matrix corresponding to the temperature is returned to control the heating step of the infrared target until the temperature uniformity standard deviation is less than the preset standard deviation threshold of 0.4. Assuming that the temperature uniformity standard deviation is less than the preset standard deviation threshold, the iterative grayscale matrix is , then As the final corrected grayscale matrix.

[0073] In this embodiment, for any temperature, based on the initial grayscale matrix corresponding to the temperature, the heating of the infrared target is controlled, and an infrared thermal imager is used to obtain an infrared image of the infrared target, and the actual temperature matrix is ​​extracted from the infrared image; the temperature uniformity standard deviation is determined according to the actual temperature matrix; when the temperature uniformity standard deviation is greater than or equal to the preset standard deviation threshold, the actual grayscale matrix corresponding to the actual temperature matrix is ​​determined based on a pre-constructed temperature grayscale relationship model; the temperature grayscale relationship model characterizes the corresponding relationship between temperature and grayscale; the actual grayscale matrix is ​​iterated using a grayscale matrix iteration model to obtain an iterated grayscale matrix corresponding to the actual grayscale matrix; the iterated grayscale matrix is ​​used as the initial grayscale matrix, and the initial grayscale matrix corresponding to the temperature is returned to control the heating of the infrared target until the temperature uniformity standard deviation is less than the preset standard deviation threshold; the iterated grayscale matrix is ​​used as the corrected grayscale matrix; in this way, the temperature grayscale relationship model can be combined to improve the efficiency of temperature uniformity correction, and further, the temperature uniformity correction of the infrared target at different temperatures can be efficiently and accurately performed through the grayscale matrix iteration model.

[0074] In an exemplary embodiment, an actual grayscale matrix is iterated using a grayscale matrix iteration model to obtain an iterated grayscale matrix corresponding to the actual grayscale matrix, including: determining a deviation matrix for the current iteration round based on the actual grayscale matrix and the initial grayscale matrix; obtaining a calibration weight matrix corresponding to the current iteration round, and adjusting the deviation matrix for the current iteration round using the calibration weight matrix corresponding to the current iteration round to obtain adjustment information for the current iteration round with respect to the initial grayscale matrix; and adjusting the initial grayscale matrix using the adjustment information for the current iteration round with respect to the initial grayscale matrix to obtain the iterated grayscale matrix.

[0075] Wherein, the current iteration round may be the iteration round at which the grayscale matrix iteration model is used for iteration.

[0076] Wherein, the deviation matrix for the current iteration round may be the deviation matrix between the actual grayscale matrix and the initial grayscale matrix in the current iteration round.

[0077] Wherein, the calibration weight matrix corresponding to the current iteration round may be the calibration weight matrix ε in the grayscale matrix iteration model in the current iteration round.

[0078] Wherein, the adjustment information for the current iteration round with respect to the initial grayscale matrix may refer to the information obtained by multiplying the calibration weight matrix ε by the deviation matrix for the current iteration round and may be expressed as .

[0079] Optionally, the controller determines the deviation matrix for the current iteration round based on the actual grayscale matrix and the initial grayscale matrix , then obtains the calibration weight matrix ε corresponding to the current iteration round, and adjusts the deviation matrix for the current iteration round using the calibration weight matrix ε corresponding to the current iteration round to obtain the adjustment information for the current iteration round , and then adjusts the initial grayscale matrix using the adjustment information for the current iteration round to obtain the iterated grayscale matrix.

[0080] In this embodiment, by determining the deviation matrix of the current iteration round according to the actual gray matrix and the initial gray matrix, obtaining the calibration weight matrix corresponding to the current iteration round, and using the calibration weight matrix corresponding to the current iteration round to adjust the deviation matrix of the current iteration round, the adjustment information of the current iteration round for the initial gray matrix is obtained. Then, using the adjustment information of the current iteration round for the initial gray matrix to adjust the initial gray matrix, the iterated gray matrix is obtained. In this way, the initial gray matrix can be iterated quickly, which is beneficial to efficiently correct the temperature uniformity of the infrared target.

[0081] Actually, the calibration weight matrices ε for different iteration rounds are all different. For the determination of the calibration weight matrix ε, please refer to the specific description in the next embodiment.

[0082] In an exemplary embodiment, the calibration weight matrix includes the calibration weights for each target position point in the infrared target. Obtaining the calibration weight matrix corresponding to the current iteration round includes: obtaining the deviation change direction information, deviation change amplitude information, and deviation change trend information corresponding to each target position point in the current iteration round; generating the iteration state vector corresponding to each target position point based on the deviation change direction information, deviation change amplitude information, and deviation change trend information corresponding to each target position point; using the iteration state vector corresponding to each target position point as an index to query the calibration weight matching each target position point in the pre-constructed calibration weight table; and generating the calibration weight matrix corresponding to the current iteration round based on the calibration weights matching each target position point.

[0083] Among them, the target position point may refer to each temperature measurement point in the infrared target.

[0084] Among them, the deviation change direction information may refer to the deviation change direction pattern. In practical applications, the deviation change direction pattern can be divided into four types, namely continuous same-direction change, double alternating change, single alternating change, and random fluctuation change. Continuous same-direction change refers to the case where the number of continuous same-direction changes is greater than or equal to 3. Double alternating change refers to the case of "positive-negative-positive-negative". Single alternating change refers to the case where it reverses after two consecutive same-direction changes. Random fluctuation change refers to the case without the above three deviation change direction patterns.

[0085] Among them, the deviation change amplitude information may refer to the deviation change amplitude classification. In practical applications, the deviation change amplitude can be divided into three levels, namely small amplitude (ΔT ≤ 2°C), medium amplitude (2°C < ΔT ≤ 4°C), and large amplitude (ΔT > 4°C).

[0086] Among them, the deviation change trend information can be the deviation change trend determined based on the recent three deviation changes. In practical applications, it can be calculated based on the slopes (i.e., deviation values) of the recent 3 adjustments. The calculation formula is (|deviation value n - 2| + |deviation value n - 1| + |deviation value n|) / 3. Among them, acceleration corresponds to |slope| > 1°C, uniform speed corresponds to 0.5°C ≤ |slope| ≤ 1°C, and deceleration corresponds to |slope| < 0.5°C.

[0087] Among them, the iterative state vector can be a state vector determined based on three dimensions: deviation change direction information, deviation change amplitude information, and deviation change trend information. The total state space where the state vector is located includes thirty-six fixed states. The calculation method for the number of fixed state types is: 36 fixed states = 4 types of deviation change directions × 3 levels of deviation amplitudes × 3 types of deviation change trends = 36 fixed states.

[0088] Among them, the calibration weights corresponding to some fixed states in the pre-constructed calibration weight table can be seen in Table 1 below.

[0089] Table 1

[0090]

[0091] For the convenience of those skilled in the art to understand, the following provides the construction process of the calibration weight table, including: Steps: Step 1: Sort the importance of different iterative state vectors. Specifically, through Monte Carlo simulation, count the occurrence frequencies of each iterative state vector and control the sensitivity; Step 2: Set the coefficient boundaries. Specifically, determine the weight range (i.e., the correction coefficient range) according to physical constraints. The lower limit is set to 0.5 (which can prevent the complete loss of control effect), and the upper limit is set to 1.5 (which can avoid actuator saturation); Step 3: Fill in with manual experience. Specifically, refer to the classical control rule Bang-Bang control idea (adopt the limit value for high-risk states, such as "single alternation + large amplitude + acceleration") or PID tuning experience (the weight of medium-frequency states ≈ 1.0 - 1.1, close to the Ziegler-Nichols parameters); Step 4: Consistency verification. Specifically, ensure that the weight changes of adjacent states are smooth.

[0092] The following also exemplarily provides a design example of the calibration weight table:

[0093] {{"Continuous same direction": { "Large": {"Acceleration": 1.5, "Uniform speed": 1.3, "Deceleration": 1.2}, "Medium": {"Acceleration": 1.3, "Uniform speed": 1.2, "Deceleration": 1.1}, "Small": {"Acceleration": 1.1, "Uniform speed": 1.0, "Deceleration": 0.9}},

[0094] "Double Alternation": {"Large": {"Acceleration": 0.6, "Constant Speed": 0.7, "Deceleration": 0.8}, "Medium": {"Acceleration": 0.7, "Constant Speed": 0.8, "Deceleration": 0.9}, "Small": {"Acceleration": 0.9, "Constant Speed": 1.0, "Deceleration": 1.0}},

[0095] "Single Alternation": {"Large": {"Acceleration": 0.5, "Constant Speed": 0.6, "Deceleration": 0.7}, "Medium": {"Acceleration": 0.6, "Constant Speed": 0.7, "Deceleration": 0.8}, "Small": {"Acceleration": 0.8, "Constant Speed": 0.9, "Deceleration": 1.0}},

[0096] "Random Fluctuation": {"Large": {"Acceleration": 1.0, "Constant Speed": 1.0, "Deceleration": 1.0}, "Medium": {"Acceleration": 1.0, "Constant Speed": 1.0, "Deceleration": 1.0}, "Small": {"Acceleration": 1.0, "Constant Speed": 1.0, "Deceleration": 1.0}}。

[0097] Optionally, in the process of determining the correction coefficient matrix corresponding to the current iteration round, it is necessary to first obtain the deviation change direction patterns of the nearest 4 iteration rounds corresponding to each target position point in the current iteration round, the deviation change amplitude level of the current iteration round, and the deviation change trends of the nearest 3 iteration rounds. Then, based on the deviation change direction patterns of the nearest 4 iteration rounds corresponding to each target position point, the deviation change amplitude level of the current iteration round, and the deviation change trends of the nearest 3 iteration rounds, generate the iteration state vectors corresponding to each target position point. Then, use the iteration state vectors corresponding to each target position point as indices to query the calibration weights matching each target position point in the pre-constructed calibration weight table. Finally, based on the calibration weights matching each target position point, generate the correction coefficient matrix corresponding to the current iteration round.

[0098] In this embodiment, by obtaining the deviation change direction information, deviation change amplitude information, and deviation change trend information corresponding to each target position point in the current iteration round; based on the deviation change direction information, deviation change amplitude information, and deviation change trend information corresponding to each target position point, generating an iteration state vector corresponding to each target position point; using the iteration state vector corresponding to each target position point as an index, querying the calibration weight matching each target position point in the pre-constructed calibration weight table; and based on the calibration weight matching each target position point, generating a calibration weight matrix corresponding to the current iteration round; in this way, it is possible to fuse the information in three dimensions of deviation change direction information, deviation change amplitude information, and deviation change trend information, construct a high-resolution iteration state vector, and achieve an optimal balance between convergence speed and stability.

[0099] In an exemplary embodiment, after the step of performing temperature uniformity correction on the infrared target based on the initial gray matrix corresponding to each temperature to obtain the corrected gray matrix of the infrared target at each temperature, the method further includes: determining the gray fitting coefficient matrix corresponding to each temperature according to the initial gray matrix and the corrected gray matrix corresponding to each temperature; constructing a mapping model according to each temperature and the gray fitting coefficient matrix corresponding to each temperature; the mapping model represents the mapping relationship between temperature and the gray fitting coefficient matrix.

[0100] Among them, the gray fitting coefficient matrix corresponding to any temperature can be the gray fitting coefficient matrix determined after the temperature uniformity correction of the infrared target at this temperature, and the gray fitting coefficient matrix corresponding to this temperature includes the gray fitting coefficients corresponding to each target position point in the infrared target.

[0101] Optionally, the controller calculates the gray fitting coefficient matrix corresponding to each temperature according to the initial gray matrix and the corrected gray matrix corresponding to each temperature, and finally constructs a mapping model representing the mapping relationship between temperature and the gray fitting coefficient matrix according to each temperature and the gray fitting coefficient matrix corresponding to each temperature.

[0102] In this embodiment, by determining the gray fitting coefficient matrix corresponding to each temperature according to the initial gray matrix and the corrected gray matrix corresponding to each temperature; constructing a mapping model according to each temperature and the gray fitting coefficient matrix corresponding to each temperature; the mapping model represents the mapping relationship between temperature and the gray fitting coefficient matrix; in this way, it is possible to accurately construct a mapping model representing the mapping relationship between temperature and the gray fitting coefficient matrix. Subsequently, when performing temperature stability control on the infrared target and needing to adjust the gray matrix of the target temperature, the gray fitting coefficient matrix corresponding to the target temperature can be directly used, which is beneficial to improving the efficiency and accuracy of temperature stability control.

[0103] In an exemplary embodiment, based on the gray-scale deviation matrix, the adjusted gray-scale matrix corresponding to the target temperature is adjusted to obtain the adjusted gray-scale matrix corresponding to the target temperature, including: determining a gray-scale fitting coefficient matrix for the target temperature based on a mapping model; adjusting the gray-scale deviation matrix using the gray-scale fitting coefficient matrix to obtain adjustment information for the corrected gray-scale matrix corresponding to the target temperature; and adjusting the corrected gray-scale matrix corresponding to the target temperature using the adjustment information to obtain the adjusted gray-scale matrix corresponding to the target temperature.

[0104] Among them, the adjustment information for the gray-scale matrix corresponding to the target temperature may include the adjustment amplitude required for each matrix element (corresponding to each target position point) in the gray-scale matrix corresponding to the target temperature T. In this embodiment, the adjustment information for the gray-scale matrix corresponding to the target temperature may be expressed as , = gray-scale fitting coefficient matrix * gray-scale deviation matrix .

[0105] Optionally, the controller determines the gray-scale fitting coefficient matrix to be used when the infrared target is at the target temperature T based on a pre-constructed mapping model of temperature and gray-scale fitting coefficient matrix , and then, uses the gray-scale fitting coefficient matrix to adjust the gray-scale deviation matrix to obtain an adjustment amplitude matrix for the gray-scale matrix corresponding to the target temperature T, and then, adds the adjustment amplitude matrix to the gray-scale matrix corresponding to the target temperature T to obtain the adjusted gray-scale matrix corresponding to the target temperature T, which can be expressed as:

[0106] .

[0107] In this embodiment, by determining the gray-scale fitting coefficient matrix for the target temperature based on the mapping model; adjusting the gray-scale deviation matrix using the gray-scale fitting coefficient matrix to obtain adjustment information for the corrected gray-scale matrix corresponding to the target temperature; and adjusting the corrected gray-scale matrix corresponding to the target temperature using the adjustment information to obtain the adjusted gray-scale matrix corresponding to the target temperature; in this way, it is possible to quickly determine the gray-scale fitting coefficient matrix for the target temperature based on the pre-constructed mapping model of temperature and gray-scale fitting coefficient matrix, and use the gray-scale fitting coefficient matrix of the target temperature to adjust the gray-scale deviation matrix, thereby obtaining the adjustment information for the corrected gray-scale matrix of the target temperature, which is beneficial to accurately and effectively adjust the corrected gray-scale matrix of the target temperature.

[0108] Regarding the temperature uniformity correction process of the infrared target, reference can be made to Figure 2 the flowchart shown. Regarding the temperature control method of the infrared target, reference can be made to Figure 3 the flowchart shown.

[0109] For the convenience of those skilled in the art to understand, the following takes a single 1m * 1m infrared target as an example, and combines Figure 2 with Figure 3 the flowchart to introduce the temperature uniformity correction process and temperature control process of the infrared target.

[0110] To reduce the influence of air convection on the temperature measurement of the infrared target, during actual calibration, heat insulation materials need to be blocked around the infrared target. Figure 4 Exemplarily, a calibration principle of the infrared target is provided, which can be understood in combination with Figure 3 the flowchart shown. Among them, the host computer sends the corrected gray matrix corresponding to the target temperature to the infrared target, and the heating array of the infrared target generates heat based on the corrected gray matrix corresponding to the target temperature and produces a temperature change; after the temperature of the heating array of the infrared target is stable, the infrared thermal imager is used to measure the infrared target to obtain the actual temperature of the infrared target; the infrared thermal imager sends the actual temperature of the infrared target to the host computer, and the host computer can execute the steps of step S106 - step S110 in the above embodiments based on the temperature difference between the actual temperature and the target temperature of the infrared target, and finally control the actual temperature of the infrared target within a range close to the target temperature, so as to achieve stable temperature control of the infrared target.

[0111] Before performing temperature uniformity correction on the infrared target at different temperatures, it is necessary to establish a relationship between the temperature increase of the infrared target and the input gray level , where T is the temperature value and DN is the input gray level. Figure 5 A schematic diagram of the relationship between the input gray level and the average temperature of the infrared target is provided. Figure 6 A schematic diagram of the relationship between the input gray level and the temperature increase of the infrared target (i.e., the average temperature minus the ambient temperature) is provided. Figure 5 and Figure 6 The curves of different colors in represent the measurement data at different ambient temperatures on different dates.

[0112] When performing temperature uniformity correction on the infrared target at different temperatures, the specific process can be seen in Figure 2 .

[0113] After completing the temperature uniformity correction of the infrared target at different temperatures, temperature stable control can be performed on the infrared target. The specific process can be seen in Figure 3 .

[0114] The comparison chart of temperature uniformity before and after correction can be seen inFigure 7 , Figure 7 in (a) of Figure 7 and (c) of Figure 7 are respectively schematic diagrams of the two-dimensional infrared image and the three-dimensional infrared image of the infrared target before calibration, Figure 7 and (b) of

[0115] and (d) of Figure 8 are respectively schematic diagrams of the two-dimensional infrared image and the three-dimensional infrared image of the infrared target after calibration. Figure 8 Figure 8 The frequency distributions of the respective temperature values before and after calibration can be seen in

[0116] , where (a) of Figure 9 shows the frequency distributions of the respective temperature values of the infrared target before calibration, and (b) of Figure 9 shows the frequency distributions of the respective temperature values of the infrared target after calibration.

[0117] The standard deviation, relative deviation, maximum temperature value, minimum temperature value and temperature fluctuation before and after calibration can be seen in Table 2 below.

[0118] Table 2

[0119]

[0120] After performing temperature uniformity calibration on the infrared target at different temperatures, a gray-scale fitting coefficient matrix of the infrared target at different temperatures (i.e., different gray scales) can be obtained. The gray-scale fitting coefficient matrix can be expressed as , and the detailed explanation regarding has been described in the above embodiments.

[0121] Figure 10 shows the three-dimensional scatter plot corresponding to the gray-scale fitting coefficient matrix at different gray scales, and Table 3 below shows the application results of the gray-scale fitting coefficient matrix at different gray scales.

[0122] Table 3

[0123]

[0124] Figure 11 shows the corresponding relationship between temperature, gray scale and fitting coefficient. The gray-scale fitting coefficient includes the fitting coefficients corresponding to each temperature or each gray scale, such as Figure 11As shown, when the grayscale is the preset grayscale value or the preset temperature value, the fitting coefficients corresponding to the preset grayscale value or the preset temperature value are directly adopted. When the grayscale is in the interval of [20, 25] or the temperature is in the interval of [25°C, 27.5°C], the adopted fitting coefficient K = (K20 + K25) / 2. When the grayscale is in the interval of [25, 30] or the temperature is in the interval of [27.55°C, 30°C], the adopted fitting coefficient K = (K25 + K30) / 2, and so on.

[0125] This application also combines six 2m * 3m infrared targets together for calibration and testing, further verifying the effect that the method of this application can achieve in the temperature uniformity correction process of multiple targets. The data comparison of the six 2m * 3m infrared targets before and after correction can be seen in Table 4 below.

[0126] Table 4

[0127]

[0128] Figure 12 In (a) of [reference], it shows a schematic diagram of the infrared image of six infrared targets before correction. Figure 12 In (b) of [reference], it shows a schematic diagram of the infrared image of six infrared targets after correction. Figure 13 In (a) of [reference], it provides a schematic diagram of the two-dimensional infrared image of the six targets after correction. Figure 13 In (b) of [reference], it provides a schematic diagram of the three-dimensional infrared image of the six targets after correction.

[0129] It can be seen that the temperature uniformity correction process of a single infrared target can be applied to the temperature uniformity correction of multiple infrared targets. And after the multiple infrared targets are corrected, the temperature uniformity shows good performance, and it is a relatively good infrared radiation source.

[0130] In another embodiment, as Figure 14 shown, a method for infrared target temperature uniformity correction and temperature control based on temperature characteristics is provided. Taking the application of this method to the controller of the infrared target as an example, it includes the following steps:

[0131] Step S1402, at each temperature, based on the initial grayscale matrix corresponding to each temperature, perform temperature uniformity correction on the infrared target to obtain the corrected grayscale matrix of the infrared target at each temperature.

[0132] Step S1404, according to the initial grayscale matrix and the corrected grayscale matrix corresponding to each temperature, determine the grayscale fitting coefficient matrix corresponding to each temperature.

[0133] Step S1406: Construct a mapping model based on each temperature and the gray-scale fitting coefficient matrix corresponding to each temperature; the mapping model represents the mapping relationship between the temperature and the gray-scale fitting coefficient matrix.

[0134] Step S1408: Determine the target temperature that the infrared target needs to maintain. Based on the corrected gray-scale matrix corresponding to the target temperature, control the infrared target to generate heat, and measure the actual temperature of the infrared target through a temperature sensor.

[0135] Step S1410: When the temperature difference between the target temperature and the actual temperature is greater than or equal to the preset deviation threshold, determine the gray-scale deviation matrix according to the corrected gray-scale matrix corresponding to the target temperature and the gray-scale matrix corresponding to the actual temperature.

[0136] Step S1412: Based on the mapping model, determine the gray-scale fitting coefficient matrix for the target temperature.

[0137] Step S1414: Use the gray-scale fitting coefficient matrix to adjust the gray-scale deviation matrix to obtain the adjustment information for the corrected gray-scale matrix corresponding to the target temperature.

[0138] Step S1416: Use the adjustment information to adjust the corrected gray-scale matrix corresponding to the target temperature to obtain the adjusted gray-scale matrix corresponding to the target temperature.

[0139] Step S1418: Take the adjusted gray-scale matrix corresponding to the target temperature as the new corrected gray-scale matrix corresponding to the target temperature, and return to the step of controlling the infrared target to generate heat based on the corrected gray-scale matrix corresponding to the target temperature until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold.

[0140] It should be noted that the specific limitations of the above steps can refer to the specific limitations of a method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics described above.

[0141] It should be understood that although the steps in the flowcharts involved in the above-mentioned embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0142] Based on the same inventive concept, an embodiment of the present application further provides a temperature uniformity correction and temperature control device for an infrared target based on temperature characteristics, which is used to implement the temperature uniformity correction and temperature control method for an infrared target based on temperature characteristics involved above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the temperature uniformity correction and temperature control device for an infrared target based on temperature characteristics provided below can refer to the limitations on the temperature uniformity correction and temperature control method for an infrared target based on temperature characteristics in the above text, and will not be repeated here.

[0143] In an exemplary embodiment, as Figure 15 shown, a temperature uniformity correction and temperature control device for an infrared target based on temperature characteristics is provided, including: a temperature uniformity correction module 1502, a temperature measurement module 1504, a temperature determination module 1506, a gray scale adjustment module 1508, and a temperature control module 1510, where:

[0144] The temperature uniformity correction module 1502 is configured to perform temperature uniformity correction on the infrared target based on the initial gray scale matrix corresponding to each temperature at each temperature, and obtain the corrected gray scale matrix of the infrared target at each temperature;

[0145] The temperature measurement module 1504 is configured to determine the target temperature that the infrared target needs to maintain, control the infrared target to generate heat based on the corrected gray scale matrix corresponding to the target temperature, and measure the actual temperature of the infrared target through a temperature sensor;

[0146] The temperature determination module 1506 is configured to determine a gray scale deviation matrix according to the corrected gray scale matrix corresponding to the target temperature and the gray scale matrix corresponding to the actual temperature when the temperature difference between the target temperature and the actual temperature is greater than or equal to a preset deviation threshold;

[0147] The gray scale adjustment module 1508 is configured to adjust the corrected gray scale matrix corresponding to the target temperature based on the gray scale deviation matrix to obtain an adjusted gray scale matrix corresponding to the target temperature;

[0148] The temperature control module 1510 is configured to use the adjusted gray scale matrix corresponding to the target temperature as the corrected gray scale matrix corresponding to the new target temperature, and return to the step of controlling the infrared target to generate heat based on the corrected gray scale matrix corresponding to the target temperature until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold.

[0149] In one embodiment, the temperature uniformity correction module 1502 is specifically configured to, for any temperature, based on the initial gray matrix corresponding to the temperature, control the infrared target to generate heat, and use an infrared thermal imager to obtain an infrared image of the infrared target, and extract an actual temperature matrix from the infrared image; determine the standard deviation of temperature uniformity according to the actual temperature matrix; in the case where the standard deviation of temperature uniformity is greater than or equal to a preset standard deviation threshold, based on a pre-constructed temperature-gray relationship model, determine an actual gray matrix corresponding to the actual temperature matrix; the temperature-gray relationship model represents the corresponding relationship between temperature and gray; use a gray matrix iteration model to iterate the actual gray matrix to obtain an iterated gray matrix corresponding to the actual gray matrix; use the iterated gray matrix as the initial gray matrix, and return to the step of controlling the infrared target to generate heat based on the initial gray matrix corresponding to the temperature until the standard deviation of temperature uniformity is less than the preset standard deviation threshold; use the iterated gray matrix as the corrected gray matrix.

[0150] In one embodiment, the temperature uniformity correction module 1502 is specifically configured to determine a deviation matrix for the current iteration round according to the actual gray matrix and the initial gray matrix; obtain a calibration weight matrix corresponding to the current iteration round, and use the calibration weight matrix corresponding to the current iteration round to adjust the deviation matrix of the current iteration round to obtain adjustment information of the current iteration round for the initial gray matrix; use the adjustment information of the current iteration round for the initial gray matrix to adjust the initial gray matrix to obtain an iterated gray matrix.

[0151] In one embodiment, the calibration weight matrix includes calibration weights for each target position point in the infrared target; the temperature uniformity correction module 1502 is specifically configured to obtain deviation change direction information, deviation change amplitude information, and deviation change trend information corresponding to each target position point in the current iteration round; generate an iteration state vector corresponding to each target position point based on the deviation change direction information, deviation change amplitude information, and deviation change trend information corresponding to each target position point; use the iteration state vector corresponding to each target position point as an index to query the calibration weight matching each target position point in a pre-constructed calibration weight table; generate a calibration weight matrix corresponding to the current iteration round based on the calibration weights matching each target position point.

[0152] In one embodiment, the temperature uniformity correction module 1502 is specifically configured to further determine a gray fitting coefficient matrix corresponding to each temperature according to the initial gray matrix and the corrected gray matrix corresponding to each temperature; construct a mapping model according to each temperature and the gray fitting coefficient matrix corresponding to each temperature; the mapping model represents the mapping relationship between temperature and the gray fitting coefficient matrix.

[0153] In one embodiment, the grayscale adjustment module 1508 is specifically configured to determine a grayscale fitting coefficient matrix for the target temperature based on the mapping model; adjust the grayscale deviation matrix using the grayscale fitting coefficient matrix to obtain adjustment information for the corrected grayscale matrix corresponding to the target temperature; and adjust the corrected grayscale matrix corresponding to the target temperature using the adjustment information to obtain an adjusted grayscale matrix corresponding to the target temperature.

[0154] Each module in the above infrared target temperature uniformity correction and temperature control device based on temperature characteristics can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor in the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form to facilitate the processor to call and execute the operations corresponding to the above respective modules.

[0155] In an exemplary embodiment, a computer device is provided. The computer device can be a server, and its internal structural diagram can be as Figure 16 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store infrared target temperature uniformity correction and temperature control data based on temperature characteristics. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a method for infrared target temperature uniformity correction and temperature control based on temperature characteristics.

[0156] Those skilled in the art can understand that Figure 16 the structure shown in

[0157] In one embodiment, a computer device is provided, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor is caused to execute the steps of the above-mentioned method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics. The steps of the method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics here may be the steps in the method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics in each of the above embodiments.

[0158] In one embodiment, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by the processor, the processor is caused to execute the steps of the above-mentioned method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics. The steps of the method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics here may be the steps in the method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics in each of the above embodiments.

[0159] In one embodiment, a computer program product is provided, which includes a computer program. When the computer program is executed by the processor, the processor is caused to execute the steps of the above-mentioned method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics. The steps of the method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics here may be the steps in the method for correcting the temperature uniformity and controlling the temperature of an infrared target based on temperature characteristics in each of the above embodiments.

[0160] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., and are not limited thereto.

[0161] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0162] The above-described embodiments merely represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for correcting and controlling temperature uniformity of an infrared target based on temperature characteristics, characterized in that: The method comprises: At each temperature, based on the initial grayscale matrix corresponding to each temperature, the infrared target is subjected to temperature uniformity correction to obtain a corrected grayscale matrix of the infrared target at each temperature; Determine the target temperature that the infrared target needs to maintain, control the heating of the infrared target based on the corrected grayscale matrix corresponding to the target temperature, and measure the actual temperature of the infrared target through a temperature sensor; When the temperature difference between the target temperature and the actual temperature is greater than or equal to a preset deviation threshold, determining a grayscale deviation matrix according to a corrected grayscale matrix corresponding to the target temperature and a grayscale matrix corresponding to the actual temperature; Based on the grayscale deviation matrix, adjusting the corrected grayscale matrix corresponding to the target temperature to obtain an adjusted grayscale matrix corresponding to the target temperature; The adjusted grayscale matrix corresponding to the target temperature is used as the new corrected grayscale matrix corresponding to the target temperature, and the corrected grayscale matrix based on the target temperature is returned to control the heating of the infrared target until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold.

2. The method according to claim 1, characterized in that The step of performing temperature uniformity correction on the infrared target based on the initial grayscale matrix corresponding to each of the temperatures to obtain a corrected grayscale matrix of the infrared target at each of the temperatures includes: For any of the temperatures, based on the initial grayscale matrix corresponding to the temperature, the infrared target is controlled to generate heat, and an infrared image of the infrared target is acquired using an infrared thermal imager, and an actual temperature matrix is ​​extracted from the infrared image; Determining a temperature uniformity standard deviation according to the actual temperature matrix; In the case where the temperature uniformity standard deviation is greater than or equal to a preset standard deviation threshold, an actual grayscale matrix corresponding to the actual temperature matrix is ​​determined based on a pre-constructed temperature grayscale relationship model; the temperature grayscale relationship model characterizes the corresponding relationship between the temperature and the grayscale; Iterating the actual grayscale matrix using a grayscale matrix iteration model to obtain an iterated grayscale matrix corresponding to the actual grayscale matrix; The step of using the iterated grayscale matrix as the initial grayscale matrix and returning the initial grayscale matrix corresponding to the temperature to control the heating of the infrared target until the temperature uniformity standard deviation is less than the preset standard deviation threshold; The iterated grayscale matrix is ​​used as the corrected grayscale matrix.

3. The method according to claim 2, characterized in that The step of iterating the actual grayscale matrix using a grayscale matrix iteration model to obtain an iterated grayscale matrix corresponding to the actual grayscale matrix includes: Determine a deviation matrix for a current iteration round according to the actual grayscale matrix and the initial grayscale matrix; Acquire a calibration weight matrix corresponding to the current iteration round, and use the calibration weight matrix corresponding to the current iteration round to adjust the deviation matrix of the current iteration round to obtain adjustment information of the current iteration round for the initial grayscale matrix; The initial grayscale matrix is ​​adjusted by using the adjustment information of the current iteration round for the initial grayscale matrix to obtain the iterated grayscale matrix.

4. The method according to claim 3, characterized in that The calibration weight matrix includes calibration weights for each target position point in the infrared target; and obtaining the calibration weight matrix corresponding to the current iteration round includes: Obtaining deviation change direction information, deviation change amplitude information and deviation change trend information corresponding to each target position point in the current iteration round; Based on the deviation change direction information, the deviation change amplitude information and the deviation change trend information corresponding to each of the target position points, an iterative state vector corresponding to each of the target position points is generated; Using the iterated state vector corresponding to each of the target position points as an index, querying the calibration weight matching each of the target position points in a pre-constructed calibration weight table; Based on the calibration weights matched with each of the target position points, a calibration weight matrix corresponding to the current iteration round is generated.

5. The method according to claim 1, characterized in that After the step of performing temperature uniformity correction on the infrared target based on the initial grayscale matrix corresponding to each of the temperatures to obtain a corrected grayscale matrix of the infrared target at each of the temperatures, the method further includes: Determine a grayscale fitting coefficient matrix corresponding to each temperature according to an initial grayscale matrix and a corrected grayscale matrix corresponding to each temperature; A mapping model is constructed according to each of the temperatures and the grayscale fitting coefficient matrix corresponding to each of the temperatures; the mapping model represents the mapping relationship between the temperature and the grayscale fitting coefficient matrix.

6. The method according to claim 5, characterized in that The step of adjusting the corrected grayscale matrix corresponding to the target temperature based on the grayscale deviation matrix to obtain the adjusted grayscale matrix corresponding to the target temperature includes: Based on the mapping model, determining a grayscale fitting coefficient matrix for the target temperature; The grayscale deviation matrix is ​​adjusted using the grayscale fitting coefficient matrix to obtain adjustment information of the corrected grayscale matrix corresponding to the target temperature; The adjusted grayscale matrix corresponding to the target temperature is adjusted using the adjustment information to obtain an adjusted grayscale matrix corresponding to the target temperature.

7. An infrared target temperature uniformity correction and temperature control device based on temperature characteristics, characterized in that: The device comprises: A temperature uniformity correction module is used to perform temperature uniformity correction on the infrared target at each temperature based on the initial grayscale matrix corresponding to each temperature, so as to obtain a corrected grayscale matrix of the infrared target at each temperature; A temperature measurement module is used to determine the target temperature that the infrared target needs to maintain, control the heating of the infrared target based on the corrected grayscale matrix corresponding to the target temperature, and measure the actual temperature of the infrared target through a temperature sensor; a temperature determination module, configured to determine a grayscale deviation matrix according to a corrected grayscale matrix corresponding to the target temperature and a grayscale matrix corresponding to the actual temperature when a temperature difference between the target temperature and the actual temperature is greater than or equal to a preset deviation threshold; A grayscale adjustment module, configured to adjust the corrected grayscale matrix corresponding to the target temperature based on the grayscale deviation matrix to obtain an adjusted grayscale matrix corresponding to the target temperature; A temperature control module is used to use the adjusted grayscale matrix corresponding to the target temperature as the new corrected grayscale matrix corresponding to the target temperature, and return the corrected grayscale matrix based on the target temperature to control the heating of the infrared target until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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