Infrared target temperature uniformity correction and temperature control method based on temperature characteristics

Abstract

The invention relates to an infrared target temperature uniformity correction and temperature control method and device based on temperature characteristics, computer equipment, a storage medium and a computer program product. The method comprises the following steps: performing temperature uniformity correction on an infrared target to obtain a corrected gray matrix at each temperature; controlling the infrared target to heat based on the corrected gray matrix of the target temperature; when the temperature difference between the target temperature and the actual temperature is larger than or equal to a preset deviation threshold value, a gray scale deviation matrix is determined according to the corrected gray scale matrix corresponding to the target temperature and the gray scale matrix corresponding to the actual temperature; adjusting the corrected gray scale matrix based on the gray scale deviation matrix to obtain an adjusted gray scale matrix; and taking the adjusted gray matrix as a new corrected gray matrix corresponding to the target temperature, and returning to the step of controlling the heating of the infrared target based on the corrected gray matrix of the target temperature until the temperature difference is smaller than a preset deviation threshold value. By adopting the method, the temperature of the infrared target can be accurately and stably controlled.

Description

Technical Field

[0001] The present application relates to the field of infrared target technology, and in particular to a method, device, computer equipment, storage medium and computer program product for correcting and controlling temperature uniformity of an infrared target based on temperature characteristics. Background Art

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

[0003] In the prior art, if the surface temperature of the infrared target is uneven, such as the temperature in the middle is high and the temperature at the edge is low, then when the infrared device is used for measurement, the readings at different locations will be different, resulting in inaccurate calibration. When the temperature of the infrared target needs to be maintained at 50°C, if the system fluctuates greatly, the actual temperature of the infrared target may vary between 48 and 52, which can easily affect the reliability of the measurement results. In addition, the temperature control system of the infrared target in the prior art has reduced temperature control performance in complex environments (such as wind speed changes) and lacks adaptability. For example, it is impossible to 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 it is impossible to accurately perform temperature uniformity correction and temperature stability control on the infrared target. Summary of the invention

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

[0006] A temperature uniformity correction and temperature control method for an infrared target based on temperature characteristics, the method comprising: at each temperature, based on an initial grayscale matrix corresponding to each temperature, performing temperature uniformity correction on the infrared target to obtain a corrected grayscale matrix of the infrared target at each temperature; determining a target temperature that the infrared target needs to maintain, controlling the heating of the infrared target based on the corrected grayscale matrix corresponding to the target temperature, and measuring 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 based on the corrected grayscale matrix corresponding to the target temperature and the grayscale matrix corresponding to the actual temperature; adjusting 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; using the adjusted grayscale matrix corresponding to the target temperature as a new corrected grayscale matrix corresponding to the target temperature, and returning to the step of controlling the heating of the infrared target based on the corrected grayscale 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 of the embodiments, based on the initial grayscale matrix corresponding to each temperature, the infrared target is corrected for temperature uniformity to obtain a corrected grayscale matrix of the infrared target at each temperature, including: for any temperature, 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; based on the actual temperature matrix, the temperature uniformity standard deviation is determined; when the temperature uniformity standard deviation is greater than or equal to a 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 correspondence 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 step of controlling the heating of the infrared target based on the initial grayscale matrix corresponding to the temperature is returned 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.

[0008] In one of the embodiments, a grayscale matrix iteration model is used to iterate an actual grayscale matrix to obtain an iterated grayscale matrix corresponding to the actual grayscale matrix, including: determining a deviation matrix for a current iteration round based on the actual grayscale matrix and an 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 initial grayscale matrix for the current iteration round; adjusting the initial grayscale matrix using the adjustment information for the initial grayscale matrix for the current iteration round to obtain an iterated grayscale matrix.

[0009] In one of the embodiments, the calibration weight matrix includes calibration weights for each target position point in the infrared target; 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; generating 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; using the iteration state vector corresponding to each target position point as an index, querying the calibration weight matching each target position point in a pre-constructed calibration weight table; generating the calibration weight matrix corresponding to the current iteration round based on the calibration weight matching each target position point.

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

[0011] In one of the embodiments, based on the grayscale deviation matrix, the corrected grayscale matrix corresponding to the target temperature is adjusted to obtain the adjusted grayscale matrix corresponding to the target temperature, including: determining the grayscale fitting coefficient matrix for the target temperature based on the mapping model; adjusting the grayscale deviation matrix using the grayscale fitting coefficient matrix to obtain adjustment information of the corrected grayscale matrix corresponding to the target temperature; adjusting the corrected grayscale matrix corresponding to the target temperature using the adjustment information to obtain the adjusted grayscale matrix corresponding to the target temperature.

[0012] A temperature uniformity correction and temperature control device for an infrared target based on temperature characteristics, the device comprises: a temperature uniformity correction module, used for performing temperature uniformity correction on the infrared target at each temperature based on an 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, used for determining a target temperature to be maintained by the infrared target, controlling the heating of the infrared target based on a corrected grayscale matrix corresponding to the target temperature, and measuring the actual temperature of the infrared target through a temperature sensor; a temperature determination module, used for determining a grayscale deviation matrix based on a corrected grayscale matrix corresponding to the target temperature and a grayscale 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 grayscale adjustment module, used for adjusting the corrected grayscale matrix corresponding to the target temperature based on the grayscale deviation matrix, so as to obtain an adjusted grayscale matrix corresponding to the target temperature; and a temperature control module, used for taking the adjusted grayscale matrix corresponding to the target temperature as a new corrected grayscale matrix corresponding to the target temperature, and returning to a step of controlling the heating of the infrared target based on the corrected grayscale 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, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0014] A computer-readable storage medium stores a computer program, which implements the steps of the above method when executed by a processor.

[0015] A computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0016] The above-mentioned infrared target temperature uniformity correction and temperature control method, device, computer equipment, storage medium and computer program product based on temperature characteristics, performs temperature uniformity correction on the infrared target at each temperature based on the initial grayscale matrix corresponding to each temperature to obtain the corrected grayscale matrix of the infrared target at each temperature; determines the target temperature that the infrared target needs to maintain, controls the heating of the infrared target based on the corrected grayscale matrix corresponding to the target temperature, and measures 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, determines the grayscale deviation matrix based on the corrected grayscale matrix corresponding to the target temperature and the grayscale matrix corresponding to the actual temperature; adjusts 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; uses the adjusted grayscale matrix corresponding to the target temperature as the corrected grayscale matrix corresponding to the new target temperature Grayscale matrix, and returns the corrected grayscale matrix corresponding to the target temperature, and controls the heating step of the infrared target until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold; in this way, the infrared target can be firstly corrected for temperature uniformity to obtain the corrected grayscale matrix of the infrared target at each temperature. After completing the temperature uniformity correction, if the temperature of the infrared target needs to be maintained at the target temperature, the correction of the grayscale 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 grayscale deviation matrix determined based on the corrected grayscale matrix corresponding to the target temperature and the grayscale matrix corresponding to the actual temperature can be quickly corrected to the corrected grayscale matrix of the target temperature, so that the temperature of the infrared target can be accurately controlled near the target temperature, thereby improving the temperature stability of the infrared target and solving the problem that the temperature of the infrared target cannot be accurately controlled and the temperature stability of the infrared target cannot be maintained in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 The figure is a flow chart of a method for correcting and controlling temperature uniformity of an infrared target based on temperature characteristics in one embodiment;

[0019] Figure 2A schematic diagram of a temperature uniformity correction process of an infrared target in one embodiment;

[0020] Figure 3 A schematic diagram of a temperature control process of an infrared target in one embodiment;

[0021] Figure 4 A calibration principle of an infrared target in one embodiment;

[0022] Figure 5 is a schematic diagram of the relationship between an input grayscale and an average temperature of an infrared target in one embodiment;

[0023] Figure 6 A schematic diagram of the relationship between an input grayscale and an increased temperature of an infrared target in one embodiment;

[0024] Figure 7 A temperature uniformity comparison diagram before and after correction in an embodiment;

[0025] Figure 8 It is a schematic diagram of the frequency distribution of the temperature values ​​of the infrared target before and after correction in one embodiment;

[0026] Fig. 9 It is a schematic diagram comparing the pixel temperature uniformity in the X-axis direction and the Y-axis direction of the infrared target before and after correction in one embodiment;

[0027] Fig.10 is a three-dimensional scatter plot corresponding to the grayscale fitting coefficient matrix at different grayscales in one embodiment;

[0028] Fig.11 Schematic diagram of the corresponding relationship between temperature, grayscale and grayscale fitting coefficient in one embodiment;

[0029] Fig.12 This is a schematic diagram of infrared images of six targets before correction in one embodiment;

[0030] Fig.13 A schematic diagram of a three-dimensional infrared image of six targets in one embodiment;

[0031] Fig.14 It is a schematic flow chart of a method for correcting and controlling temperature uniformity of an infrared target based on temperature characteristics in another embodiment;

[0032] Fig.15 It is a structural block diagram of a temperature uniformity correction and temperature control device for an infrared target based on temperature characteristics in one embodiment;

[0033] Fig.16 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is 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 in the embodiment of the present application can be applied to the controller of the infrared target. The infrared target includes a plurality of heating units arranged in an array plate, the plurality of heating units of the infrared target are connected to the output end of the power supply circuit, the control end of the power supply circuit is connected to the controller, and 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, Figure 1 As shown, a method for correcting and controlling the temperature uniformity of an infrared target based on temperature characteristics is provided, and the method is described by taking the application of the method to the controller of the infrared target as an example, including the following steps S102 to S110. Among them:

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

[0038] Among them, each temperature can be a 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] The initial grayscale matrix corresponding to each temperature may be a grayscale matrix corresponding to each temperature that has not been corrected for temperature uniformity.

[0040] The corrected grayscale matrix of the infrared target at each temperature may be a grayscale matrix obtained by performing temperature uniformity correction on the initial grayscale matrix of the infrared target at different temperatures.

[0041] Optionally, the controller controls the infrared target to generate heat at each temperature based on an initial grayscale matrix corresponding to each temperature, thereby performing temperature uniformity correction on the infrared target to obtain a corrected grayscale matrix of the infrared target at each temperature.

[0042] Step S104, determining the target temperature that the infrared target needs to maintain, controlling the infrared target to generate heat based on the corrected grayscale matrix corresponding to the target temperature, and measuring the actual temperature of the infrared target through a temperature sensor.

[0043] Here, the target temperature can be represented by 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 stability control of the infrared target is performed. 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, step S102 performs temperature uniformity correction on the infrared target at temperatures of 25°C, 27.5°C, and 30°C, and 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 grayscale values ​​of each element in the initial grayscale matrix corresponding to each temperature can be the same, that is, the grayscale values ​​of each element in the initial grayscale matrix of each temperature can all be the grayscale values ​​corresponding to each temperature, while the grayscale values ​​of each element in the corrected grayscale matrix corresponding to each temperature can be different, that is, the grayscale values ​​of each element in the corrected grayscale matrix corresponding to each temperature are not necessarily the grayscale values ​​corresponding to each temperature.

[0046] The actual temperature can be obtained by controlling the infrared target to heat according to the corrected grayscale matrix corresponding to the target temperature T, and measuring the temperature of the infrared target with a temperature sensor after the temperature stabilizes. .

[0047] In practical applications, when the infrared target is heated according to the corrected grayscale matrix corresponding to the target temperature T, the actual temperature of the infrared target measured is There may be a difference with the preset temperature T. If the actual temperature of the infrared target needs to be If the temperature is controlled within a certain range, the temperature of the infrared target can be accurately and stably controlled by adopting the technical solution of the present application.

[0048] Optionally, when it is determined that the temperature of the infrared target needs to be maintained at a target temperature T, the corrected grayscale matrix corresponding to the target temperature T is determined: , the corrected grayscale matrix corresponding to the target temperature T Input to the host computer, the host computer will convert the corrected gray matrix corresponding to the target temperature T The infrared target controller controls the infrared target to adjust the grayscale matrix according to the target temperature T. Heat is generated, and after the heat is stable, the actual temperature of the infrared target is measured using a temperature sensor .

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

[0050] The temperature difference can be the target temperature T and the actual temperature The temperature difference between .

[0051] The preset deviation threshold may be a threshold value pre-set 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 relatively stable near the target temperature T, thereby achieving the effect of stably controlling the temperature of the infrared target at the target temperature T. In practical applications, the preset deviation threshold may be set to 0.2°C, or it may be freely set according to the actual temperature stability requirements.

[0052] The grayscale deviation matrix may be a matrix obtained by subtracting a corrected grayscale matrix corresponding to the target temperature from a grayscale matrix corresponding to the actual temperature.

[0053] Optionally, the controller can be configured to detect the actual temperature of the infrared target. and the target temperature T, determine the temperature difference , then, the temperature deviation When the deviation is greater than or equal to the preset threshold of 0.2°C, the gray matrix corresponding to the target temperature T is used. With actual temperature The corresponding grayscale matrix , determine the grayscale deviation matrix, the grayscale deviation matrix can be expressed as - .

[0054] In practical applications, if the temperature difference If it is less than the preset deviation threshold of 0.2°C, it means that the temperature of the infrared target remains 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, adjusting 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.

[0056] The adjusted grayscale matrix corresponding to the target temperature may be the corrected grayscale matrix corresponding to the target temperature T. The matrix obtained after adjustment, the adjusted grayscale matrix corresponding to the target temperature can be expressed as .

[0057] Optionally, the controller is based on a grayscale deviation matrix - , the corrected grayscale matrix corresponding to the target temperature T Adjust to get the adjusted grayscale matrix corresponding to the target temperature T .

[0058] Step S110, taking the adjusted grayscale matrix corresponding to the target temperature as the corrected grayscale matrix corresponding to the new target temperature, and returning to the step of controlling the heating of the infrared target based on the corrected grayscale 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 sets the adjusted grayscale matrix corresponding to the target temperature T As the corrected grayscale matrix at the new target temperature T, the process returns to step S102 until the target temperature T is equal to the actual temperature. Temperature difference Less than the preset deviation threshold of 0.2°C.

[0060] In the above-mentioned infrared target temperature uniformity correction and temperature control method based on temperature characteristics, the infrared target is subjected to temperature uniformity correction at each temperature based on the initial grayscale matrix corresponding to each temperature to obtain the corrected grayscale matrix of the infrared target at each temperature; the target temperature that the infrared target needs to maintain is determined, and the heating of the infrared target is controlled based on the corrected grayscale matrix corresponding to the target temperature, 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 the preset deviation threshold, the grayscale deviation matrix is ​​determined based on the corrected grayscale matrix corresponding to the target temperature and the grayscale matrix corresponding to the actual temperature; based on the grayscale deviation matrix, the corrected grayscale matrix corresponding to the target temperature is adjusted to obtain the adjusted grayscale matrix corresponding to the target temperature; the adjusted grayscale matrix corresponding to the target temperature is used as the corrected grayscale matrix corresponding to the new target temperature, and the grayscale matrix corresponding to the actual temperature is returned. The corrected grayscale matrix corresponding to the target temperature controls the heating step of the infrared target until the temperature difference between the target temperature and the actual temperature is less than the preset deviation threshold. In this way, the infrared target can be firstly corrected for temperature uniformity to obtain the corrected grayscale matrix of the infrared target at each temperature. After completing the temperature uniformity correction, if it is necessary to maintain the temperature of the infrared target at the target temperature, the correction of the grayscale 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. The corrected grayscale matrix of the target temperature can be quickly corrected based on the grayscale deviation matrix determined based on the corrected grayscale matrix corresponding to the target temperature and the grayscale matrix corresponding to the actual temperature. The temperature of the infrared target can be accurately controlled near the target temperature, the temperature stability of the infrared target is improved, and the problem that the temperature of the infrared target cannot be accurately controlled and the temperature stability of the infrared target cannot be maintained in the prior art is solved.

[0061] In an exemplary embodiment, based on the initial grayscale matrix corresponding to each temperature, the infrared target is subjected to temperature uniformity correction to obtain the corrected grayscale matrix of the infrared target at each temperature, including: for any temperature, 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; based on the actual temperature matrix, the temperature uniformity standard deviation is determined; when the temperature uniformity standard deviation is greater than or equal to a 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 correspondence 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 step of controlling the infrared target heating based on the initial grayscale matrix corresponding to the temperature is returned 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.

[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 an 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 temperature uniformity standard deviation 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, is the average value of the actual temperature of all target locations.

[0066] The preset standard deviation threshold may be a threshold value pre-set for the temperature uniformity standard deviation. When the temperature uniformity standard deviation 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 temperature uniformity standard deviation 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 may be set to 0.4, or it may be freely set according to actual temperature uniformity requirements.

[0067] The pre-built 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 gray matrix iteration model can be expressed as:

[0069] ,

[0070] In the formula, =DN, DN is the uniform 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 , the actual gray 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, a grayscale matrix iteration model is used to iterate the actual grayscale matrix to obtain an iterated grayscale matrix corresponding to the actual grayscale matrix, including: determining the deviation matrix of the current iteration round based on the actual grayscale matrix and the initial grayscale matrix; obtaining the calibration weight matrix corresponding to the current iteration round, and adjusting the deviation matrix of the current iteration round using the calibration weight matrix corresponding to the current iteration round to obtain adjustment information for the initial grayscale matrix for the current iteration round; adjusting the initial grayscale matrix using the adjustment information for the initial grayscale matrix for the current iteration round to obtain an iterated grayscale matrix.

[0075] The current iteration round may be the iteration round when the gray matrix iteration model is used for iteration.

[0076] The deviation matrix of the current iteration round may be a deviation matrix between an actual grayscale matrix and an initial grayscale matrix in the current iteration round.

[0077] Among them, the calibration weight matrix corresponding to the current iteration round can be the gray matrix iteration model under the current iteration round The calibration weight matrix ε in .

[0078] The adjustment information of the initial grayscale matrix for the current iteration round may refer to the calibration weight matrix ε multiplied by the deviation matrix of the current iteration round: The information obtained can be expressed as .

[0079] Optionally, the controller can be configured to calculate the grayscale matrix according to the actual grayscale matrix. and the initial grayscale matrix , determine the deviation matrix of the current iteration round Then, obtain the calibration weight matrix ε corresponding to the current iteration round, and use the calibration weight matrix ε corresponding to the current iteration round to calculate the deviation matrix of the current iteration round Make adjustments to get the adjustment information of the current iteration round , and then use the adjustment information of the current iteration round For the initial gray matrix Make adjustments to obtain the grayscale matrix after iteration.

[0080] In this embodiment, the deviation matrix of the current iteration round is determined based on the actual grayscale matrix and the initial grayscale matrix; the calibration weight matrix corresponding to the current iteration round is obtained, and the calibration weight matrix corresponding to the current iteration round is used to adjust the deviation matrix of the current iteration round to obtain the adjustment information of the initial grayscale matrix for the current iteration round; the initial grayscale matrix is ​​adjusted using the adjustment information of the current iteration round for the initial grayscale matrix to obtain the grayscale matrix after iteration; in this way, the initial grayscale matrix can be iterated quickly, which is conducive to efficiently correcting the temperature uniformity of the infrared target.

[0081] In fact, the calibration weight matrix ε of different iteration rounds is different. For the determination of the calibration weight matrix ε, reference may be made to the detailed description of the next embodiment.

[0082] In an exemplary embodiment, the calibration weight matrix includes calibration weights for each target position point in the infrared target; 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; generating 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; using the iteration state vector corresponding to each target position point as an index, querying the calibration weight matching each target position point in a pre-constructed calibration weight table; generating the calibration weight matrix corresponding to the current iteration round based on the calibration weight matching each target position point.

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

[0084] Among them, the deviation change direction information can refer to the deviation change direction pattern. In practical applications, the deviation change direction patterns can be divided into four types, namely, continuous same-direction changes, double alternating changes, single alternating changes and random fluctuation changes. Continuous same-direction changes refer to the situation where the number of continuous same-direction changes is greater than or equal to 3, double alternating changes refer to the "positive-negative-positive-negative" situation, single alternating changes refer to the situation where reversal occurs after two consecutive same-direction changes, and random fluctuation changes refer to the situation where none of the above three deviation change direction patterns are present.

[0085] The deviation change amplitude information may refer to deviation change amplitude classification. In practical applications, the deviation change amplitude may 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 a deviation change trend determined based on the three most recent deviation changes. In actual applications, it can be calculated and determined based on the slope (i.e., deviation value) of the three most recent adjustments. The calculation formula is (|deviation value n-2|+|deviation value n-1|+|deviation value n|) / 3, where 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 in which the state vector is located includes thirty-six fixed states. The number of fixed state types is calculated as follows: 36 fixed states = 4 types of deviation change direction × 3 types of deviation amplitude × 3 types of deviation change trend = 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] In order to facilitate the understanding of those skilled in the art, the following provides a 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 frequency of occurrence of each iterative state vector and control the sensitivity; Step 2: Coefficient boundary setting. Specifically, determine the weight range (i.e., correction coefficient range) according to physical constraints, with the lower limit set to 0.5 (to prevent complete loss of control), and the upper limit set to 1.5 (to avoid actuator saturation); Step 3: Artificial experience filling. Specifically, refer to the classic control rule Bang-Bang control idea (for high-risk states, such as "single alternation + large amplitude + acceleration", use the limit value) or PID tuning experience (intermediate frequency state weight ≈1.0~1.1, close to the Ziegler-Nichols parameter); Step 4: Consistency verification. Specifically, ensure that the weight changes of adjacent states are smooth.

[0092] The following also provides an exemplary design example of a 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, "Uniform": 0.7, "Deceleration": 0.8},"Medium": {"Acceleration": 0.7, "Uniform": 0.8, "Deceleration": 0.9},"Small": {"Acceleration": 0.9, "Uniform": 1.0, "Deceleration":1.0}},

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

[0096] "Random Fluctuation": { "Large": {"Acceleration": 1.0, "Uniform Speed": 1.0, "Deceleration": 1.0},"Medium": {"Acceleration": 1.0, "Uniform Speed": 1.0, "Deceleration": 1.0},"Small": {"Acceleration": 1.0, "Uniform 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 pattern of the latest 4 iteration rounds, the deviation change amplitude level of the current iteration round and the deviation change trend of the latest 3 iteration rounds corresponding to each target position point in the current iteration round, and then, based on the deviation change direction pattern of the latest 4 iteration rounds, the deviation change amplitude level of the current iteration round and the deviation change trend of the latest 3 iteration rounds corresponding to each target position point, generate the iteration state vector corresponding to each target position point, and then, 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 the pre-constructed calibration weight table, and finally generate the correction coefficient matrix corresponding to the current iteration round based on the calibration weight matching each target position point.

[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, an iteration state vector corresponding to each target position point is generated; using the iteration state vector corresponding to each target position point as an index, a calibration weight matching each target position point is queried in a pre-constructed calibration weight table; based on the calibration weight matching each target position point, a calibration weight matrix corresponding to the current iteration round is generated; in this way, the information of the three dimensions of deviation change direction information, deviation change amplitude information and deviation change trend information can be integrated to construct a high-resolution iteration state vector, thereby achieving an optimized 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 grayscale matrix corresponding to each temperature to obtain the corrected grayscale matrix of the infrared target at each temperature, the method also includes: determining the grayscale fitting coefficient matrix corresponding to each temperature according to the initial grayscale matrix and the corrected grayscale matrix corresponding to each temperature; constructing a mapping model according to each temperature and the grayscale fitting coefficient matrix corresponding to each temperature; the mapping model characterizes the mapping relationship between the temperature and the grayscale fitting coefficient matrix.

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

[0101] Optionally, the controller calculates the grayscale fitting coefficient matrix corresponding to each temperature based on the initial grayscale matrix and the corrected grayscale matrix corresponding to each temperature. Finally, based on each temperature and the grayscale fitting coefficient matrix corresponding to each temperature, a mapping model characterizing the mapping relationship between the temperature and the grayscale fitting coefficient matrix is ​​constructed.

[0102] In this embodiment, the grayscale fitting coefficient matrix corresponding to each temperature is determined according to the initial grayscale matrix and the corrected grayscale matrix corresponding to each temperature; a mapping model is constructed according to each temperature and the grayscale fitting coefficient matrix corresponding to each temperature; the mapping model characterizes the mapping relationship between the temperature and the grayscale fitting coefficient matrix; in this way, a mapping model that characterizes the mapping relationship between the temperature and the grayscale fitting coefficient matrix can be accurately constructed, and when the temperature stability control of the infrared target is subsequently performed and the grayscale matrix of the target temperature needs to be adjusted, the grayscale 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 grayscale deviation matrix, the corrected grayscale matrix corresponding to the target temperature is adjusted to obtain the adjusted grayscale matrix corresponding to the target temperature, including: determining the grayscale fitting coefficient matrix for the target temperature based on the mapping model; adjusting the grayscale deviation matrix using the grayscale fitting coefficient matrix to obtain adjustment information of the corrected grayscale matrix corresponding to the target temperature; adjusting the corrected grayscale matrix corresponding to the target temperature using the adjustment information to obtain the adjusted grayscale matrix corresponding to the target temperature.

[0104] The adjustment information of the grayscale matrix for the target temperature may include the amplitude required to adjust each matrix element (corresponding to each target position point) in the grayscale matrix corresponding to the target temperature T. In this embodiment, the adjustment information of the grayscale matrix for the target temperature may be expressed as: , = Grayscale fitting coefficient matrix * Grayscale deviation matrix .

[0105] Optionally, the controller determines the grayscale fitting coefficient matrix to be used when the infrared target is at the target temperature T based on a pre-constructed mapping model of the temperature and grayscale fitting coefficient matrix. , then, the grayscale fitting coefficient matrix is ​​used Grayscale deviation matrix Adjust the grayscale matrix for the target temperature T to obtain the adjustment amplitude matrix , then, the grayscale matrix corresponding to the target temperature T Based on the adjustment matrix , get the adjusted grayscale matrix corresponding to the target temperature T , It can be expressed as:

[0106] .

[0107] In this embodiment, the grayscale fitting coefficient matrix for the target temperature is determined based on the mapping model; the grayscale fitting coefficient matrix is ​​used to adjust the grayscale deviation matrix to obtain adjustment information of the corrected grayscale matrix corresponding to the target temperature; the adjustment information is used to adjust the corrected grayscale matrix corresponding to the target temperature to obtain the adjusted grayscale matrix corresponding to the target temperature; in this way, based on the pre-constructed mapping model of temperature and grayscale fitting coefficient matrix, the grayscale fitting coefficient matrix for the target temperature can be quickly determined, and the grayscale deviation matrix is ​​adjusted using the grayscale fitting coefficient matrix of the target temperature, so as to obtain adjustment information of the corrected grayscale matrix for the target temperature, which is conducive to accurately and effectively adjusting the corrected grayscale matrix for the target temperature.

[0108] For the temperature uniformity calibration process of infrared targets, please refer to Figure 2 For the temperature control method of infrared target, please refer to the flowchart shown in Figure 3 Flowchart shown.

[0109] To facilitate understanding by those skilled in the art, the following takes a single 1m*1m infrared target as an example. Figure 2 and Figure 3 The flowchart introduces the temperature uniformity correction process and temperature control process of the infrared target.

[0110] In order to reduce the impact of air convection on the infrared target temperature test, it is necessary to block the infrared target with heat insulation materials during actual calibration. Figure 4 An exemplary calibration principle of an infrared target is provided, which can be used with Figure 3 The flowchart shown in the figure is combined for understanding. Among them, the host computer sends the corrected grayscale matrix corresponding to the target temperature to the infrared target, and the heating array of the infrared target generates heat based on the corrected grayscale matrix corresponding to the target temperature, and generates temperature changes; after the temperature of the heating array of the infrared target is stable, the infrared target is measured by an infrared thermal imager 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 perform steps S106 to S110 in the above embodiment based on the temperature difference between the actual temperature of the infrared target and the target temperature, and finally control the actual temperature of the infrared target within a range close to the target temperature, thereby realizing stable temperature control of the infrared target.

[0111] Before performing temperature uniformity correction on infrared targets at different temperatures, it is necessary to establish the relationship between the infrared target temperature rise and the input grayscale. , where T is the temperature value, DN is the input grayscale, Figure 5 A schematic diagram of the relationship between the input grayscale and the average temperature of the infrared target is provided. Figure 6 A diagram showing the relationship between the input grayscale and the elevated temperature 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 represent the measurement data at different dates and different ambient temperatures.

[0112] When performing temperature uniformity calibration on infrared targets at different temperatures, the specific process can be found in Figure 2 .

[0113] After completing the temperature uniformity calibration for the infrared targets at different temperatures, the temperature stabilization control can be performed on the infrared targets. For the specific process, see Figure 3 .

[0114] The temperature uniformity comparison chart before and after correction can be found in Figure 7 , Figure 7 (a) Figure 7 (c) in the figure are schematic diagrams of the two-dimensional infrared image and the three-dimensional infrared image of the infrared target before correction. Figure 7 (b) Figure 7 (d) in the figure are schematic diagrams of the corrected two-dimensional infrared image and three-dimensional infrared image of the infrared target.

[0115] The frequency distribution of each temperature value before and after correction can be found in Figure 8 , Figure 8 (a) Figure 8 (b) in the figure shows the frequency distribution of each temperature value of the infrared target before and after correction.

[0116] The pixel temperature uniformity in the X-axis direction before and after correction can be seen in Fig. 9 In (a), the pixel temperature uniformity in the Y-axis direction before and after correction can be seen in Fig. 9 (b) in the figure.

[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 the temperature uniformity correction is performed on the infrared target at different temperatures, the grayscale fitting coefficient matrix of the infrared target at different temperatures (i.e. different grayscales) can be obtained. The grayscale fitting coefficient matrix can be expressed as ,about The detailed explanation has been described in the above embodiments.

[0121] Fig.10 The three-dimensional scatter plot corresponding to the grayscale fitting coefficient matrix at different grayscales is shown, and the following Table 3 shows the application results of the grayscale fitting coefficient matrix at different grayscales.

[0122] Table 3

[0123]

[0124] Fig.11 The corresponding relationship between temperature, grayscale and fitting coefficient is shown. The grayscale fitting coefficient includes the fitting coefficient corresponding to each temperature or each grayscale. Fig.11As shown, when the grayscale is a preset grayscale value or a preset temperature value, the fitting coefficient corresponding to the preset grayscale value or the preset temperature value is directly used, and when the grayscale is in the interval of [20,25] or the temperature is in the interval of [25℃, 27.5℃], the fitting coefficient K=(K20+K25) / 2 is used, when the grayscale is in the interval of [25,30] or the temperature is in the interval of [27.55℃, 30℃], the fitting coefficient K=(K25+K30) / 2 is used, and so on.

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

[0126] Table 4

[0127]

[0128] Fig.12 (a) shows a schematic diagram of infrared images of six infrared targets before correction. Fig.12 (b) shows a schematic diagram of the infrared image of 6 infrared targets after correction. Fig.13 (a) in the figure provides a schematic diagram of the corrected two-dimensional infrared image of the six targets. Fig.13 (b) provides a schematic diagram of the corrected three-dimensional infrared image of the six targets.

[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 correction, the temperature uniformity of the multiple infrared targets is good, and they are relatively good infrared radiation sources.

[0130] In another embodiment, Fig.14 As shown, a method for correcting and controlling the temperature uniformity of an infrared target based on temperature characteristics is provided, and the method is described by taking the application of the method to a controller of an infrared target as an example, and includes the following steps:

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

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

[0133] Step S1406, constructing a mapping model according to each temperature and the grayscale fitting coefficient matrix corresponding to each temperature; the mapping model represents the mapping relationship between the temperature and the grayscale fitting coefficient matrix.

[0134] Step S1408, determining the target temperature that the infrared target needs to maintain, controlling the infrared target to generate heat based on the corrected grayscale matrix corresponding to the target temperature, and measuring 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 a preset deviation threshold, a grayscale deviation matrix is ​​determined according to a corrected grayscale matrix corresponding to the target temperature and a grayscale matrix corresponding to the actual temperature.

[0136] Step S1412: Determine the grayscale fitting coefficient matrix for the target temperature based on the mapping model.

[0137] Step S1414, using the grayscale fitting coefficient matrix to adjust the grayscale deviation matrix, to obtain adjustment information of the corrected grayscale matrix corresponding to the target temperature.

[0138] Step S1416, using the adjustment information to adjust the corrected grayscale matrix corresponding to the target temperature, to obtain an adjusted grayscale matrix corresponding to the target temperature.

[0139] Step S1418, taking the adjusted grayscale matrix corresponding to the target temperature as the corrected grayscale matrix corresponding to the new target temperature, and returning to the step of controlling the heating of the infrared target based on the corrected grayscale 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 definition of the above steps can refer to the specific definition of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics mentioned above.

[0141] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, 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 can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0142] Based on the same inventive concept, the embodiment of the present application also provides an infrared target temperature uniformity correction and temperature control device based on temperature characteristics for implementing the infrared target temperature uniformity correction and temperature control method based on temperature characteristics. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations of one or more embodiments of the infrared target temperature uniformity correction and temperature control device based on temperature characteristics provided below can refer to the limitations of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics above, and will not be repeated here.

[0143] In an exemplary embodiment, Fig.15 As shown, a temperature uniformity correction and temperature control device for an infrared target based on temperature characteristics is provided, comprising: a temperature uniformity correction module 1502, a temperature measurement module 1504, a temperature determination module 1506, a grayscale adjustment module 1508 and a temperature control module 1510, wherein:

[0144] The temperature uniformity correction module 1502 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 the corrected grayscale matrix of the infrared target at each temperature;

[0145] The temperature measurement module 1504 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;

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

[0147] A grayscale adjustment module 1508 is used 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;

[0148] The temperature control module 1510 is used to use the adjusted grayscale matrix corresponding to the target temperature as the corrected grayscale matrix corresponding to the new target temperature, and return the corrected grayscale matrix based on the target temperature to control the heating step of the infrared target until the temperature difference between the target temperature and the actual temperature is less than a preset deviation threshold.

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

[0150] In one of the embodiments, the temperature uniformity correction module 1502 is specifically used to determine the deviation matrix of the current iteration round based on the actual grayscale matrix and the initial grayscale matrix; 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 initial grayscale matrix for the current iteration round; use the adjustment information of the current iteration round for the initial grayscale matrix to adjust the initial grayscale matrix to obtain the grayscale matrix after iteration.

[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 used to obtain 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 an 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 weight matching each target position point in a pre-constructed calibration weight table; based on the calibration weight matching each target position point, generate a calibration weight matrix corresponding to the current iteration round.

[0152] In one of the embodiments, the temperature uniformity correction module 1502 is specifically used to determine the grayscale fitting coefficient matrix corresponding to each temperature based on the initial grayscale matrix and the corrected grayscale matrix corresponding to each temperature; construct a mapping model based on each temperature and the grayscale fitting coefficient matrix corresponding to each temperature; the mapping model represents the mapping relationship between the temperature and the grayscale fitting coefficient matrix.

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

[0154] Each module in the above-mentioned infrared target temperature uniformity correction and temperature control device based on temperature characteristics can be fully or partially implemented by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0155] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig.16 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to 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 an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for correcting and controlling the temperature uniformity of an infrared target based on temperature characteristics is implemented.

[0156] Those skilled in the art will understand that Fig.16 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0157] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics. The steps of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics here can be the steps of the infrared target temperature uniformity correction and temperature control method 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 a processor, the processor executes the steps of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics. The steps of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics here can be the steps of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics in each of the above embodiments.

[0159] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the processor executes the steps of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics. The steps of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics here can be the steps of the infrared target temperature uniformity correction and temperature control method based on temperature characteristics in each of the above embodiments.

[0160] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. 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. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0161] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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, they should be considered to be within the scope of this specification.

[0162] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached 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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