Parameter calibration method, temperature measurement method and device of infrared temperature measurement equipment

Abstract

This application provides a parameter calibration method, temperature measurement method, and apparatus for an infrared temperature measuring device, relating to the field of data processing technology. The parameter calibration method for the infrared temperature measuring device includes: acquiring multiple calibration data sets; determining the calibration data corresponding to each device status information from the acquired calibration data sets; for each device status information set, calibrating the temperature measurement correction coefficient of the infrared temperature measuring device based on the calibration data corresponding to that device status information, obtaining the calibrated temperature measurement correction coefficient corresponding to that device status information; and storing each device status information set and its corresponding calibrated temperature measurement correction coefficient in association within the infrared temperature measuring device to complete the calibration of the temperature measurement correction coefficient of the infrared temperature measuring device. This application enables the calibration of the temperature measurement correction coefficient of an infrared temperature measuring device, improving the accuracy of temperature measurement by the infrared temperature measuring device.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a parameter calibration method, temperature measurement method and device for an infrared temperature measurement device. Background Technology

[0002] Currently, infrared temperature measurement equipment has been widely used in many fields. The various temperature measurement parameters obtained when using infrared temperature measurement equipment include, for example, the grayscale data and emissivity of the object being measured, obtained from infrared signal conversion, and the temperature of the infrared temperature measurement equipment itself. These parameters, combined with the temperature correction coefficient (coeff) of the infrared temperature measurement equipment, are used to calculate the measured temperature of the object.

[0003] In related technologies, for an infrared temperature measuring device, a fixed temperature correction coefficient is usually used to calculate the temperature of the object being measured.

[0004] However, the condition of the infrared temperature measuring device itself also affects the temperature measurement. Therefore, using a fixed temperature correction coefficient for temperature calculation will undoubtedly result in low accuracy of the infrared temperature measuring device. Summary of the Invention

[0005] The purpose of this application is to provide a parameter calibration method, a temperature measurement method, and a device for infrared temperature measurement equipment. The specific technical solution is as follows:

[0006] In a first aspect, embodiments of this application provide a parameter calibration method for an infrared temperature measuring device, the method comprising:

[0007] Acquire multiple calibration data points; each calibration data point includes: the actual temperature of a calibration object, and the parameter values ​​of each temperature measurement parameter obtained by measuring the temperature of the calibration object using an infrared thermometer, as well as the equipment status information when measuring the temperature of the calibration object;

[0008] From the acquired multiple calibration data, determine the calibration data corresponding to each device status information; wherein, the calibration data corresponding to each device status information is each calibration data containing that device status information;

[0009] For each device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated based on the calibration data corresponding to the device status information to obtain the calibrated temperature measurement correction coefficient corresponding to the device status information; wherein, the calibration process is used to ensure that the temperature measured based on the calibrated temperature measurement correction coefficient corresponding to the device status information and the parameter values ​​of the temperature measurement parameters in the corresponding calibration data matches the actual temperature in the corresponding calibration data.

[0010] The status information of each device and the corresponding calibrated temperature correction coefficient are stored in the infrared temperature measuring device in association to complete the calibration of the temperature correction coefficient of the infrared temperature measuring device.

[0011] Secondly, embodiments of this application provide a temperature measurement method applied to an infrared temperature measuring device, wherein the infrared temperature measuring device is a device calibrated according to the aforementioned parameter calibration method; the method includes:

[0012] In response to the temperature measurement operation on the target object, the parameter values ​​of each temperature measurement parameter obtained from the temperature measurement of the target object are acquired;

[0013] Obtain the device status information when measuring the temperature of the target object, and use it as the target device status information;

[0014] Based on the status information of each device stored in the infrared temperature measurement device and the corresponding calibrated temperature measurement correction coefficient, the calibrated temperature measurement correction coefficient corresponding to the status information of the target device is determined.

[0015] Based on the obtained parameter values ​​of each temperature measurement parameter and the calibrated temperature measurement correction coefficient corresponding to the target device status information, the temperature of the target object is determined.

[0016] Thirdly, embodiments of this application provide a parameter calibration device for an infrared temperature measurement device, the device comprising:

[0017] The first acquisition module is used to acquire multiple calibration data; each calibration data includes: the actual temperature of a calibration object, and the parameter values ​​of each temperature measurement parameter obtained by measuring the temperature of the calibration object through an infrared temperature measuring device, as well as the device status information when measuring the temperature of the calibration object;

[0018] The first determining module is used to determine the calibration data corresponding to each device status information from the multiple calibration data obtained; wherein, the calibration data corresponding to each device status information is each calibration data containing that device status information;

[0019] The calibration module is used to calibrate the temperature correction coefficient of the infrared thermometer based on the calibration data corresponding to each device status information, so as to obtain the calibrated temperature correction coefficient corresponding to the device status information; wherein, the calibration process is used to ensure that the temperature calculated based on the calibrated temperature correction coefficient corresponding to the device status information and the parameter values ​​of the temperature measurement parameters in the corresponding calibration data matches the actual temperature in the corresponding calibration data.

[0020] The storage module is used to store the status information of each device and the corresponding calibrated temperature correction coefficient in the infrared temperature measuring device in association, so as to complete the calibration of the temperature correction coefficient of the infrared temperature measuring device.

[0021] Fourthly, embodiments of this application provide a temperature measuring device applied to an infrared temperature measuring equipment, wherein the infrared temperature measuring equipment is a device calibrated according to the aforementioned parameter calibration method; the device includes:

[0022] The second acquisition module is used to acquire the parameter values ​​of various temperature measurement parameters obtained from the temperature measurement of the target object in response to the temperature measurement operation of the target object.

[0023] The third acquisition module is used to acquire the device status information when the target object is being measured, as the target device status information.

[0024] The second determining module is used to determine the calibrated temperature correction coefficient corresponding to the target device status information based on the status information of each device stored in the infrared temperature measuring device and the corresponding calibrated temperature correction coefficient.

[0025] The third determining module is used to determine the temperature of the target object based on the parameter values ​​of each obtained temperature measurement parameter and the calibrated temperature measurement correction coefficient corresponding to the target device status information.

[0026] Fifthly, embodiments of this application provide an electronic device, including:

[0027] Memory, used to store computer programs;

[0028] The processor, when executing a program stored in memory, implements the parameter calibration method of any of the infrared temperature measuring devices described above.

[0029] Sixthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements either the parameter calibration method of any of the infrared temperature measuring devices described above, or the temperature measurement method described above.

[0030] This application also provides a computer program product containing instructions that, when run on a computer, cause the computer to execute the parameter calibration method of any of the infrared temperature measuring devices described above, or to implement the temperature measurement method described above.

[0031] Beneficial effects of the embodiments in this application:

[0032] The parameter calibration method for infrared temperature measuring devices provided in this application, after acquiring multiple calibration data, first identifies each calibration data point containing the same device status information, i.e., classifying the multiple calibration data according to the device status information to obtain the calibration data corresponding to each device status information; then, for each device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated based on the corresponding calibration data, resulting in the calibrated temperature measurement correction coefficient for that device status information; each device status information and its corresponding calibrated temperature measurement correction coefficient are stored in association within the infrared temperature measuring device. Through this parameter calibration method, for each device status information, a corresponding calibrated temperature measurement correction coefficient is determined based on the corresponding calibration data, and the device status information and the corresponding calibrated temperature measurement correction coefficient are stored in association. Thus, for the temperature measurement of the infrared temperature measuring device, calibrated temperature measurement correction coefficients corresponding to each device status information can be provided, thereby providing a foundation for improving the accuracy of the infrared temperature measuring device.

[0033] In the temperature measurement method provided in this application, when the infrared thermometer measures the temperature of a target object, it does not directly select a fixed temperature correction coefficient. Instead, it considers the influence of the device status on the temperature measurement, thereby obtaining the device status information of the infrared thermometer at the time of testing as the target device status information, and using the calibrated temperature correction coefficient corresponding to the target device status information to calculate the temperature. Therefore, the temperature measurement method provided in this application considers the influence of the device status on the temperature measurement and selects a matching calibrated temperature correction coefficient for temperature calculation. Thus, compared to using a fixed temperature correction coefficient, it can improve the accuracy of the infrared thermometer.

[0034] Of course, implementing any product or method of this application does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0036] Figure 1 A flowchart illustrating a parameter calibration method for an infrared temperature measurement device provided in this application embodiment;

[0037] Figure 2 A schematic flowchart illustrating a calibration method based on parameter iterative optimization provided in this application embodiment;

[0038] Figure 3 This application provides another schematic flowchart of a parameter calibration method for an infrared temperature measurement device.

[0039] Figure 4 A schematic flowchart of a temperature measurement method provided in an embodiment of this application;

[0040] Figure 5 This is a schematic diagram of the structure of a parameter calibration device for an infrared temperature measurement device provided in an embodiment of this application;

[0041] Figure 6 This is a schematic diagram of the structure of a temperature measuring device provided in an embodiment of this application;

[0042] Figure 7 This is a block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0043] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of this application.

[0044] In related technologies, for infrared temperature measurement devices, there are schemes that can adjust the response rate and temperature adjustment parameters. However, the adjustment process requires pre-calibrating the adjustment range of the response rate and temperature adjustment parameters, and then iterating and optimizing according to a certain step size. When there are many parameters to be adjusted, the time consumed by iterative optimization in these schemes increases significantly. Furthermore, the choice of step size affects the adjustment time and accuracy, requiring certain prior knowledge and human intervention to achieve a certain adjustment time and accuracy.

[0045] Among them, the response rate adjustment parameter is used to optimize the conversion efficiency of infrared temperature measurement equipment for infrared signals of different intensities, ensuring that a stable and identifiable electrical signal can be output in different temperature measurement scenarios (such as scenarios with different temperatures or different radiation sources), thereby obtaining the parameter values ​​of each temperature measurement parameter. The response rate adjustment parameter may include: gain, integration time, bandwidth, etc. The temperature adjustment parameter is a calibration parameter for the accuracy of the temperature measurement result. Its core function is to compensate for the influence of environmental factors or the characteristics of the measured object on the infrared radiation propagation, converting the infrared signal received by the detector of the infrared temperature measurement equipment into the true temperature value. The temperature adjustment parameter may include: emissivity, ambient temperature compensation, distance coefficient, etc.

[0046] In addition, the temperature correction coefficient (coeff) of infrared thermometers can be understood as a specific quantification of temperature regulation parameters, and is a core component of temperature regulation parameters.

[0047] As can be seen, the aforementioned related technologies suffer from time-consuming iterative optimization of the temperature correction coefficient, and the selection of the step size affects the adjustment time and accuracy. Furthermore, the optimized temperature correction coefficient remains a fixed coefficient, failing to consider the impact of equipment status on temperature measurement, which also leads to low accuracy in infrared temperature measurement. Considering that the equipment status itself affects temperature measurement, using a fixed temperature correction coefficient for temperature calculation undoubtedly results in low accuracy. Therefore, this application provides a parameter calibration method, temperature measurement method, and apparatus for infrared temperature measurement.

[0048] The parameter calibration method for an infrared temperature measurement device provided in this application will be introduced first below.

[0049] The parameter calibration method for an infrared temperature measuring device provided in this application can be applied to electronic devices, which can be infrared temperature measuring devices or terminal devices such as mobile phones and computers that communicate with infrared temperature measuring devices. This application does not limit the specific form of the electronic devices. The parameter calibration method for an infrared temperature measuring device provided in this application can be applied to scenarios where the temperature correction coefficient of an infrared temperature measuring device is calibrated before temperature measurement, for example, calibrating a fixed temperature correction coefficient used by an infrared temperature measuring device.

[0050] Alternatively, the execution entity of a parameter calibration method for an infrared temperature measuring device can be a parameter calibration device for the infrared temperature measuring device. For example, a parameter calibration device for an infrared temperature measuring device can be functional software running on a terminal device. In this case, the terminal device communicates with the infrared temperature measuring device, can obtain multiple calibration data from the infrared temperature measuring device, and execute a parameter calibration method for the infrared temperature measuring device. Alternatively, a parameter calibration device for an infrared temperature measuring device can be a functional module of the infrared temperature measuring device. In this case, the parameter calibration device can directly obtain multiple calibration data from the infrared temperature measuring device and execute a parameter calibration method for the infrared temperature measuring device.

[0051] This application provides a parameter calibration method for an infrared temperature measurement device, which may include the following steps:

[0052] Acquire multiple calibration data points; each calibration data point includes: the actual temperature of a calibration object, and the parameter values ​​of each temperature measurement parameter obtained by measuring the temperature of the calibration object using an infrared thermometer, as well as the equipment status information when measuring the temperature of the calibration object;

[0053] From the acquired multiple calibration data, determine the calibration data corresponding to each device status information; wherein, the calibration data corresponding to each device status information is each calibration data containing that device status information;

[0054] For each device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated based on the calibration data corresponding to the device status information to obtain the calibrated temperature measurement correction coefficient corresponding to the device status information; wherein, the calibration process is used to ensure that the temperature measured based on the calibrated temperature measurement correction coefficient corresponding to the device status information and the parameter values ​​of the temperature measurement parameters in the corresponding calibration data matches the actual temperature in the corresponding calibration data.

[0055] The status information of each device and the corresponding calibrated temperature correction coefficient are stored in the infrared temperature measuring device in association to complete the calibration of the temperature correction coefficient of the infrared temperature measuring device.

[0056] The parameter calibration method for infrared temperature measuring devices provided in this application, after acquiring multiple calibration data, first identifies each calibration data point containing the same device status information, i.e., classifying the multiple calibration data according to the device status information to obtain the calibration data corresponding to each device status information; then, for each device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated based on the corresponding calibration data, resulting in the calibrated temperature measurement correction coefficient for that device status information; each device status information and its corresponding calibrated temperature measurement correction coefficient are stored in association within the infrared temperature measuring device. Through this parameter calibration method, for each device status information, a corresponding calibrated temperature measurement correction coefficient is determined based on the corresponding calibration data, and the device status information and the corresponding calibrated temperature measurement correction coefficient are stored in association. Thus, for the temperature measurement of the infrared temperature measuring device, calibrated temperature measurement correction coefficients corresponding to each device status information can be provided, thereby providing a foundation for improving the accuracy of the infrared temperature measuring device.

[0057] The parameter calibration method of an infrared temperature measuring device provided in this application will be described exemplarily below with reference to the accompanying drawings.

[0058] like Figure 1 As shown in the embodiments of this application, a parameter calibration method for an infrared temperature measuring device may include the following steps:

[0059] S101: Acquire multiple calibration data points;

[0060] Each calibration data point includes: the actual temperature of a calibration object, and the parameter values ​​of each temperature measurement parameter obtained by measuring the temperature of the calibration object using an infrared thermometer, as well as the equipment status information when measuring the temperature of the calibration object.

[0061] The parameter calibration method for infrared temperature measuring devices provided in this application can correct the infrared temperature measurement correction coefficient based on the device status itself. First, multiple calibration data points are acquired to calibrate the temperature measurement correction coefficient of the infrared temperature measuring device, adapting it to different device statuses. Each calibration data point includes the actual temperature of a calibration object, the parameter values ​​of various temperature measurement parameters obtained by measuring the temperature of the calibration object using the infrared temperature measuring device, and the device status information during the temperature measurement of the calibration object. The actual temperature of the calibration object is used as a reference to evaluate the accuracy of the calibrated temperature measurement correction coefficient. The parameter values ​​of each temperature measurement parameter can be used to determine the calibrated temperature measurement correction coefficient with the actual temperature of the calibration object, or to calculate the measured temperature of the calibration object, etc. The device status information during the temperature measurement of the calibration object is used to associate with the calibrated temperature measurement correction coefficient; that is, each piece of device status information corresponds to a calibrated temperature measurement correction coefficient. For example, the various temperature parameters may include: grayscale, device temperature, emissivity, etc. (and may also include ambient temperature, etc. Ambient temperature can be used as a reference and is not included in the calculation of the measured temperature). In the case that the measured temperature can be calculated based on the various temperature parameters, this application does not limit the various temperature parameters.

[0062] In addition, device status information can include parameters across multiple dimensions, such as the infrared temperature measurement device's power setting, lens type, and TEC (Thermoelectric Cooler, primarily used to stabilize the operating temperature of infrared detectors, thereby improving measurement accuracy and device stability, and enabling the infrared temperature measurement device to reach thermal equilibrium with the ambient temperature). The power setting of the infrared temperature measurement device is mainly to adapt to different temperature measurement scenarios, object characteristics, or environmental conditions to ensure measurement accuracy. The lens type directly affects the infrared temperature measurement device's measurement range, accuracy, distance coefficient, and applicable scenarios. Different lens materials, focal lengths, and designs determine the infrared temperature measurement device's focusing ability on infrared light and its environmental adaptability.

[0063] In one implementation, the number of calibration objects indicated in the multiple calibration data is multiple, and the multiple calibration objects are isothermal objects with different temperatures;

[0064] The methods for measuring the temperature of each calibration object using infrared thermometers include:

[0065] The calibration material is placed in environments with different temperatures, and after the infrared thermometer and the environment reach thermal equilibrium, the temperature is measured by the infrared thermometer.

[0066] The number of calibration objects indicated in multiple calibration data points is multiple, and these multiple calibration objects are isothermal objects with different temperatures. The number of calibration objects indicated in each calibration data point can be one or more. The parameter value of each temperature measurement parameter in each calibration data point includes the parameter value of the temperature measurement parameter corresponding to one or more calibration objects. Each calibration data point includes the actual temperature of one or more calibration objects.

[0067] When measuring the temperature of each calibration object, infrared thermometers can place the calibration object in different temperature environments. That is, the infrared thermometer measures the same calibration object at different ambient temperatures, and the measurement is performed after the environment around the infrared thermometer has reached thermal equilibrium to ensure accuracy. By measuring the temperature of each calibration object under different temperature environments and comparing the results, the accuracy and stability of the infrared thermometer can be verified, as well as the impact of environmental factors on the thermometer.

[0068] In addition, to ensure the accuracy of subsequent calibration of the temperature measurement correction coefficient, in this embodiment of the application, after acquiring multiple calibration data and before determining the calibration data corresponding to each device status information from the acquired multiple calibration data, the method further includes:

[0069] Remove calibration data that is considered dirty data from multiple calibration data sets;

[0070] Among them, any calibration data belonging to dirty data is data that does not meet any of the specified conditions; wherein, each specified condition includes: a first type of condition that a single calibration data needs to meet, and a second type of condition that a single calibration data needs to meet with other calibration data; the first type of condition is a condition about the magnitude of the parameter value, and the second type of condition is a condition about the changing trend of the parameter values ​​of multiple parameters that have a correlation relationship.

[0071] This application can also remove calibration data that is considered "dirty" from multiple calibration data sets to ensure the accuracy of subsequent calibrations. Dirty data refers to incomplete, inaccurate, inconsistent, duplicate, or data that does not conform to the expected format. Dirty data can interfere with the accuracy of data analysis, mining, or decision-making, and may even lead to erroneous conclusions. For example, dirty data can specifically be data that does not meet any of the specified conditions. The specified conditions are the conditions that correct calibration data must meet, including: the first type of conditions that a single calibration data set must meet and the second type of conditions that a single calibration data set must meet with other calibration data sets.

[0072] In one implementation, the first type of condition is a condition concerning the magnitude of the parameter value. For example, in a single calibration data point, the device temperature of the infrared thermometer must be greater than the ambient temperature during temperature measurement (i.e., single calibration data points where the device temperature of the infrared thermometer is less than or equal to the ambient temperature during temperature measurement are excluded). The second type of condition concerns the changing trends of parameter values ​​among multiple related parameters. For example, in multiple calibration data sets, the higher the actual temperature of the calibration object, the higher its grayscale value; or, under the same equipment status information, the higher the actual temperature of the calibration object, the greater the degree of grayscale change (i.e., in the range where the actual temperature is higher, the slope of the calibration object with respect to grayscale and temperature is greater, such as: G(T)-G(T-10)>G(T-10)-G(T-20), where G is grayscale, T is temperature, and G(T), G(T-10), and G(T-20) are the grayscale values ​​corresponding to temperatures of T, T-10, and T-20, respectively); or, when the actual temperature of the calibration object is the same, the grayscale value of the calibration object obtained under different equipment temperatures is monotonic, for example, under the same equipment status, the grayscale value of the calibration object increases or decreases as the equipment temperature increases. In addition, each specified condition includes a third type of condition that characterizes the true state of the infrared temperature measuring device with device status information, namely, the device status information in the accurate calibration data needs to characterize the true state of the infrared temperature measuring device when measuring the temperature of the calibration object.

[0073] In other words, for the second type of condition, among multiple calibration data points, if the actual temperature of the calibrated object in one calibration data point is greater than the actual temperature of the calibrated object in another calibration data point, but the grayscale value of the calibrated object in the first calibration data point is less than the grayscale value of the calibrated object in the second calibration data point, then that calibration data point is discarded; or, among multiple calibration data points, if the actual temperature of the calibrated object in one calibration data point is greater than the actual temperature of the calibrated object in another calibration data point, then that calibration data point is discarded. If the grayscale change of a calibration object is less than or equal to the grayscale change of another calibration data point, then that calibration data point is discarded. Alternatively, if multiple calibration data points have the same actual temperature for the calibration object, and the grayscale of the calibration object increases with the increase of the equipment temperature, and there exists a calibration data point where the equipment temperature of the calibration object in that data point is greater than the equipment temperatures of the calibration objects in the multiple calibration data points, but the grayscale of that data point is less than or equal to the grayscale of the calibration objects in the multiple calibration data points, then that calibration data point is discarded.

[0074] The above descriptions of the specified conditions are merely illustrative and should not be construed as limiting the scope of this application.

[0075] In addition, the electronic device can standardize each calibration data to adapt to the data format required for subsequent calibration. First, the temperature parameters (e.g., device temperature, lens temperature, and focal plane temperature) in each calibration data can be normalized to scale the temperature parameters to the range [0, 1]. Then, the information contained in each calibration data is sorted in a predetermined order to obtain the standardized calibration data. The predetermined order can be: [actual temperature, temperature parameter values, device status information, emissivity, distance, grayscale]. Among these, the temperature parameter values, emissivity, distance, and grayscale can all be understood as the parameter values ​​of each temperature measurement parameter. The distance is the distance between the infrared thermometer and the calibration object during temperature measurement. Furthermore, the distance in each calibration data is the same, meaning that each calibration data is measured by the infrared thermometer at the same distance from the calibration object.

[0076] The temperature parameter values ​​can be normalized using the following formula: T_ 归一 =(T-T_min) / (T_max-T_min), T_ 归一 T is the normalized parameter value for temperature, T is the parameter value for temperature before normalization, T_max is the maximum value of the parameter value for temperature in the calibration data, and T_min is the minimum value of the parameter value for temperature in the calibration data.

[0077] S102: Determine the calibration data corresponding to each device status information from the multiple calibration data obtained;

[0078] Among them, the calibration data corresponding to each device status information is each calibration data containing the device status information;

[0079] After obtaining multiple calibration data (which can be multiple calibration data after removing dirty data and standardized calibration data), in order to calibrate the corresponding temperature measurement correction coefficient for the infrared temperature measurement equipment status, this application determines the calibration data corresponding to each equipment status information from the multiple calibration data obtained. The calibration data corresponding to each equipment status information is the calibration data containing that equipment status information. That is, according to the equipment status information, the multiple calibration data obtained are classified to obtain the calibration data corresponding to each equipment status information. The calibration data corresponding to each equipment status information is used to calibrate the temperature measurement correction coefficient for that equipment status information.

[0080] Optionally, in one implementation, determining the calibration data corresponding to each device status information from the acquired multiple calibration data includes:

[0081] Determine the storage space for device status information;

[0082] Each piece of calibration data is traversed. When a piece of calibration data is encountered, it is analyzed whether the device status information in the calibration data exists in the storage space. If it exists, the traversal of the next piece of calibration data continues. If it does not exist, the device status information in the calibration data is stored in the storage space.

[0083] In response to the completion of the traversal of multiple calibration data, for each device status information currently stored in the storage space, the calibration data corresponding to the device status information is determined from the multiple calibration data obtained.

[0084] This application can determine a storage space for device status information, such as a queue, stack, or memory, which is used for different device status information. Then, it iterates through each calibration data set. When a calibration data set is encountered, it analyzes whether the device status information exists in the storage space. If it exists, it continues to the next calibration data set; if it does not exist, the device status information from that calibration data set is stored in the storage space. After all iterations are complete, the device status information for each calibration data set is stored in the storage space, and the device status information stored in this storage space represents the individual device status information for the temperature correction coefficient to be calibrated. For each device status information set, it identifies the calibration data sets containing that device status information from multiple calibration data sets to obtain the corresponding calibration data. Thus, each device status information set corresponds to calibration data, allowing the calibration of the temperature correction coefficient for that device status information to be performed using the corresponding calibration data. Furthermore, the storage space approach avoids missing device status information, enabling the analysis of each device status information set from multiple calibration data sets.

[0085] It should be noted that the above method of classifying the status information of each device and determining the corresponding calibration data of each device status information through storage space is merely an example and should not constitute a limitation on this application.

[0086] S103: For each device status information, based on the calibration data corresponding to the device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated to obtain the calibrated temperature measurement correction coefficient corresponding to the device status information.

[0087] The calibration process is used to ensure that the temperature measured, calculated based on the calibrated temperature correction coefficient corresponding to the device status information and the parameter values ​​of the temperature measurement parameters in the corresponding calibration data, matches the actual temperature in the corresponding calibration data.

[0088] After obtaining the calibration data corresponding to each identification status information, this application can calibrate the temperature correction coefficient of the infrared thermometer based on the calibration data corresponding to each device status information, thereby obtaining the calibrated temperature correction coefficient corresponding to that device status information. The calibration process in this application ensures that the temperature calculated based on the calibrated temperature correction coefficient corresponding to the device status information and the parameter values ​​of the temperature measurement parameters in the corresponding calibration data matches the actual temperature in the corresponding calibration data. In other words, the calibration process in this application ensures that each device status information corresponds to a calibrated temperature correction coefficient, and the temperature calculated based on the calibrated temperature correction coefficient for each device status information matches the actual temperature measured by the infrared thermometer for the object under that device status information. That is, using the calibrated temperature correction coefficient for each device status information for temperature measurement, the true temperature measured by the infrared thermometer for the object under that device status information can be obtained.

[0089] In one implementation, the step of calibrating the temperature correction coefficient of the infrared thermometer based on the calibration data corresponding to each device status information to obtain the calibrated temperature correction coefficient corresponding to the device status information includes:

[0090] For each device status information, based on the calibration data corresponding to the device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated according to a predetermined calibration method to obtain the calibrated temperature measurement correction coefficient corresponding to the device status information.

[0091] The predetermined calibration methods include: a calibration method based on forward fitting, a calibration method based on parameter iterative optimization, or a calibration method based on a neural network model.

[0092] In this application, during calibration, the calibrated temperature correction coefficient corresponding to the device status information can be obtained according to a predetermined calibration method. The predetermined calibration method includes: a calibration method based on forward fitting, a calibration method based on parameter iterative optimization, or a calibration method based on a neural network model.

[0093] The calibration method based on forward fitting can be understood as follows: based on the actual temperature of the calibration object in the calibration data corresponding to the equipment status information, and the parameter values ​​of each temperature measurement parameter, the nonlinear relationship between the parameter values ​​of each temperature measurement parameter and the actual temperature is fitted. This nonlinear relationship is the calibrated temperature measurement correction coefficient corresponding to the equipment status information. For example, the calibrated temperature measurement correction coefficient includes multiple sub-coefficients, which are used as parameter value coefficients of each temperature measurement parameter to form a polynomial. The actual temperature of the calibration object is used as the sum of each polynomial. Based on this, the multiple sub-coefficients are solved to obtain the calibrated temperature measurement correction coefficient corresponding to the equipment status information. The calibration method based on a neural network model can be understood as follows: The parameter values ​​of each temperature measurement parameter in the calibration data corresponding to the device's status information are input into a neural network model (used for temperature prediction based on multiple parameter values). This yields the measured temperature of the calibration object in the calibration data for the device's status information. By continuously adjusting the model parameters of the neural network model to match the measured temperature with the actual temperature of the calibration object in the calibration data, the model parameters of the neural network model are determined as the calibrated temperature correction coefficients corresponding to the device's status information. Furthermore, the calibration method based on parameter iterative optimization will be described in detail in subsequent embodiments and will not be elaborated upon here.

[0094] It should be noted that the aforementioned calibration methods based on forward fitting, parameter iterative optimization, or neural network models are all methods of optimizing the temperature correction coefficient during calibration. Through this predetermined calibration method, the accurate calibrated temperature correction coefficient corresponding to the device status information can be obtained. As long as the temperature calculated based on the calibrated temperature correction coefficient corresponding to the device status information and the parameter values ​​of the temperature measurement parameters in the corresponding calibration data matches the actual temperature in the corresponding calibration data, this application does not limit the predetermined calibration method.

[0095] S104: Store the status information of each device and the corresponding calibrated temperature correction coefficient in the infrared temperature measuring device to complete the calibration of the temperature correction coefficient of the infrared temperature measuring device.

[0096] After obtaining the status information of each device and the corresponding calibrated temperature correction coefficient, this application can also store them in association in the infrared temperature measuring device to complete the calibration of the temperature correction coefficient of the infrared temperature measuring device.

[0097] When the execution subject of the parameter calibration method of the infrared temperature measuring device is a terminal device that communicates with the infrared temperature measuring device, the terminal device can upload the status information of each device and the corresponding calibrated temperature measurement correction coefficient to the infrared temperature measuring device for associated storage; when the execution subject of the parameter calibration method of the infrared temperature measuring device is the infrared temperature measuring device, the infrared temperature measuring device can directly store the status information of each device and the corresponding calibrated temperature measurement correction coefficient locally.

[0098] In addition, when storing the status information of each device and the corresponding calibrated temperature correction coefficient in association, the status information of each device and the corresponding calibrated temperature correction coefficient can be stored in association through tables or other means. Alternatively, a pointer to each device status information can be established, and the pointer to each device status information indicates the calibrated temperature correction coefficient or the cache address of the calibrated temperature correction coefficient corresponding to that device status information. This application does not limit the method of storing the status information of each device and the corresponding calibrated temperature correction coefficient in association.

[0099] In the technical solution of this application, all operations such as acquiring, storing, using, processing, transmitting, providing, and disclosing calibration data, actual temperature of the calibration object, parameters of each temperature measurement parameter, equipment status information, and temperature measurement correction coefficient are carried out with the user's authorization.

[0100] The parameter calibration method for infrared temperature measuring devices provided in this application, after acquiring multiple calibration data, first identifies each calibration data point containing the same device status information, i.e., classifying the multiple calibration data according to the device status information to obtain the calibration data corresponding to each device status information; then, for each device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated based on the corresponding calibration data, resulting in the calibrated temperature measurement correction coefficient for that device status information; each device status information and its corresponding calibrated temperature measurement correction coefficient are stored in association within the infrared temperature measuring device. Through this parameter calibration method, for each device status information, a corresponding calibrated temperature measurement correction coefficient is determined based on the corresponding calibration data, and the device status information and the corresponding calibrated temperature measurement correction coefficient are stored in association. Thus, for the temperature measurement of the infrared temperature measuring device, calibrated temperature measurement correction coefficients corresponding to each device status information can be provided, thereby providing a foundation for improving the accuracy of the infrared temperature measuring device.

[0101] Alternatively, in another embodiment of this application, such as Figure 2 As shown, the calibration method based on parameter iterative optimization may include the following steps:

[0102] S201: The initial temperature correction coefficient of the infrared temperature measuring device is perturbed to obtain a first number of candidate temperature correction coefficients;

[0103] In order to calibrate the temperature correction coefficient of the infrared temperature measurement device, the initial temperature correction coefficient is first perturbed to obtain a first number of candidate temperature correction coefficients, so as to expand the number of temperature correction coefficients, and then perform parameter iterative optimization on the first number of candidate temperature correction coefficients to obtain the calibrated temperature correction coefficients corresponding to the device status information.

[0104] The initial temperature correction factor can be understood as the fixed temperature correction factor used in related technologies. This fixed temperature correction factor is the general temperature correction factor (coeff). The applicability, accuracy, and scenario coverage of this fixed temperature correction factor are in the middle of the industry. It is neither a high-precision parameter optimized for specific scenarios nor a low-precision parameter simplified to the extreme. Instead, it is an "intermediate solution" formed after balancing universality, cost, and accuracy.

[0105] For example, in one implementation, any temperature measurement correction factor includes multiple types of sub-coefficients;

[0106] The initial temperature correction coefficient of the infrared temperature measuring device is perturbed to obtain a first number of candidate temperature correction coefficients, including:

[0107] According to a specified perturbation method, the multiple sub-coefficients in the initial temperature measurement correction coefficients of the infrared temperature measurement device are perturbed to obtain a first number of candidate temperature measurement correction coefficients; wherein, the specified perturbation method includes: a perturbation method of adding to a random number, and / or a perturbation method of multiplying by a random coefficient.

[0108] Any temperature measurement correction coefficient may include multiple types of sub-coefficients. During perturbation processing, the multiple types of sub-coefficients in the initial temperature measurement correction coefficients of the infrared temperature measurement device can be perturbed by adding to a random number and / or multiplying with a random coefficient to obtain a first number of candidate temperature measurement correction coefficients. The perturbation methods for different sub-coefficients can be the same or different, and the random number and / or random coefficients used during perturbation can also be the same or different; this application does not impose any limitations on this.

[0109] This application perturbs multiple sub-coefficients in the initial temperature measurement correction coefficients by specifying a perturbation method, thereby obtaining a first number of candidate temperature measurement correction coefficients with diversity, so as to perform parameter iteration and more conveniently and quickly determine the calibrated temperature measurement correction coefficients.

[0110] S202: For each candidate temperature measurement correction coefficient, calculate the temperature measurement related to the calibration data of the device status information under the candidate temperature measurement correction coefficient according to the predetermined calculation method;

[0111] The predetermined calculation method includes: performing temperature calculation based on the temperature correction coefficient of the candidate and the parameter values ​​of the temperature measurement parameters in the calibration data corresponding to the device status information;

[0112] For each of the first number of candidate temperature correction coefficients, in order to verify whether the candidate temperature correction coefficient is accurate, for example, whether the temperature that matches the actual temperature of the calibration object can be calculated using the candidate temperature correction coefficient, the temperature related to the calibration data corresponding to the device status information under the candidate temperature correction coefficient can be calculated according to a predetermined calculation method. For example, the temperature can be calculated based on the candidate temperature correction coefficient and the parameter value of the temperature measurement parameter in the calibration data corresponding to the device status information to obtain the temperature measurement.

[0113] In addition, each candidate temperature measurement correction coefficient can also include multiple sub-coefficients. Each sub-coefficient can be used as a coefficient of the parameter value of a temperature measurement parameter in the calibration data. The parameter value of each temperature measurement coefficient is multiplied by the corresponding sub-coefficient and then summed to obtain the temperature measurement temperature.

[0114] It should be noted that the method of calculating the temperature based on any temperature correction coefficient and the parameter values ​​of each temperature measurement parameter can be similar to existing technologies. For example, the temperature measurement process of the infrared temperature measurement device can be abstracted into a model, the parameters of which are the temperature correction coefficients. By inputting the parameter values ​​of each temperature measurement parameter into the model, the corresponding temperature measurement can be output.

[0115] S203: Based on the measured temperature related to the calibration data corresponding to the obtained device status information, and the actual temperature in the calibration data corresponding to the device status information, iteratively optimize the current first number of candidate temperature measurement correction coefficients to obtain the iteratively optimized first number of candidate temperature measurement correction coefficients, and return the step of calculating the measured temperature related to the calibration data corresponding to the device status information under the current candidate temperature measurement correction coefficient according to a predetermined calculation method;

[0116] During parameter iterative optimization, the measured temperature related to the calibration data corresponding to the device status information, and the actual temperature in the calibration data corresponding to the device status information, can be used to iteratively optimize the first number of candidate temperature measurement correction coefficients to obtain the iteratively optimized first number of candidate temperature measurement correction coefficients; then return to step S202 until the iteration termination condition is met. During iterative optimization, the accuracy of the temperature measurement correction coefficients can be judged based on the difference between the measured temperature and the actual temperature, thereby iteratively optimizing the first number of candidate temperature measurement correction coefficients.

[0117] For example, in one implementation, the step of iteratively optimizing the first number of candidate temperature measurement correction coefficients based on the measured temperature related to the calibration data corresponding to the obtained device status information and the actual temperature in the calibration data corresponding to the device status information, to obtain the iteratively optimized first number of candidate temperature measurement correction coefficients, includes:

[0118] For each candidate temperature measurement correction factor, based on the temperature measurement temperature formed by the calibration data corresponding to the device status information under the candidate temperature measurement correction factor, and the actual temperature in the calibration data corresponding to the device status information, calculate the loss value of the temperature difference corresponding to the candidate temperature measurement correction factor.

[0119] Based on the loss value of temperature difference corresponding to each candidate temperature correction coefficient, a second number of candidate temperature correction coefficients are selected from the current first number of candidate temperature correction coefficients; wherein, the loss value of temperature difference corresponding to the second number of candidate temperature correction coefficients is less than the loss value of temperature difference corresponding to the other temperature correction coefficients; wherein, the other temperature correction coefficients are parameters other than the second number of candidate temperature correction coefficients from the current first number of candidate temperature correction coefficients.

[0120] The selected second number of candidate temperature measurement correction coefficients are adjusted to obtain the first number of candidate temperature measurement correction coefficients after iterative optimization.

[0121] During the iterative optimization process, for each candidate temperature measurement correction coefficient, the measured temperature formed by the calibration data corresponding to the device status information under the candidate temperature measurement correction coefficient, and the actual temperature in the calibration data corresponding to the device status information are used to calculate the temperature difference loss value corresponding to the candidate temperature measurement correction coefficient under the device status information and the corresponding actual temperature. This is used to evaluate whether the candidate temperature measurement correction coefficient is accurate. Then, based on the temperature difference loss value corresponding to each candidate temperature measurement correction coefficient, a second number of candidate temperature measurement correction coefficients with a smaller loss value than the temperature difference loss values ​​corresponding to other temperature measurement correction coefficients are selected from the first number of candidate temperature measurement correction coefficients. That is, the second number of candidate temperature measurement correction coefficients with smaller loss values ​​are selected from the first number of candidate temperature measurement correction coefficients, which are more accurate. The parameters are then adjusted using the more accurate second number of candidate temperature measurement correction coefficients to obtain the iteratively optimized first number of candidate temperature measurement correction coefficients.

[0122] Among them, the loss value of the second number of candidate temperature measurement correction coefficients corresponding to the temperature difference is smaller than the loss value of the other temperature measurement correction coefficients corresponding to the temperature difference; this application can sort the loss values ​​of the first number of candidate temperature measurement correction coefficients corresponding to the temperature difference, for example, sort them in ascending or descending order, and select the temperature measurement correction coefficients corresponding to the second number of loss values ​​from the sorting results in ascending order of loss value to obtain the second number of candidate temperature measurement correction coefficients.

[0123] Furthermore, there are multiple ways to calculate the loss value. For example, a piece of equipment status information can correspond to multiple calibration data points. For each calibration data point, the difference between the measured temperature and the actual temperature can be calculated. Then, the absolute values ​​of the differences calculated for each calibration data point in the equipment status information are summed to obtain the loss value related to the temperature difference corresponding to the candidate temperature measurement correction coefficient under that equipment status information. Of course, other methods can also be used to calculate the loss value, such as averaging, calculating variance and standard deviation, etc. This application does not limit this method.

[0124] Thus, since the temperature correction coefficients of the second number of candidates are more accurate than those of the first number of candidates, the temperature correction coefficients of the first number of candidates after iterative optimization are more accurate than those of the first number of candidates without iterative optimization.

[0125] In addition, any temperature measurement correction factor includes multiple sub-factors, and the order of the multiple sub-factors in different temperature measurement correction factors is the same;

[0126] The parameter adjustment process includes:

[0127] Genetic manipulation, crossover manipulation, and / or mutation manipulation;

[0128] The genetic treatment includes:

[0129] Retain the second number of candidate temperature measurement correction coefficients;

[0130] The cross-processing includes: swapping the sub-coefficients with the same sorting position among the second number of candidate temperature measurement correction coefficients;

[0131] The mutation processing includes: adjusting the sub-coefficients in the second number of candidate temperature measurement correction coefficients respectively using a predetermined mutation coefficient.

[0132] In this application, any temperature measurement correction coefficient includes multiple sub-coefficients, and the order of the multiple sub-coefficients in different temperature measurement correction coefficients is the same. For example, the multiple sub-coefficients include a1, a2, a3...an, and the multiple sub-coefficients in different temperature measurement correction coefficients are all a1-an. When adjusting the parameters of a second number of candidate temperature measurement correction coefficients, the following can be performed: genetic processing to retain the second number of candidate temperature measurement correction coefficients; crossover processing to interchange the sub-coefficients with the same sorting position in the second number of candidate temperature measurement correction coefficients; and / or, adjusting the sub-coefficients in the second number of candidate temperature measurement correction coefficients respectively through a predetermined coefficient of variation.

[0133] In one implementation, the first quantity can be 3N, the second quantity can be N, and the predetermined coefficient of variation can be α, where α takes the value [0.8, 1.2].

[0134] In this application, through genetic processing, crossover processing and / or mutation processing, the parameters of various sub-coefficients of the selected second number of candidate temperature measurement correction coefficients can be adjusted to expand the number of temperature measurement correction coefficients and obtain a first number of candidate temperature measurement correction coefficients with richness and diversity after iterative optimization.

[0135] S204: In response to the fulfillment of the iteration termination condition, determine the calibrated temperature correction coefficient based on the current candidate temperature correction coefficients.

[0136] During the iteration process, if the iteration termination condition is met, the calibrated temperature correction coefficient can be determined based on the current candidate temperature correction coefficients to complete the calibration process of the temperature correction coefficient under the device status information, and obtain the calibrated temperature correction coefficient corresponding to the device status information.

[0137] Optionally, the condition for satisfying the iteration termination includes:

[0138] Satisfy any one of the predetermined conditions;

[0139] The predetermined conditions include: the first condition and the second condition;

[0140] The first condition includes: among the current candidate temperature measurement correction coefficients, there exists a specified temperature measurement correction coefficient; wherein, the loss value of the temperature difference corresponding to the specified temperature measurement correction coefficient is less than a predetermined loss value, and under the specified temperature measurement correction coefficient, the difference between the measured temperature related to the calibration data corresponding to the device status information and the corresponding actual temperature is less than a predetermined threshold.

[0141] The second condition includes: the number of iterations reaches a predetermined number;

[0142] Accordingly, in response to satisfying the iteration termination condition, determining the calibrated temperature correction coefficient based on the current candidate temperature correction coefficients includes:

[0143] In response to the fulfillment of the first condition, the specified temperature measurement correction factor is determined as the calibrated temperature measurement correction factor; or...

[0144] In response to the second condition being met, the candidate temperature correction coefficient with the smallest loss value for temperature difference is selected from the current candidate temperature correction coefficients to obtain the calibrated temperature correction coefficient.

[0145] The iteration termination condition can include a first condition and a second condition. Meeting the iteration termination condition means satisfying either the first or second condition. The first condition is that among the current candidate temperature measurement correction coefficients, there exists a specified temperature measurement correction coefficient. The loss value corresponding to the specified correction coefficient regarding temperature difference is less than a predetermined loss value, and the difference between the measured temperature calculated by the specified temperature measurement correction coefficient and the actual temperature is less than a predetermined threshold. In other words, the measured temperature calculated using the specified temperature measurement correction coefficient and the parameter values ​​of the temperature measurement parameters in the calibration data corresponding to the device status information matches the actual temperature in the corresponding calibration data. That is, the specified temperature measurement correction coefficient is a corrected temperature measurement correction coefficient that meets the accuracy requirements. The second condition can be that the number of iterations reaches a predetermined number. The predetermined loss value and predetermined threshold can be set according to the actual accuracy requirements, and this application does not limit them.

[0146] When the first condition is met, since the specified temperature correction coefficient is the temperature correction coefficient that meets the accuracy required under the device status information, it can be directly determined as the calibrated temperature correction coefficient corresponding to the device status information. When the second condition is met, since the temperature correction coefficient of each iteration is more accurate than the previous iteration, and when the number of iterations reaches a predetermined number, the current temperature correction coefficient is the most accurate in all iterations. Therefore, the candidate temperature correction coefficient with the smallest loss value regarding temperature difference can be selected from the current candidate temperature correction coefficients to obtain the calibrated temperature correction coefficient.

[0147] In this application, different iteration termination conditions are set, and the corresponding methods for determining the calibrated temperature measurement correction coefficient under different iteration termination conditions are used to match different accuracy requirements or iteration number requirements, and select the corresponding accurate calibrated temperature measurement correction coefficient.

[0148] As can be seen, this application can generate a first number of candidate temperature measurement correction coefficients through parameter iterative optimization, satisfying the requirements of diversity and richness for selection during the iterative process. Furthermore, for each candidate temperature measurement correction coefficient, the first number of candidate temperature measurement correction coefficients are iteratively optimized using the temperature measured by the candidate temperature measurement correction coefficient and the corresponding actual temperature, resulting in more accurate iteratively optimized first number of candidate temperature measurement correction coefficients. When the iteration termination condition is met, the calibrated temperature measurement correction coefficients can be determined from the current temperature measurement correction coefficients of each candidate that are more accurate than the temperature measurement correction coefficients optimized in the previous iteration, ensuring that the calibrated temperature measurement correction coefficients are more accurate under the condition of the device status information.

[0149] The parameter calibration method of the infrared temperature measurement device provided in this application is described below with reference to a specific embodiment.

[0150] Step 1, Data Preprocessing:

[0151] The data source for the parameter calibration method of the infrared thermometer in this application is as follows: after the infrared thermometer reaches thermal equilibrium with the environment at different ambient temperatures, calibration data of different calibration objects are collected at a fixed distance d (i.e., each calibration data is obtained by the infrared thermometer at the same distance from the calibration object), and under different TEC parameters, settings, and / or lens types. Each calibration data includes the parameter values ​​of various temperature measurement parameters such as the grayscale G of the calibration object, the device temperature cav, and the emissivity emiss of the object, as well as the device status information such as the TEC parameters, setting sen, and lens type lensType during temperature measurement, and the actual temperature T_real of the calibration object. Generally, an infrared thermometer will acquire N data points. For these N data points, dirty data is removed based on certain prior knowledge, and the data content and format are standardized. The standardized calibration data is used for subsequent parameter calibration of the infrared thermometer.

[0152] The specified conditions for removing dirty data include:

[0153] a) The temperature (cav) of the infrared thermometer must be higher than the ambient temperature;

[0154] b) Among multiple calibration data, the higher the actual temperature of the calibration object, the higher the gray value of the calibration object;

[0155] c) When the equipment status information is the same, the higher the actual temperature of the calibration object, the greater the degree of grayscale change of the calibration object (that is, in the range where the actual temperature is higher, the slope of the calibration object with respect to grayscale and temperature is greater, such as: G(T)-G(T-10)>G(T-10)-G(T-20), where G is grayscale and T is temperature); that is, the higher the actual temperature of the calibration object, the greater the response of the calibration object (the slope of the function with respect to temperature and grayscale, and the first derivative with respect to temperature).

[0156] d) When the actual temperature of the calibration object is the same, the gray level of the calibration object obtained under different equipment temperatures (cav) is monotonous. For example, under the same equipment conditions, the gray level of the calibration object increases or decreases as the equipment temperature increases. For example, if the actual temperature of the calibration object is T, under a certain lens type, TEC, and sen, the gray level G of the calibration object increases or decreases as the equipment temperature (cav) increases.

[0157] e)lensType,TEC,sen meet the actual possible conditions of current infrared temperature measurement equipment.

[0158] Among them, a) is the first type of condition mentioned above, b)-d) are the second type of condition mentioned above, and e) is the third type of condition mentioned above.

[0159] Data standardization methods are as follows:

[0160] Data standardization: Temperature-related parameter values ​​such as cavity temperature (CAV), lens temperature (LEN), and focal plane temperature (FPA) are preprocessed according to scaling relationships. For example, if the infrared thermometer's temperature measurement model is a neural network model, the temperature-related parameter values ​​such as CAV, LEN, and FPA can be scaled to [0,1], specifically according to the formula: T_ 归一 =(T-T_min) / (T_max-T_min) is used for normalized scaling, thereby preventing certain features from dominating the training of the neural network model due to excessively large parameter values.

[0161] Data format standardization: Based on the data format requirements of the back-end automatic calibration module (a functional module for calibration processing, which can be used to perform the above step S103), the data format is standardized. For example, each calibration data is stored in the following order from left to right (i.e., the predetermined order mentioned above): [T_real, cav, lensType, TEC, sen, emiss, d, G] (lensT (lens temperature), FPA (focal plane temperature), etc. are omitted).

[0162] Step 2, Parameter Calibration:

[0163] The temperature measurement model of an infrared thermometer can be abstracted as T_out = f(G, cav, emiss, d, coeff(lensType, TEC, sen)). This means that the measured temperature is calculated based on the device status information (ensType, TEC, sen) and the parameter values ​​of each temperature measurement parameter of the measured object (G, emiss, d, cav), combined with the temperature correction coefficient coeff of the infrared thermometer. The device status information (ensType, TEC, sen) does not participate in the temperature calculation; it is only associated with the corresponding coeff parameter. For example, when calculating the temperature, coeff contains multiple sub-coefficients, which are multiplied as coefficients of the parameter values ​​of temperature measurement parameters G, emiss, d, and cav, and the results of these multiplications are summed to obtain the measured temperature.

[0164] For example, in another implementation, under different ambient temperatures (env) (and different device temperatures (cav), with a fixed distance (d) and an emissivity (emiss), the calculation process for the measured temperature (T_out) based on the grayscale (G) of different measured objects is as follows:

[0165] G=(a*T 2 +b*T+C)*rv;

[0166] rv=p*cav 2 +q*cav+R;

[0167] T_out^4*emiss+env^4*(1-emiss)=T;

[0168] Where p, q, R, a, b, and C are sub-coefficients in the temperature measurement correction coefficient coeff; T_out is the measured temperature (matching the true temperature of the object being measured), and T is the equivalent temperature measured by the detector of the infrared thermometer. T_out is related to T through emissivity emiss and ambient temperature env. Given T, emiss, and env, T_out can be derived. The equivalent temperature T can be understood as the equivalent temperature of "object's own radiation + ambient reflected radiation" measured by the detector of the infrared thermometer.

[0169] The parameter calibration method for infrared temperature measurement equipment can automatically calculate the calibrated temperature correction coefficient coeff corresponding to each equipment status information based on the data preprocessed in step 1. After production on the production line, the infrared temperature measurement equipment can be automatically calibrated to achieve the expected temperature measurement accuracy under various equipment statuses. The temperature correction coefficient coeff varies depending on the lens type, TEC parameters, and settings. Methods for calculating the calibrated temperature correction coefficient corresponding to any equipment status parameter include, but are not limited to, forward fitting, parameter iterative optimization, and neural network models.

[0170] Step 3: Store the calibrated temperature correction parameters to the infrared temperature measurement device: For each device status information, after calibrating the temperature correction parameters of the device status information, customized and calibrated temperature correction parameters for each device status information of the infrared temperature measurement device will be generated and saved to the infrared temperature measurement device.

[0171] like Figure 3 As shown in the embodiments of this application, the parameter calibration method for the infrared temperature measurement device may include the following steps:

[0172] S1: Based on standard data, statistically analyze the equipment status information of the current infrared temperature measurement equipment that needs to be calibrated, that is, determine which lens types and temperature measurement correction parameters under TEC and sen need to be calibrated;

[0173] S2: Under a single lensType, TEC, and sen, perturb the sub-coefficients in the initial temperature correction coefficients to generate 3N temperature correction coefficients (the first number of candidate temperature correction coefficients). For example: the initial temperature correction coefficient coeff contains n sub-parameters (a1~an). Each sub-parameter is processed by adding a random number to the n sub-parameters, repeated 3N times to obtain 3N temperature correction coefficients. That is, for the temperature correction coefficients before optimization (the initial temperature correction coefficients), 3N sets of perturbation parameters are used to perturb them, resulting in 3N temperature correction coefficients.

[0174] S3: Under a single lensType, TEC, and sen, based on 3N temperature measurement correction coefficients and multiple standardized calibration data, 3N temperature measurements are calculated. Loss is calculated for each of these 3N temperature measurement results (which can be 3N temperature measurements) and the corresponding actual temperature. This yields the loss corresponding to each of the 3N temperature measurement correction coefficients, i.e., the 3N sets of losses. For example: For each temperature measurement correction coefficient, the loss value is obtained by summing the absolute values ​​of the differences between the measured temperature and the actual temperature, where loss = sum(abs(T_out – T_real)), where abs is the function for calculating the absolute value and sum is the function for summing.

[0175] S4: Under a single lensType, TEC, and sen, sort the 3N losses to obtain the top N losses (the second-largest number of candidate temperature correction coefficients sorted by loss from smallest to largest) and their corresponding temperature correction coefficients (i.e., obtain the top 1-N losses and their corresponding temperature correction coefficients). Based on the top N temperature correction coefficients, perform parameter adjustments such as genetics, crossover, and mutation to generate another 3N sets of temperature correction coefficients. For example, the parameter adjustment process is as follows:

[0176] Genetics: Directly retain the current N sets of temperature measurement correction coefficients;

[0177] Crossover: The sub-parameters of the current N sets of temperature measurement correction coefficients are exchanged with each other;

[0178] Mutation: The individual parameters of each of the n sub-parameters of the current N temperature measurement correction coefficients are mutated by multiplying by the mutation coefficient α (exemplary: α∈[0.8,1.2]).

[0179] S5: Under a single lensType, TEC, and sen, repeat S3 to S4 to determine whether the iteration termination condition is met. If yes, directly obtain the temperature correction coefficient with the highest loss (which can be used as the calibrated temperature correction coefficient corresponding to the device's state parameters). If no, regenerate 3N new temperature correction coefficients (iteration number + 1) through parameter adjustment, and calculate 3N new sets of temperature measurement results and 3N new sets of losses based on the newly generated 3N temperature correction coefficients, until the iteration termination condition is met.

[0180] S6: Repeat S2 to S5 with a different set of lensType, TEC, and sen until all lensType, TEC, and sen have been calibrated, and obtain the calibrated temperature correction coefficients corresponding to the status parameters of each device.

[0181] After automatic calibration, the calibrated temperature correction coefficients corresponding to the status parameters of each device of the infrared temperature measuring device will be generated and stored in the infrared temperature measuring device.

[0182] As shown in Table 1, under the premise of ±1 / ±1% accuracy standard, the infrared temperature measuring device achieves an accuracy of ±1 / ±1% after parameter calibration. With TEC parameter = 1, sen = 0, and a standard lens, the infrared temperature measuring device achieves an accuracy of ±1 / ±1% under different ambient temperatures. Here, bbttemp is the actual temperature of the blackbody (the target object being measured), resluttemp is the measured blackbody temperature (i.e., the measured temperature calculated according to the calibrated temperature correction coefficient corresponding to the corresponding device status information), errornum is the error, riteStd is the reference temperature standard, and flag_good_bad is used to characterize the quality (accuracy) of the calibrated temperature correction coefficient corresponding to the device status information.

[0183] Table 1

[0184]

[0185]

[0186] In this application, each infrared temperature measurement device was calibrated according to the parameter calibration method for infrared temperature measurement devices, and the parameters were highly customized (various device status information corresponded to the corrected temperature measurement correction coefficient). Compared with using a fixed temperature measurement correction coefficient, the accuracy of infrared temperature measurement devices is higher because a fixed temperature measurement correction coefficient is located at the median level of the temperature measurement correction coefficients of infrared temperature measurement devices. If applied to temperature measurement scenarios far from the median level, the temperature measurement accuracy of infrared temperature measurement devices will decrease, meaning that the temperature measurement accuracy of infrared temperature measurement devices is not high in such scenarios.

[0187] The infrared temperature measurement equipment is automatically calibrated after production on the production line, eliminating the time spent by developers to develop universal and fixed temperature measurement correction coefficients and the time spent calibrating the infrared temperature measurement equipment on the production line. In other words, this application improves the accuracy of the infrared temperature measurement equipment while also increasing its production efficiency.

[0188] Based on the parameter calibration method for the aforementioned infrared temperature measuring device, this application also provides a temperature measuring method applied to an infrared temperature measuring device, wherein the infrared temperature measuring device is a device whose parameters have been calibrated according to the aforementioned parameter calibration method for infrared temperature measuring devices, such as... Figure 4 As shown, this temperature measurement method may include the following steps:

[0189] S401: In response to the temperature measurement operation on the target object, obtain the parameter values ​​of each temperature measurement parameter obtained from the temperature measurement of the target object;

[0190] In this application, the infrared temperature measuring device, after parameter calibration according to the above-mentioned parameter calibration method, can obtain the parameter values ​​of each temperature measurement parameter obtained by measuring the target object in response to the temperature measurement operation of the target object; the specific process of obtaining the parameter values ​​of each temperature measurement parameter can be similar to the prior art, and will not be described in detail here.

[0191] S402: Obtain the device status information when measuring the temperature of the target object, and use it as the target device status information;

[0192] In this application, since the calibrated temperature measurement correction coefficient is associated with the device status information of the infrared temperature measurement device, in order to accurately measure the temperature of the target object, the device status information when measuring the temperature of the target object is first obtained as the target device status information.

[0193] S403: Based on the status information of each device stored in the infrared temperature measuring device and the corresponding calibrated temperature measurement correction coefficient, determine the calibrated temperature measurement correction coefficient corresponding to the status information of the target device;

[0194] After determining the target device status information, the calibrated temperature correction factor corresponding to the target device status information can be determined from the associated stored status information of each device and the corresponding calibrated temperature correction factor. This allows for a more accurate measurement of the target object's temperature under the target device status information by using the calibrated temperature correction factor corresponding to the target device status information.

[0195] S404: Based on the obtained parameter values ​​of each temperature measurement parameter and the calibrated temperature measurement correction coefficient corresponding to the target device status information, determine the temperature of the target object.

[0196] This application is able to determine the measured temperature of the target object under the target device status information based on the obtained parameter values ​​of each temperature measurement parameter and the calibrated temperature measurement correction coefficient corresponding to the target device status information.

[0197] In the temperature measurement method provided in this application, when the infrared thermometer measures the temperature of a target object, it does not directly select a fixed temperature correction coefficient. Instead, it considers the influence of the device status on the temperature measurement, thereby obtaining the device status information of the infrared thermometer at the time of testing as the target device status information, and using the calibrated temperature correction coefficient corresponding to the target device status information to calculate the temperature. Therefore, the temperature measurement method provided in this application considers the influence of the device status on the temperature measurement and selects a matching calibrated temperature correction coefficient for temperature calculation. Thus, compared to using a fixed temperature correction coefficient, it can improve the accuracy of the infrared thermometer.

[0198] Based on the above method embodiments, this application also provides a parameter calibration device for infrared temperature measurement equipment, such as... Figure 5 As shown, the device includes:

[0199] The first acquisition module 510 is used to acquire multiple calibration data; wherein each calibration data includes: the actual temperature of a calibration object, and the parameter values ​​of each temperature measurement parameter obtained by measuring the temperature of the calibration object through an infrared temperature measuring device, and the device status information when measuring the temperature of the calibration object;

[0200] The first determining module 520 is used to determine the calibration data corresponding to each device status information from the acquired multiple calibration data; wherein, the calibration data corresponding to each device status information is each calibration data containing that device status information;

[0201] The calibration module 530 is used to calibrate the temperature correction coefficient of the infrared temperature measuring device based on the calibration data corresponding to the device status information for each device status information, so as to obtain the calibrated temperature correction coefficient corresponding to the device status information; wherein, the calibration process is used to ensure that the temperature calculated based on the calibrated temperature correction coefficient corresponding to the device status information and the parameter values ​​of the temperature measuring parameters in the corresponding calibration data matches the actual temperature in the corresponding calibration data.

[0202] The storage module 540 is used to store the status information of each device and the corresponding calibrated temperature correction coefficient in the infrared temperature measuring device in association, so as to complete the calibration of the temperature correction coefficient of the infrared temperature measuring device.

[0203] The parameter calibration device for infrared temperature measurement equipment provided in this application, after acquiring multiple calibration data, can first identify each calibration data containing the same equipment status information from the multiple calibration data, that is, classify the multiple calibration data according to the equipment status information to obtain the calibration data corresponding to each equipment status information; then, for each equipment status information, based on the calibration data corresponding to that equipment status information, the temperature measurement correction coefficient of the infrared temperature measurement equipment is calibrated to obtain the calibrated temperature measurement correction coefficient corresponding to that equipment status information; each equipment status information and its corresponding calibrated temperature measurement correction coefficient are stored in association in the infrared temperature measurement equipment. Through this parameter calibration method, for each equipment status information, a corresponding calibrated temperature measurement correction coefficient is determined based on the corresponding calibration data, and the equipment status information and the corresponding calibrated temperature measurement correction coefficient are stored in association. In this way, for the temperature measurement of the infrared temperature measurement equipment, calibrated temperature measurement correction coefficients corresponding to each equipment status information can be provided, thereby providing a basis for improving the temperature measurement accuracy of the infrared temperature measurement equipment.

[0204] Optionally, the number of calibration objects indicated in the multiple calibration data is multiple, and the multiple calibration objects are isothermal objects with different temperatures;

[0205] The methods for measuring the temperature of each calibration object using infrared thermometers include:

[0206] The calibration material is placed in environments with different temperatures, and after the infrared thermometer and the environment reach thermal equilibrium, the temperature is measured by the infrared thermometer.

[0207] Optionally, the first determining module is specifically used for:

[0208] Determine the storage space for device status information;

[0209] Each piece of calibration data is traversed. When a piece of calibration data is encountered, it is analyzed whether the device status information in the calibration data exists in the storage space. If it exists, the traversal of the next piece of calibration data continues. If it does not exist, the device status information in the calibration data is stored in the storage space.

[0210] In response to the completion of the traversal of multiple calibration data, for each device status information currently stored in the storage space, the calibration data corresponding to the device status information is determined from the multiple calibration data obtained.

[0211] Optionally, the calibration module is specifically used for:

[0212] For each device status information, based on the calibration data corresponding to the device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated according to a predetermined calibration method to obtain the calibrated temperature measurement correction coefficient corresponding to the device status information.

[0213] The predetermined calibration methods include: a calibration method based on forward fitting, a calibration method based on parameter iterative optimization, or a calibration method based on a neural network model.

[0214] Optionally, when the calibration method includes a calibration method based on parameter iterative optimization, the calibration module includes:

[0215] The perturbation submodule is used to perturb the initial temperature correction coefficient of the infrared temperature measuring device to obtain a first number of candidate temperature correction coefficients.

[0216] The calculation module is used to calculate the temperature related to the calibration data of the device status information under each candidate temperature correction coefficient according to a predetermined calculation method; the predetermined calculation method includes: performing temperature calculation based on the candidate temperature correction coefficient and the parameter values ​​of the temperature measurement parameters in the calibration data corresponding to the device status information.

[0217] The iterative submodule is used to iteratively optimize the first number of candidate temperature measurement correction coefficients based on the measured temperature related to the calibration data corresponding to the obtained device status information and the actual temperature in the calibration data corresponding to the device status information, to obtain the first number of candidate temperature measurement correction coefficients after iterative optimization, and return the step of calculating the measured temperature related to the calibration data corresponding to the device status information under the temperature measurement correction coefficient of each candidate according to a predetermined calculation method;

[0218] The determination submodule is used to determine the calibrated temperature correction coefficient based on the current candidate temperature correction coefficients in response to the fulfillment of the iteration termination condition.

[0219] Optionally, the iterative submodule is specifically used for:

[0220] For each candidate temperature measurement correction factor, based on the temperature measurement temperature formed by the calibration data corresponding to the device status information under the candidate temperature measurement correction factor, and the actual temperature in the calibration data corresponding to the device status information, calculate the loss value of the temperature difference corresponding to the candidate temperature measurement correction factor.

[0221] Based on the loss value of temperature difference corresponding to each candidate temperature correction coefficient, a second number of candidate temperature correction coefficients are selected from the current first number of candidate temperature correction coefficients; wherein, the loss value of temperature difference corresponding to the second number of candidate temperature correction coefficients is less than the loss value of temperature difference corresponding to the other temperature correction coefficients; wherein, the other temperature correction coefficients are parameters other than the second number of candidate temperature correction coefficients from the current first number of candidate temperature correction coefficients.

[0222] The selected second number of candidate temperature measurement correction coefficients are adjusted to obtain the first number of candidate temperature measurement correction coefficients after iterative optimization.

[0223] Optionally, the condition for satisfying the iteration termination includes:

[0224] Satisfy any one of the predetermined conditions;

[0225] The predetermined conditions include: the first condition and the second condition;

[0226] The first condition includes: among the current candidate temperature measurement correction coefficients, there exists a specified temperature measurement correction coefficient; wherein, the loss value of the temperature difference corresponding to the specified temperature measurement correction coefficient is less than a predetermined loss value, and under the specified temperature measurement correction coefficient, the difference between the measured temperature related to the calibration data corresponding to the device status information and the corresponding actual temperature is less than a predetermined threshold.

[0227] The second condition includes: the number of iterations reaches a predetermined number;

[0228] Accordingly, in response to satisfying the iteration termination condition, determining the calibrated temperature correction coefficient based on the current candidate temperature correction coefficients includes:

[0229] In response to the fulfillment of the first condition, the specified temperature measurement correction factor is determined as the calibrated temperature measurement correction factor; or...

[0230] In response to the second condition being met, the candidate temperature correction coefficient with the smallest loss value for temperature difference is selected from the current candidate temperature correction coefficients to obtain the calibrated temperature correction coefficient.

[0231] Optionally, any temperature measurement correction factor includes multiple sub-coefficients, and the order of the multiple sub-coefficients in different temperature measurement correction factors is the same;

[0232] The parameter adjustment process includes:

[0233] Genetic manipulation, crossover manipulation, and / or mutation manipulation;

[0234] The genetic treatment includes:

[0235] Retain the second number of candidate temperature measurement correction coefficients;

[0236] The cross-processing includes: swapping the sub-coefficients with the same sorting position among the second number of candidate temperature measurement correction coefficients;

[0237] The mutation processing includes: adjusting the sub-coefficients in the second number of candidate temperature measurement correction coefficients respectively using a predetermined mutation coefficient.

[0238] Optionally, any temperature measurement correction factor may include multiple sub-factors;

[0239] The disturbance submodule is specifically used for:

[0240] According to a specified perturbation method, the multiple sub-coefficients in the initial temperature measurement correction coefficients of the infrared temperature measurement device are perturbed to obtain a first number of candidate temperature measurement correction coefficients; wherein, the specified perturbation method includes: a perturbation method of adding to a random number, and / or a perturbation method of multiplying by a random coefficient.

[0241] Optionally, the device further includes a rejection module for:

[0242] Remove calibration data that is considered dirty data from multiple calibration data sets;

[0243] Among them, any calibration data belonging to dirty data is data that does not meet any of the specified conditions; wherein, each specified condition includes: a first type of condition that a single calibration data needs to meet, and a second type of condition that a single calibration data needs to meet with other calibration data; the first type of condition is a condition about the magnitude of the parameter value, and the second type of condition is a condition about the changing trend of the parameter values ​​of multiple parameters that have a correlation relationship.

[0244] Based on the above method embodiments, this application also provides a temperature measuring device applied to an infrared temperature measuring equipment, wherein the infrared temperature measuring equipment is a device whose parameters have been calibrated according to the above-described parameter calibration method for infrared temperature measuring equipment; such as Figure 6 As shown, the device includes:

[0245] The second acquisition module 610 is used to acquire the parameter values ​​of various temperature measurement parameters obtained by measuring the temperature of the target object in response to the temperature measurement operation of the target object.

[0246] The third acquisition module 620 is used to acquire the device status information when measuring the temperature of the target object, as the target device status information;

[0247] The second determining module 630 is used to determine the calibrated temperature correction coefficient corresponding to the target device status information based on the status information of each device stored in the infrared temperature measuring device and the corresponding calibrated temperature correction coefficient.

[0248] The third determining module 640 is used to determine the temperature of the target object based on the parameter values ​​of each obtained temperature measurement parameter and the calibrated temperature measurement correction coefficient corresponding to the target device status information.

[0249] In the temperature measurement method provided in this application, when the infrared thermometer measures the temperature of a target object, it does not directly select a fixed temperature correction coefficient. Instead, it considers the influence of the device status on the temperature measurement, thereby obtaining the device status information of the infrared thermometer at the time of testing as the target device status information, and using the calibrated temperature correction coefficient corresponding to the target device status information to calculate the temperature. Therefore, the temperature measurement method provided in this application considers the influence of the device status on the temperature measurement and selects a matching calibrated temperature correction coefficient for temperature calculation. Thus, compared to using a fixed temperature correction coefficient, it can improve the accuracy of the infrared thermometer.

[0250] This application also provides an electronic device, such as... Figure 7 As shown, it includes:

[0251] Memory 701 is used to store computer programs;

[0252] The processor 702, when executing the program stored in the memory 701, implements the parameter calibration method of any of the infrared temperature measuring devices described above.

[0253] Furthermore, the aforementioned electronic device may also include a communication bus and / or a communication interface, with the processor 702, the communication interface, and the memory 701 communicating with each other via the communication bus.

[0254] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0255] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0256] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0257] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0258] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores a computer program. When the computer program is executed by a processor, it implements the parameter calibration method of any of the infrared temperature measuring devices described above, or implements any of the temperature measuring methods described above.

[0259] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the parameter calibration method of any of the infrared temperature measuring devices described in the above embodiments, or to implement any of the temperature measuring methods described.

[0260] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a solid-state drive (SSD), etc.

[0261] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0262] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0263] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A parameter calibration method for an infrared temperature measuring device, characterized in that, The method includes: Acquire multiple calibration data points; each calibration data point includes: the actual temperature of a calibration object, and the parameter values ​​of each temperature measurement parameter obtained by measuring the temperature of the calibration object using an infrared thermometer, as well as the equipment status information when measuring the temperature of the calibration object; From the multiple calibration data obtained, determine the calibration data corresponding to each device status information; wherein, the calibration data corresponding to each device status information is each calibration data containing that device status information; For each device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated based on the calibration data corresponding to the device status information to obtain the calibrated temperature measurement correction coefficient corresponding to the device status information; wherein, the calibration process is used to ensure that the temperature measured based on the calibrated temperature measurement correction coefficient corresponding to the device status information and the parameter values ​​of the temperature measurement parameters in the corresponding calibration data matches the actual temperature in the corresponding calibration data. The status information of each device and the corresponding calibrated temperature correction coefficient are stored in the infrared temperature measuring device in association to complete the calibration of the temperature correction coefficient of the infrared temperature measuring device.

2. The method according to claim 1, characterized in that, The number of calibration objects indicated in the multiple calibration data is multiple, and the multiple calibration objects are isothermal objects with different temperatures; The methods for measuring the temperature of each calibration object using infrared thermometers include: The calibration material is placed in environments with different temperatures, and after the infrared thermometer and the environment reach thermal equilibrium, the temperature is measured by the infrared thermometer.

3. The method according to claim 1, characterized in that, The step of determining the calibration data corresponding to each device status information from multiple acquired calibration data includes: Determine the storage space for device status information; Each piece of calibration data is traversed. When a piece of calibration data is encountered, it is analyzed whether the device status information in the calibration data exists in the storage space. If it exists, the traversal of the next piece of calibration data continues. If it does not exist, the device status information in the calibration data is stored in the storage space. In response to the completion of the traversal of multiple calibration data, for each device status information currently stored in the storage space, the calibration data corresponding to the device status information is determined from the multiple calibration data obtained.

4. The method according to any one of claims 1-3, characterized in that, For each device status information, based on the calibration data corresponding to that device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated to obtain the calibrated temperature measurement correction coefficient corresponding to that device status information, including: For each device status information, based on the calibration data corresponding to the device status information, the temperature measurement correction coefficient of the infrared temperature measuring device is calibrated according to a predetermined calibration method to obtain the calibrated temperature measurement correction coefficient corresponding to the device status information. The predetermined calibration methods include: a calibration method based on forward fitting, a calibration method based on parameter iterative optimization, or a calibration method based on a neural network model.

5. The method according to claim 4, characterized in that, When the calibration method includes a parameter iteration optimization-based calibration method, based on the calibration data corresponding to the device status information, the temperature correction coefficient of the infrared thermometer is calibrated according to a predetermined calibration method to obtain the calibrated temperature correction coefficient corresponding to the device status information, including: The initial temperature correction coefficient of the infrared temperature measuring device is perturbed to obtain a first number of candidate temperature correction coefficients. For each candidate temperature correction factor, the temperature related to the calibration data corresponding to the device status information is calculated according to a predetermined calculation method. The predetermined calculation method includes: performing temperature calculation based on the candidate temperature correction factor and the parameter values ​​of the temperature measurement parameters in the calibration data corresponding to the device status information. Based on the measured temperature related to the calibration data corresponding to the obtained device status information, and the actual temperature in the calibration data corresponding to the device status information, the first number of candidate temperature measurement correction coefficients are iteratively optimized to obtain the first number of candidate temperature measurement correction coefficients after iterative optimization. Then, for each candidate temperature measurement correction coefficient, the steps of calculating the measured temperature related to the calibration data corresponding to the device status information under the candidate temperature measurement correction coefficient according to the predetermined calculation method are returned. In response to the fulfillment of the iteration termination condition, the calibrated temperature correction coefficient is determined based on the current candidate temperature correction coefficients.

6. The method according to claim 5, characterized in that, The step of iteratively optimizing the first number of candidate temperature measurement correction coefficients based on the measured temperature related to the calibration data corresponding to the obtained device status information, and the actual temperature in the calibration data corresponding to the device status information, to obtain the iteratively optimized first number of candidate temperature measurement correction coefficients, including: For each candidate temperature measurement correction factor, based on the temperature measurement temperature formed by the calibration data corresponding to the device status information under the candidate temperature measurement correction factor, and the actual temperature in the calibration data corresponding to the device status information, calculate the loss value of the temperature difference corresponding to the candidate temperature measurement correction factor. Based on the loss value of temperature difference corresponding to each candidate temperature correction coefficient, a second number of candidate temperature correction coefficients are selected from the current first number of candidate temperature correction coefficients; wherein, the loss value of temperature difference corresponding to the second number of candidate temperature correction coefficients is less than the loss value of temperature difference corresponding to the other temperature correction coefficients; wherein, the other temperature correction coefficients are parameters other than the second number of candidate temperature correction coefficients from the current first number of candidate temperature correction coefficients. The selected second number of candidate temperature measurement correction coefficients are adjusted to obtain the first number of candidate temperature measurement correction coefficients after iterative optimization.

7. The method according to claim 6, characterized in that, The iteration termination conditions include: Satisfy any one of the predetermined conditions; The predetermined conditions include: the first condition and the second condition; The first condition includes: among the current candidate temperature measurement correction coefficients, there exists a specified temperature measurement correction coefficient; wherein, the loss value of the temperature difference corresponding to the specified temperature measurement correction coefficient is less than a predetermined loss value, and under the specified temperature measurement correction coefficient, the difference between the measured temperature related to the calibration data corresponding to the device status information and the corresponding actual temperature is less than a predetermined threshold. The second condition includes: the number of iterations reaches a predetermined number; Accordingly, in response to satisfying the iteration termination condition, determining the calibrated temperature correction coefficient based on the current candidate temperature correction coefficients includes: In response to the fulfillment of the first condition, the specified temperature measurement correction factor is determined as the calibrated temperature measurement correction factor; or... In response to the second condition being met, the candidate temperature correction coefficient with the smallest loss value for temperature difference is selected from the current candidate temperature correction coefficients to obtain the calibrated temperature correction coefficient.

8. The method according to claim 6, characterized in that, Any temperature measurement correction factor includes multiple sub-factors, and the order of the multiple sub-factors in different temperature measurement correction factors is the same; The parameter adjustment process includes: Genetic manipulation, crossover manipulation, and / or mutation manipulation; The genetic treatment includes: Retain the second number of candidate temperature measurement correction coefficients; The cross-processing includes: swapping the sub-coefficients with the same sorting position among the second number of candidate temperature measurement correction coefficients; The mutation processing includes: adjusting the sub-coefficients in the second number of candidate temperature measurement correction coefficients respectively using a predetermined mutation coefficient.

9. The method according to claim 5, characterized in that, Any temperature measurement correction factor includes multiple sub-factors; The initial temperature correction coefficient of the infrared temperature measuring device is perturbed to obtain a first number of candidate temperature correction coefficients, including: According to a specified perturbation method, the multiple sub-coefficients in the initial temperature measurement correction coefficients of the infrared temperature measurement device are perturbed to obtain a first number of candidate temperature measurement correction coefficients; wherein, the specified perturbation method includes: a perturbation method of adding to a random number, and / or a perturbation method of multiplying by a random coefficient.

10. The method according to any one of claims 1-3, characterized in that, After acquiring multiple calibration data points, and before determining the calibration data corresponding to each device status information from the acquired multiple calibration data points, the method further includes: Remove calibration data that is considered dirty data from multiple calibration data sets; Among them, any calibration data belonging to dirty data is data that does not meet any of the specified conditions; wherein, each specified condition includes: a first type of condition that a single calibration data needs to meet, and a second type of condition that a single calibration data needs to meet with other calibration data; the first type of condition is a condition about the magnitude of the parameter value, and the second type of condition is a condition about the changing trend of the parameter values ​​of multiple parameters that have a correlation relationship.

11. A temperature measurement method, characterized in that, The method is applied to an infrared temperature measuring device, wherein the infrared temperature measuring device is a device whose parameters have been calibrated according to the parameter calibration method described in any one of claims 1-10; the method includes: In response to the temperature measurement operation on the target object, the parameter values ​​of each temperature measurement parameter obtained from the temperature measurement of the target object are acquired; Obtain the device status information when measuring the temperature of the target object, and use it as the target device status information; Based on the status information of each device stored in the infrared temperature measurement device and the corresponding calibrated temperature measurement correction coefficient, the calibrated temperature measurement correction coefficient corresponding to the status information of the target device is determined. Based on the obtained parameter values ​​of each temperature measurement parameter and the calibrated temperature measurement correction coefficient corresponding to the target device status information, the temperature of the target object is determined.

12. A parameter calibration device for an infrared temperature measurement equipment, characterized in that, The device includes: The first acquisition module is used to acquire multiple calibration data; each calibration data includes: the actual temperature of a calibration object, and the parameter values ​​of each temperature measurement parameter obtained by measuring the temperature of the calibration object through an infrared temperature measuring device, as well as the device status information when measuring the temperature of the calibration object; The first determining module is used to determine the calibration data corresponding to each device status information from the multiple calibration data obtained; wherein, the calibration data corresponding to each device status information is each calibration data containing that device status information; The calibration module is used to calibrate the temperature correction coefficient of the infrared thermometer based on the calibration data corresponding to each device status information, so as to obtain the calibrated temperature correction coefficient corresponding to the device status information; wherein, the calibration process is used to ensure that the temperature calculated based on the calibrated temperature correction coefficient corresponding to the device status information and the parameter values ​​of the temperature measurement parameters in the corresponding calibration data matches the actual temperature in the corresponding calibration data. The storage module is used to store the status information of each device and the corresponding calibrated temperature correction coefficient in the infrared temperature measuring device in association, so as to complete the calibration of the temperature correction coefficient of the infrared temperature measuring device.

13. A temperature measuring device, characterized in that, The device is applied to an infrared temperature measuring device, wherein the infrared temperature measuring device is a device whose parameters have been calibrated according to the parameter calibration method described in any one of claims 1-10; the device comprises: The second acquisition module is used to acquire the parameter values ​​of various temperature measurement parameters obtained from the temperature measurement of the target object in response to the temperature measurement operation of the target object. The third acquisition module is used to acquire the device status information when the target object is being measured, as the target device status information. The second determining module is used to determine the calibrated temperature correction coefficient corresponding to the target device status information based on the status information of each device stored in the infrared temperature measuring device and the corresponding calibrated temperature correction coefficient. The third determining module is used to determine the temperature of the target object based on the parameter values ​​of each obtained temperature measurement parameter and the calibrated temperature measurement correction coefficient corresponding to the target device status information.

14. An electronic device, characterized in that, include: Memory, used to store computer programs; The processor, when executing a program stored in the memory, implements the parameter calibration method of the infrared temperature measuring device according to any one of claims 1-10.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the parameter calibration method of the infrared temperature measuring device according to any one of claims 1-10, or the temperature measuring method according to claim 11.

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