Emissivity determination method, device, equipment and program product

Abstract

The invention relates to the technical field of data processing, in particular to an emissivity determination method and device, equipment and a program product. The method comprises the following steps: acquiring infrared temperature measurement nephograms respectively acquired from a target to-be-measured area at a plurality of continuous acquisition moments; starting from the infrared temperature measurement cloud picture corresponding to the first acquisition moment, obtaining energy conservation residual errors in the heat conduction process from the heating wire to the substrate based on the infrared temperature measurement cloud picture in sequence; and under the condition that the energy conservation residual corresponding to the second acquisition moment is larger than or equal to the energy conservation residual corresponding to the first acquisition moment, the tested heating wire emissivity corresponding to the second acquisition moment is determined as the target heating wire emissivity, and the first acquisition moment and the second acquisition moment are two sequentially adjacent acquisition moments. According to the invention, the heating wire emissivity of the heating wire can be determined more accurately, so that the accuracy of infrared temperature measurement is ensured.

Description

Technical Field

[0001] This application relates to the field of data processing technology, specifically to a method, apparatus, device, and program product for determining emissivity. Background Technology

[0002] In the electronic atomization industry, the temperature distribution characteristics vary significantly due to the different arrangements of heating wires within the heating element. For example, the highest temperature point inside the element cannot be determined, and the heating wires are generally very small, making it difficult to effectively arrange contact measurement points for temperature measurement. Therefore, infrared thermography is required to obtain the temperature field across the entire surface of the heating element.

[0003] However, infrared thermometry infers the surface temperature of an object by measuring its thermal radiation, which is affected by the object's emissivity. For the heating element being measured, the heating wire and electrodes are formed on the surface of a ceramic substrate through a co-sintering and thick-film printing process. The material used in this process is a metallide paste, which has a lower emissivity than the substrate, and different types of metallites have different emissivity. Furthermore, the emissivity of the heating wire is difficult to determine due to the influence of the sintering and printing processes. Consequently, the measured temperature in the area where the heating wire has a very low emissivity is underestimated, and the significant difference in emissivity at the interface between the heating wire and the substrate also causes temperature distortion. Therefore, inaccurately obtained heating wire emissivity significantly impacts the reliability and accuracy of infrared thermometry. Summary of the Invention

[0004] Based on the defects and shortcomings of the prior art, this application proposes a method, apparatus, equipment and program product for determining emissivity, which can more accurately determine the emissivity of the heating wire, thereby ensuring the accuracy of infrared temperature measurement.

[0005] According to a first aspect of the present application, an emissivity determination method is provided, comprising: acquiring infrared thermograms of a target area to be tested collected at multiple consecutive acquisition times, wherein the target area to be tested includes a heating wire and a substrate, the heating wire being arranged on the substrate, and the infrared thermometer being configured with different test heating wire emissivity at different acquisition times; starting from the infrared thermogram corresponding to the first acquisition time, sequentially acquiring the energy conservation residual during the heat conduction process from the heating wire to the substrate based on the infrared thermogram; if the energy conservation residual corresponding to the second acquisition time is greater than or equal to the energy conservation residual corresponding to the first acquisition time, determining the test heating wire emissivity corresponding to the second acquisition time as the target heating wire emissivity, wherein the first acquisition time and the second acquisition time are two sequentially adjacent acquisition times.

[0006] According to the emissivity determination method provided in the first aspect of the present application, the infrared thermography cloud map includes point temperature values ​​at multiple pixels corresponding to the target area to be measured; the step of obtaining the energy conservation residual during the heat conduction process from the heating wire to the substrate based on the infrared thermography cloud map includes: determining the boundary line between the heating wire and the substrate in the infrared thermography cloud map, wherein the boundary line is a closed curve; based on the boundary line, determining the heating wire temperature domain corresponding to the heating wire, and the substrate temperature determination domain and substrate temperature calculation domain corresponding to the substrate in the infrared thermography cloud map, wherein the accuracy of the point temperature value in the substrate temperature determination domain is greater than the accuracy of the point temperature value in the substrate temperature calculation domain; and calculating the energy conservation residual during the heat conduction process from the heating wire to the substrate based on the heating wire temperature domain, the substrate temperature determination domain, and the substrate temperature calculation domain.

[0007] According to the emissivity determination method provided in the first aspect of the present application, the step of calculating the energy conservation residual during the heat conduction process from the heating wire to the substrate based on the heating wire temperature domain, the substrate temperature determination domain, and the substrate temperature calculation domain includes: for any first pixel in the innermost layer of the substrate temperature determination domain, determining the n nearest neighboring pixels to the first pixel, wherein the innermost layer of the substrate temperature determination domain includes each pixel located in the substrate temperature determination domain and adjacent to the substrate temperature calculation domain, n is a positive integer, and the neighboring pixels are located in the substrate temperature determination domain or the substrate temperature calculation domain; the point temperature value of each first pixel and the point temperature value of the corresponding neighboring pixels are input into the energy conservation equation for calculation to obtain the energy conservation residual.

[0008] According to the emissivity determination method provided in the first aspect of the embodiments of this application, for each of the neighboring pixels located in the substrate temperature calculation domain, the following processing is performed: a second pixel closest to the neighboring pixel is determined in the substrate temperature determination domain, and a third pixel closest to the neighboring pixel is determined in the heating wire temperature domain; the point temperature value of the second pixel and the point temperature value of the third pixel are interpolated, and the interpolation result is used as the point temperature value of the neighboring pixel.

[0009] According to the emissivity determination method provided in the first aspect of the present application, the energy conservation equation is obtained by discretizing the energy conservation formula based on the innermost layer of the matrix temperature determination domain.

[0010] According to the emissivity determination method provided in the first aspect of the present application, the step of obtaining infrared thermograms of a target area to be tested acquired at multiple consecutive acquisition times includes: at each acquisition time, acquiring the original thermogram of the heating element to be tested by configuring the infrared thermogram device corresponding to the emissivity of the heating wire, wherein the heating element to be tested includes the target area to be tested; filtering the point temperature values ​​of each pixel in the original thermogram of the first acquisition time by using a critical temperature value to obtain the initial thermogram of the first acquisition time, and acquiring the location information of the target area to be tested; based on the location information of the target area to be tested, acquiring the initial thermogram of each acquisition time other than the first acquisition time; and filtering each initial thermogram to obtain the infrared thermogram of each acquisition time.

[0011] According to the emissivity determination method provided in the first aspect of the present application, determining the boundary line between the heating wire and the substrate in the infrared thermography cloud image includes: performing convolution processing on the infrared thermography cloud image to obtain the gradient index corresponding to each pixel in the infrared thermography cloud image; based on the gradient index, selecting at least one maximum point from each pixel point through non-maximum suppression processing; and performing numerical point refinement and padding processing on each maximum point to obtain the boundary line.

[0012] According to a second aspect of the embodiments of this application, an emissivity determination device is provided, comprising: an image acquisition module, configured to acquire infrared thermograms of a target area to be measured at multiple consecutive acquisition times, wherein the target area to be measured includes a heating wire and a substrate, the heating wire being arranged on the substrate, and the infrared thermometer being configured with different test heating wire emissivity at different acquisition times; an image processing module, configured to acquire, starting from the infrared thermogram corresponding to the first acquisition time, the energy conservation residual during the heat conduction process from the heating wire to the substrate based on the infrared thermogram; and an emissivity determination module, configured to determine the emissivity of the test heating wire corresponding to the second acquisition time as the target heating wire emissivity if the energy conservation residual corresponding to the second acquisition time is greater than or equal to the energy conservation residual corresponding to the first acquisition time, wherein the first acquisition time and the second acquisition time are two sequentially adjacent acquisition times.

[0013] According to a third aspect of the present application, an electronic device is provided, comprising: a memory and a processor; the memory is connected to the processor and is used to store a program; the processor is used to implement the emissivity determination method as described in the first aspect by running the program in the memory.

[0014] According to a fourth aspect of the embodiments of this application, a computer program product is provided, including computer program instructions; the computer program instructions, when executed by a processor, cause the processor to perform the emissivity determination method as described in the first aspect. Optionally, the computer program may be stored in a readable storage medium of a computer device or in the cloud; the processor of the computer device reads the computer program from the readable storage medium or the cloud.

[0015] In this embodiment, infrared thermograms of the target area to be tested are acquired at multiple consecutive acquisition times. The target area to be tested includes a heating wire and a substrate, with the heating wire arranged on the substrate. The infrared thermometer is configured with different test heating wire emissivity at different acquisition times. Starting from the infrared thermogram corresponding to the first acquisition time, the energy conservation residual during the heat conduction process from the heating wire to the substrate is acquired sequentially based on the infrared thermogram. If the energy conservation residual corresponding to the second acquisition time is greater than or equal to the energy conservation residual corresponding to the first acquisition time, the test heating wire emissivity corresponding to the second acquisition time is determined to be the target heating wire emissivity. The first acquisition time and the second acquisition time are two sequentially adjacent acquisition times. In the above process, infrared thermograms from multiple consecutive acquisition times are used to configure different test heating wire emissivities for the infrared thermometer at different acquisition times. Energy conservation is verified based on the principle of heat conduction. When the energy conservation residual at the second acquisition time is greater than or equal to the energy conservation residual at the first acquisition time, it indicates that the energy conservation residual is beginning to converge. At this point, the test heating wire emissivity is closer to the true emissivity of the heating wire. Therefore, the test heating wire emissivity at the second acquisition time is taken as the target heating wire emissivity. This target heating wire emissivity is more accurate, and thus, when infrared thermometry is performed based on this target heating wire emissivity, more accurate temperature measurement data can be obtained. Attached Figure Description

[0016] 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 embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0017] Figure 1 One of the flowcharts for an emissivity determination method provided in this application embodiment;

[0018] Figure 2 An example diagram of an original temperature measurement cloud image provided in an embodiment of this application;

[0019] Figure 3This is a schematic diagram of a cloud image capture operation provided in an embodiment of this application;

[0020] Figure 4 An example diagram of a boundary line provided for an embodiment of this application;

[0021] Figure 5 An example diagram of a "rhombus" field provided for embodiments of this application;

[0022] Figure 6 An example diagram illustrating the temperature determination domain of a heating wire provided in an embodiment of this application;

[0023] Figure 7 An example diagram of a heating wire temperature calculation domain is provided for an embodiment of this application;

[0024] Figure 8 An example diagram of a matrix temperature determination domain provided in an embodiment of this application;

[0025] Figure 9 This is one of the schematic diagrams of non-maximum suppression processing provided in the embodiments of this application;

[0026] Figure 10 This is a second schematic diagram of a non-maximum suppression processing method provided in an embodiment of this application;

[0027] Figure 11 This is the third schematic diagram of a non-maximum suppression processing provided in the embodiments of this application;

[0028] Figure 12 This is the fourth schematic diagram of a non-maximum suppression processing method provided in the embodiments of this application;

[0029] Figure 13 A second schematic flowchart illustrating an emissivity determination method provided in an embodiment of this application;

[0030] Figure 14 A block diagram of an emissivity determination device provided in an embodiment of this application;

[0031] Figure 15 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0032] 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 without creative effort are within the scope of protection of this application.

[0033] Exemplary methods

[0034] To address the problem of distorted infrared thermometry data caused by the small and difficult-to-determine emissivity of the heating wire on the heating element under test, an emissivity determination method is proposed to determine a more accurate emissivity of the heating wire.

[0035] In one embodiment, such as Figure 1 As shown, the process steps for implementing the emissivity determination method include:

[0036] Step 101: Obtain infrared thermograms of the target area under test at multiple consecutive acquisition times. The target area under test includes a heating wire and a substrate. The heating wire is arranged on the substrate. The infrared thermometer is configured with different test heating wire emissivity at different acquisition times.

[0037] In this embodiment, when using an infrared thermometer to perform infrared temperature measurement on the heating element under test, the infrared thermometer is input with voltage and power matching the heating element under test to perform a heating and temperature rise test on the heating element under test. During the heating period, the emissivity of the test heating wire configured in the infrared thermometer varies at different acquisition times. The infrared thermometer collects the overall surface temperature field data of the heating element under test at multiple consecutive acquisition times, i.e., the original temperature cloud map. After obtaining the original temperature cloud map, the infrared temperature cloud map corresponding to the target test area can be obtained based on the original temperature cloud map. This allows for targeted analysis of the heating wire based on the infrared temperature cloud map. The target test area can be extracted from a larger original temperature area using preset conditions such as a fixed-size window and a temperature critical value, facilitating subsequent correction processing, reducing computational load, and improving correction efficiency. Optionally, the substrate on which the heating wire is arranged on the heating element under test can be a ceramic substrate. Optionally, the heating wire can be a heating resistance wire.

[0038] Step 102: Starting from the infrared temperature measurement cloud image corresponding to the first acquisition time, obtain the energy conservation residual during the heat conduction process from the heating wire to the substrate based on the infrared temperature measurement cloud image.

[0039] In this embodiment, the overall heating process of the heating element under test must satisfy the conservation of heat transfer, that is, the Joule heat generated by the heating wire should be equal to the enthalpy increase of the heating wire itself and its thermal conductivity to the substrate. The thermal conductivity of the heating wire to the substrate can be reflected by the temperature rise of the substrate and its external thermal conductivity. Therefore, this application adopts the principle of heat conduction to obtain the energy conservation residual during the heat conduction process from the heating wire to the substrate, and determines the more accurate emissivity of the target heating wire based on the energy conservation residual.

[0040] Step 103: If the energy conservation residual at the second acquisition time is greater than or equal to the energy conservation residual at the first acquisition time, determine the emissivity of the test heating wire at the second acquisition time as the target heating wire emissivity. Here, the first acquisition time and the second acquisition time are two sequentially adjacent acquisition times.

[0041] In this embodiment, if the energy conservation residual corresponding to the second acquisition time is greater than or equal to the energy conservation residual corresponding to the first acquisition time, it indicates that the energy conservation residual at the second acquisition time has reached the convergence criterion. Then, the emissivity of the test heating wire corresponding to the second acquisition time can be determined as the emissivity of the target heating wire, which is more realistic and reasonable.

[0042] A detailed analysis of the principle of infrared thermometry is provided. The principle of infrared thermometry is to first calculate the temperature of an object assuming it is a blackbody by examining the magnitude of the radiation emitted by the object. Then, based on the object's emissivity set in the infrared thermometry device and relevant radiation parameters of the surrounding environment, the object's true temperature is calculated; this is the object's infrared measured temperature.

[0043] Optionally, an infrared thermal imager temperature measurement mathematical model that is widely used and highly reliable can be used for infrared temperature measurement:

[0044]

[0045] Where T0 is the infrared temperature of the surface of the object being measured; ε is the emissivity of the object; τ a ε is atmospheric transmittance; a Atmospheric emissivity; T B T represents the surface temperature of the object being measured as a blackbody. u The ambient temperature; T a The atmospheric temperature is represented by n, which is 3.9889.

[0046] As can be seen from equation (1) above, given the known parameters of the laboratory measurement environment, such as atmospheric transmittance, atmospheric emissivity, ambient temperature, and atmospheric temperature, T can first be calculated from the existing temperature measurement data. B Then, different test values ​​for the emissivity of different objects can be input, and corresponding infrared measurement temperatures can be obtained. Finally, through iterative calculations at different temperature acquisition times, the emissivity corresponding to the object's reasonable temperature value can be obtained.

[0047] In this embodiment, the heating wire is the object mentioned above. Through relevant iterative calculations, a more accurate and reasonable target heating wire emissivity is obtained.

[0048] In one embodiment, acquiring infrared thermograms of the target area to be tested at multiple consecutive acquisition times includes: at each acquisition time, acquiring an original thermogram of the heating element to be tested by configuring an infrared thermometer with a corresponding test heating wire emissivity, wherein the heating element to be tested includes the target area to be tested; filtering the point temperature values ​​of each pixel in the original thermogram of the first acquisition time by a critical temperature value to obtain an initial thermogram of the first acquisition time, and acquiring the location information of the target area to be tested; based on the location information of the target area to be tested, acquiring an initial thermogram of the target area to be tested at each acquisition time other than the first acquisition time; and filtering each initial thermogram to obtain an infrared thermogram of the target area to be tested at each acquisition time.

[0049] In this embodiment, for the heat-generating element under test, the original temperature measurement cloud map obtained by the infrared temperature measurement device is as follows: Figure 2 The example image shown is of the original temperature measurement cloud map; firstly, the initial temperature measurement cloud map is extracted from the original temperature measurement cloud map using the critical temperature value, as shown below. Figure 3 The diagram shown illustrates the cloud image capture operation, obtaining an example of an initial temperature measurement cloud image. Then, the initial temperature measurement cloud image is filtered and noise-reduced to avoid the influence of noise on the processing, thus obtaining the infrared temperature measurement cloud image.

[0050] In this embodiment, for the heating element under test, an appropriate voltage and power are input to test the heating temperature rise of the heating element under test. An infrared thermometer is used for recording. Optionally, when the substrate of the heating element under test is a ceramic substrate, the emissivity value of the infrared thermometer is set to the emissivity of the ceramic substrate. When a relatively obvious temperature field forms on the surface of the heating element under test in the middle of the time period, the overall surface temperature field data of the heating element under test is recorded at multiple consecutive acquisition moments within a time period, i.e., the original temperature cloud maps acquired at each of the multiple consecutive acquisition moments are obtained. Then, the initial temperature cloud map corresponding to the target area under test is extracted from the first acquisition moment of that time period. For example, if the duration of a time period is 5 seconds, then the original temperature cloud maps at six acquisition moments—0s, 1s, 2s, 3s, 4s, and 5s—are recorded, and the initial temperature cloud map corresponding to the target area under test is extracted from the original temperature cloud map at 0s.

[0051] In this embodiment, for the first data acquisition moment, an initial temperature measurement cloud map is captured from the original temperature measurement cloud map. First, a critical temperature value is set. For each pixel in the original temperature measurement cloud map, starting from the left and right ends of each row of pixels, the left and right column numbers of the corresponding pixels whose temperature values ​​are greater than the critical temperature value are calculated, and the minimum and maximum values ​​of the left and right column numbers are determined. Starting from the top and bottom of each column of pixels, the top and bottom row numbers of the corresponding pixels whose temperature values ​​are greater than the critical temperature value are calculated, and the minimum and maximum values ​​of the top and bottom row numbers are output. Based on the minimum and maximum values ​​of the left and right column numbers, the top and bottom row numbers, and the maximum values ​​of the bottom row numbers, the top, bottom, left, and right positions of the initial temperature measurement cloud map are obtained. The critical temperature value can be adjusted through multiple adjustments and observation of the captured portion until the initial temperature measurement cloud map that needs correction can be captured.

[0052] In this embodiment, the location information of the target area to be measured includes the upper, lower, left, and right positions. After the upper, lower, left, and right positions of the original temperature measurement cloud map at the first acquisition time are determined, the original temperature measurement cloud map at each acquisition time other than the first acquisition time can be cropped based on these upper, lower, left, and right positions to obtain the initial temperature measurement cloud map at each acquisition time.

[0053] In one embodiment, each initial temperature measurement cloud image is filtered to obtain an infrared temperature measurement cloud image at each acquisition time, including: for each infrared temperature measurement cloud image, performing median filtering on the initial temperature measurement cloud image to obtain intermediate temperature measurement data, and performing Gaussian filtering on the intermediate temperature measurement data to obtain an infrared temperature measurement cloud image.

[0054] In this embodiment, the noise sources and components of the infrared temperature measurement data are mainly Gaussian noise and salt-and-pepper noise. Gaussian noise refers to a type of noise whose probability density function follows a Gaussian distribution. Salt-and-pepper noise, also known as impulse noise, randomly changes the pixel values ​​in the image and is a black-and-white noise generated during camera, transmission channel, and decoding processes. This application performs median filtering and Gaussian filtering for noise reduction against Gaussian and salt-and-pepper noise respectively. The point temperature value corresponding to each pixel in the infrared temperature measurement cloud image can be represented in the form of an infrared temperature measurement matrix, thereby reducing the difficulty of subsequent processing and calculation.

[0055] In this embodiment, each initial temperature measurement contour image is filtered. The filtering process for any initial temperature measurement contour image is as follows:

[0056] Since the original temperature measurement cloud image output by infrared temperature measurement is generally small in size after being cropped, the size of the filtering window used for filtering can be adjusted according to the actual situation and needs. Optionally, the size of the filtering window can be 3×3.

[0057] First, median filtering is applied to the initial temperature cloud map. For median filtering, an adaptive optimization method is implemented. Specifically, during the median filtering operation, the value of the object to be filtered is first judged, and then the filtering result is output based on the judgment result. Specifically, when the value of the object to be filtered is very close to the maximum or minimum value within the filtering window, the median value within the filtering window is output; otherwise, the value of the object itself is output. The mathematical description is as follows:

[0058] When the core of the filtering window coincides with pixel (j,k) in the initial temperature measurement cloud map (represented as a matrix) I(m×n), first calculate the maximum value of I within the filtering window. and minimum value

[0059]

[0060] When I(j,k) satisfies and At that time, there were:

[0061] I1(j,k)=I(j,k) (4)

[0062] Otherwise, we have:

[0063]

[0064] Where I1(j,k) represents the point temperature value of pixel (j,k) after median filtering, and median represents the median.

[0065] The above process uses the maximum value and minimum value The comparison process enables adaptive median filtering, which can filter out outliers whose values ​​are too large or too small compared to their surrounding values, while also maintaining normal data points without reducing the effective information in the data, thus helping to preserve details.

[0066] In this embodiment, Gaussian filtering is performed after median filtering. For Gaussian filtering, an adaptive optimization method is implemented. Specifically, during Gaussian filtering, the Gaussian kernel parameters within the filtering window are determined based on the relative magnitude of the standard deviation within the filtering window and the global standard deviation of the initial temperature measurement cloud map. The mathematical description is as follows:

[0067] The principle of generating a Gaussian filter matrix:

[0068] For a filter window consisting of r rows and c columns, the sequence of values ​​in the row direction is as follows:

[0069]

[0070] The data values ​​in the column are:

[0071]

[0072] The two-dimensional Gaussian function used in Gaussian filtering is:

[0073]

[0074] Where (x,y) are arbitrary two-dimensional variables, π and e are different hyperparameters, and σ is the Gaussian kernel parameter;

[0075] In summary, the resulting Gaussian filter matrix can be expressed as:

[0076]

[0077] Clearly, the value of the generated Gaussian kernel filter matrix is ​​closely related to the Gaussian kernel parameter σ, and different values ​​will result in significantly different Gaussian filter effects. In this embodiment, the adaptive Gaussian filtering method obtains the Gaussian kernel parameter σ by dividing the global maximum standard deviation of the initial temperature measurement cloud map by the standard deviation within the filtering window. Therefore, for regions with greater dispersion, a smaller Gaussian kernel standard deviation is used for filtering to suppress noise interference.

[0078] Specifically, the maximum standard deviation of the initial temperature measurement contour map (represented as a matrix) I1(m×n) after median filtering is defined as S. Imax :

[0079]

[0080] in The average value of all elements in I1(m×n) is calculated using the following formula:

[0081]

[0082] For the filter matrix G(r×c), assuming the core of the filter window is at point (j,k), the set of row indices and column indices of all elements within the filter window can be represented as:

[0083]

[0084]

[0085] Standard deviation of all elements within the filter window for:

[0086]

[0087] Within a filtering window with core (j,k) and size r×c, the generated Gaussian kernel parameter σ is:

[0088]

[0089] After determining the Gaussian filter matrix G, it is convolved with the initial temperature measurement cloud map (represented in matrix form) I(m×n). The output result is the Gaussian filtering noise reduction result, i.e., the Gaussian filtered infrared temperature measurement cloud map I2.

[0090] I2=I1※G (16).

[0091] In one embodiment, the infrared temperature measurement cloud map includes point temperature values ​​at multiple pixels corresponding to the target area to be measured. Based on the infrared temperature measurement cloud map, the energy conservation residual during the heat conduction process from the heating wire to the substrate is obtained, including: determining the boundary line between the heating wire and the substrate in the infrared temperature measurement cloud map, wherein the boundary line is a closed curve; based on the boundary line, determining the heating wire temperature domain corresponding to the heating wire, and the substrate temperature determination domain and substrate temperature calculation domain corresponding to the substrate in the infrared temperature measurement cloud map, wherein the accuracy of the point temperature value in the substrate temperature determination domain is greater than the accuracy of the point temperature value in the substrate temperature calculation domain; and calculating the energy conservation residual during the heat conduction process from the heating wire to the substrate based on the heating wire temperature domain, the substrate temperature determination domain, and the substrate temperature calculation domain.

[0092] In this embodiment, when verifying the energy conservation during heat conduction between the heating wire and the substrate, the verification process is achieved by using the point temperature values ​​of pixels in different regions corresponding to the heating wire and the substrate in the infrared thermography cloud image. Before dividing the heating wire temperature domain, the substrate temperature determination domain, and the substrate temperature calculation domain into different regions, the boundary line between the heating wire and the substrate is first determined in the infrared thermography cloud image, such as... Figure 4 The example diagram of the boundary lines is shown, and then each region is determined based on the boundary lines.

[0093] In this embodiment, based on the boundary line, the process of determining the heating wire temperature domain corresponding to the heating wire, and the substrate temperature determination domain and substrate temperature calculation domain corresponding to the substrate in the infrared thermography cloud map is as follows:

[0094] In one embodiment, the generated closed boundary line divides the infrared thermogram into two parts, which are visually easily distinguishable and referred to as the outer part and the inner part, respectively. The inner part inside the closed boundary line is the heating wire temperature domain. The substrate temperature domain is composed of the boundary line and the outer part outside the closed boundary line.

[0095] By applying overall edge judgment to both the substrate and the heating wire, the internal and edge regions of the heating wire temperature domain and the substrate temperature domain can be obtained separately, i.e., the temperature determination domain and the temperature calculation domain. The temperature measurement data in the temperature determination domain is reliable and valid, while the temperature measurement data in the temperature calculation domain is inaccurate due to the emissivity difference at the boundary between the two parts and requires correction. The edge judgment method is shown below:

[0096] For the heating wire temperature domain or the substrate temperature domain, taking the heating wire temperature domain as an example, for any point (i,j) within the heating wire temperature domain, a "rhombus" neighborhood search is performed around it. The "rhombus" neighborhood includes the two closest pixels in each of the top, bottom, left, and right directions of pixel point (i,j), and the closest pixel in each of the top-left, bottom-left, top-right, and bottom-right directions of pixel point (i,j). Figure 5 The diagram shown illustrates a "diamond-shaped" area, which includes... Figure 5 The area outlined in bold black boxes is defined as follows: If all pixels within the "diamond" neighborhood belong to the heating wire temperature domain, then pixel (i,j) is considered to be inside the heating wire and falls under the heating wire temperature determination domain. In practice, the final heating wire temperature determination domain is as follows: Figure 6 As shown. Conversely, if at least one pixel in the "diamond" neighborhood does not belong to the heating wire temperature domain, then pixel (i,j) belongs to the edge of the heating wire and is classified into the heating wire temperature calculation domain. In practice, the final heating wire temperature calculation domain is as follows: Figure 7 As shown.

[0097] Similarly, the "diamond" neighborhood method is also used to determine the interior and edges of the matrix. If all pixels within the "diamond" neighborhood belong to the matrix temperature domain, then pixel (i,j) is considered to belong to the interior of the matrix and falls under the matrix temperature determination domain. For example, the final matrix temperature determination domain is as follows: Figure 8 As shown. Conversely, if there is at least one pixel in the "diamond" neighborhood that does not belong to the matrix temperature domain, then pixel (i,j) belongs to the matrix edge and is classified into the matrix temperature calculation domain.

[0098] For the substrate, after obtaining the substrate temperature determination domain using edge detection, the point temperature value of each pixel in the substrate temperature determination domain at each acquisition time needs to be read as the input temperature data for subsequent iterative calculation of the heat transfer conservation equation. For the heating wire, after obtaining the heating wire temperature determination domain and the heating wire temperature calculation domain using edge detection, the point temperature value of each pixel in the heating wire temperature determination domain at each acquisition time needs to be read. At each acquisition time, based on the temperature value of the heating wire temperature determination domain, the point temperature value of each pixel in the heating wire temperature calculation region is reasonably corrected to obtain the complete heating wire temperature domain, which is then used as the input temperature data for subsequent iterative calculation of the heat transfer conservation equation.

[0099] In one embodiment, the process of correcting the temperature values ​​of each point in the heating wire temperature calculation domain includes: dividing the heating wire temperature calculation domain into at least one sub-temperature layer based on the distance between each pixel in the heating wire temperature calculation domain and the heating wire temperature determination domain; starting from the sub-temperature layer closest to the heating wire temperature determination domain, processing each sub-temperature layer in order of increasing distance as follows: taking any point temperature value in the sub-temperature layer as the center point of a first neighborhood window, determining at least one point temperature value belonging to the heating wire temperature determination domain in the first neighborhood window as a first point temperature value, determining the heating wire temperature correction value corresponding to the first point temperature value, and after traversing each point temperature value in the sub-temperature layer, adding the sub-temperature layer to the heating wire temperature determination domain. After processing each sub-temperature layer, the final heating wire temperature determination domain is the heating wire temperature domain.

[0100] In this embodiment, the heating wire temperature calculation domain is processed by using a layered calculation and superposition method to obtain the heating wire temperature correction value.

[0101] Assuming the heating wire is considered as a long, curved cuboid, its Bi number on the cross-section of the cuboid, according to the heat transfer model, is:

[0102]

[0103] Wherein, Bi number describes the uniformity of heat flow distribution within the object; the smaller Bi is, the smaller the internal thermal resistance and the larger the external thermal resistance; h is the heat transfer coefficient of the heating wire; k1 is the thermal conductivity of the heating wire. In this embodiment, the convective heat transfer coefficient is treated using a dimensionless method. For the surface of the heating wire, its heat transfer is equivalent to the heat conduction to the temperature domain of the substrate. l is the characteristic dimension of the cuboid cross-section, and L is the characteristic dimension of the entire substrate.

[0104] In this embodiment, based on the planar heating element structure, it is clear that c = L / l < 1. That is, Bi is less than the ratio of the thermal conductivity of the substrate to the thermal conductivity of the heating wire. Therefore, the value of Bi is very small, meaning that relative to the substrate temperature field, the temperature change on the cuboid cross-section of the heating wire is very small, and the temperature distribution within the cross-section should have strong uniformity. Therefore, it is reasonable to use a layered calculation and superposition method to solve for the heating wire temperature correction value within the heating wire temperature calculation domain.

[0105] In this embodiment, the implementation process of the layered calculation and overlay method is as follows:

[0106] First, the heating wire temperature calculation domain is divided into two layers (i.e., the heating wire temperature calculation domain is divided into two sub-temperature layers). The points that are close to the temperature determination domain are combined into one layer, which is called the outer layer; the remaining points are called the inner layer.

[0107] Second, the outer layer is calculated first. For each pixel in the outer layer, an 8-neighborhood query is performed (the first neighborhood window is a 3×3 window). For pixels in the 8-neighborhood that belong to the heating wire temperature determination domain, their corresponding point temperature value is recorded as the first point temperature value. The median of all first point temperature values ​​is calculated as the heating wire temperature correction value for that pixel. After the calculation for each pixel is completed, the temperature value correction of the outer layer can be completed.

[0108] Third, after the outer layer calculation is completed, the outer layer is classified into the heating wire temperature determination domain, and the temperature correction values ​​of all heating wires in the inner layer are calculated using the same method.

[0109] Fourth, there may be individual pixels in the inner layer that are separated from the heating wire temperature determination domain and have not been assigned a value for calculation. For these pixels, a query is performed on their surrounding 24 neighborhoods (the first neighborhood window is a 5×5 window). For pixels in the 24 neighborhoods that belong to the heating wire temperature determination domain, their corresponding point temperature value is recorded as the first point temperature value. The minimum value of all first point temperature values ​​is calculated, and the corresponding point is assigned a value, thus obtaining the heating wire temperature correction value for that pixel.

[0110] By completing the above four steps, the temperature value correction of the heating wire temperature calculation domain can be completed.

[0111] In one embodiment, determining the boundary line between the heating wire and the substrate in the infrared temperature measurement cloud image includes: performing convolution processing on the infrared temperature measurement cloud image to obtain the gradient index corresponding to each pixel; based on the gradient index, selecting at least one maximum point from each pixel through non-maximum suppression processing; and performing numerical point refinement and padding processing on each maximum point to obtain the boundary line.

[0112] In this embodiment, the boundary line between the heating wire and the substrate is obtained through a boundary detection algorithm, which includes three main steps: First, gradient calculation is performed on the infrared temperature matrix: a gradient operator is generated based on the gradient calculation method. The gradient operator performs convolution calculation on the temperature field data, and the convolution result is the gradient index of each data point in the row and column directions. Second, gradient index filtering: based on the gradient index of each data point in the row and column directions, each pixel is filtered using a relevant maximum value determination algorithm to generate a set of filtered points, which is the initial boundary between the heating wire and the substrate. Third, using the gradient index as a constraint, a secondary filtering is performed on the filtered points. Points whose gradient modulus satisfies the constraint are retained, while points that do not satisfy the constraint are suppressed. Then, discontinuities between points are filled, ultimately completing the generation of the boundary line.

[0113] In one embodiment, convolution processing is performed on the infrared thermogram to obtain the gradient index corresponding to each pixel, including: calculating a Gaussian kernel operator based on a preset operator scale; performing convolution smoothing processing on the infrared temperature matrix corresponding to the infrared thermogram using the Gaussian kernel operator to obtain a first temperature data matrix; performing difference processing on the Gaussian kernel operator to obtain a Gaussian gradient operator; calculating the gradient matrix corresponding to the infrared temperature matrix based on the first temperature data matrix and the Gaussian gradient operator; calculating the gradient magnitude corresponding to the temperature value of each point in the infrared temperature matrix based on the gradient matrix; and calculating the gradient angle and gradient tangent corresponding to the temperature value of each point based on the gradient magnitude. The gradient index includes the gradient angle and the gradient tangent.

[0114] In this embodiment, convolution smoothing and gradient calculation are mainly performed. Optionally, Gaussian convolution smoothing and Gaussian first derivative gradient convolution calculation are used.

[0115] In this embodiment, the standard deviation of the Gaussian kernel is set to σ, and the scale of the Gaussian kernel operator is ceil(4σ), which is 4 times the size of σ and rounded up. ceil means rounding up.

[0116] Let the sequence {x} n}:x1=-ceil(4σ),x n =ceil(4σ), x n =x n-1 +1

[0117] The expression for the Gaussian function is:

[0118]

[0119] {x n Substituting the Gaussian function g(x), we get:

[0120] [g(x1),g(x2),…,g(x n―1 ),g(x n (19)

[0121] set up

[0122] g max =max[g(x1),g(x2),…,g(x n―1 ),g(x n (20)

[0123] Then the Gaussian kernel operator is generated:

[0124] gk = 1 / g max ·[g(x1),g(x2),…,g(x n―1 ),g(x n)] (twenty one);

[0125] Therefore, I is first subjected to convolution smoothing, where I is the first temperature data matrix after filtering and noise reduction, as follows:

[0126]

[0127] I y =I*gk (23);

[0128] Among them, I x I represents the result of convolution in the x-direction. y This represents the result of convolution in the y-direction. This represents the transpose of gk.

[0129] The Gaussian kernel operator is differentially processed to generate the Gaussian gradient operator:

[0130] dgk = [dg1,dg2,…,dg n―1 ,dg n ] (twenty four);

[0131] in,

[0132] dg1=1 / g max ·[g(x2)―g(x1)] (25);

[0133] dg n =1 / g max ·[g(x n )―g(x n―1 (26)

[0134] dg i =0.5 / g max ·[g(x i+1 )―g(x i―1 )](1 <i<n) (27);

[0135] That is, perform forward difference processing on the first and last elements of the Gaussian kernel operator, and perform central difference processing on the other internal elements.

[0136] The gradients of I in the x and y directions can be calculated by the following convolution:

[0137] G x =I x *dgk (28);

[0138]

[0139] According to the solution G x and G yThe gradient magnitude of each pixel in I can be calculated, and the gradient magnitude is then normalized as follows:

[0140]

[0141] G m =G m0 ÷max(G m0 (31);

[0142] In the above formula, G m This is the gradient magnitude matrix corresponding to I, which records the gradient magnitude value of each pixel in I.

[0143] According to the solution G x and G y Calculate the gradient angle matrix θ and the gradient angle tangent matrix d for each pixel:

[0144] θ = arctan(G) y · / G x (32);

[0145] d=|tan(G y · / G x )| (33).

[0146] In one embodiment, based on a gradient index, at least one maximum point is selected from each pixel through non-maximum suppression processing, including: taking the temperature value of any point in the infrared temperature matrix as the center point of a second neighborhood window; determining the intersection point between the point temperature value and the second neighborhood window based on the gradient angle; performing interpolation processing based on the tangent of the gradient angle to obtain the interpolated value corresponding to the intersection point; determining the maximum point from the intersection point based on the point temperature value and the interpolated value; and traversing each point temperature value in the infrared temperature matrix to obtain at least one maximum point.

[0147] In this embodiment, non-maximum suppression is used for gradient magnitude screening. Specifically, non-maximum suppression is performed on each pixel in I. That is, the boundary between the heating wire and the substrate should meet the necessary condition of maximum rate of change. If the gradient of a pixel is not a local maximum, it does not belong to the boundary and needs to be suppressed. Non-maximum suppression has four different cases:

[0148] In the first case, for any pixel (j,k), if |G x |>|G y |, and G x ·G y >0, meaning θ ranges from (0, 45°) ∪ (180°, 225°):

[0149] At this point, the intersections of point (i,j) with its two surrounding 8 neighbors (the second neighborhood window uses a 3×3 window) along the gradient direction are as follows: Figure 9 As shown, for intersection point 1, the gradient value is obtained by interpolation between pixel (j-1,k+1) and pixel (j,k+1); for intersection point 2, the gradient value is obtained by interpolation between pixel (j,k-1) and pixel (j+1,k-1).

[0150] G1=d·G j―1,k+1 +(1―d)·G j,k+1 (34);

[0151] G2=d·G j+1,k―1 +(1―d)·G j,k―1 (35);

[0152] When G(j,k)≥G1 and G(j,k)≥G2, the pixel (j,k) is a maximum point and is selected; otherwise, it is discarded.

[0153] In the second case, for any pixel (j,k), if |G x |<|G y |, and G x ·G y >0, meaning θ ranges from (45°, 90°) ∪ (225°, 270°):

[0154] At this point, the intersection of pixel (i,j) with its two neighboring 8-bit neighbors (the second neighboring window uses a 3×3 window) along the gradient direction is as follows: Figure 10 As shown, for intersection point 1, the gradient value is obtained by interpolation between pixel (j-1,k) and pixel (j-1,k+1); for intersection point 2, the gradient value is obtained by interpolation between pixel (j+1,k-1) and pixel (j+1,k).

[0155]

[0156]

[0157] When G(j,k)≥G1 and G(j,k)≥G2, the pixel (j,k) is a maximum point and is selected; otherwise, it is discarded.

[0158] In the third case, for any pixel (j,k), if |G x |<|G y |, and G x ·G y <0, meaning θ ranges from (90°, 135°) ∪ (270°, 315°):

[0159] At this point, the intersection of pixel (i,j) with its two neighboring 8-bit neighbors (the second neighboring window uses a 3×3 window) along the gradient direction is as follows: Figure 11 As shown, for intersection point 1, the gradient value is obtained by interpolation between pixel (j-1,k-1) and pixel (j-1,k); for intersection point 2, the gradient value is obtained by interpolation between pixel (j+1,k) and pixel (j+1,k+1).

[0160]

[0161]

[0162] When G(j,k)≥G1 and G(j,k)≥G2, the pixel (j,k) is a maximum point and is selected; otherwise, it is discarded.

[0163] The fourth case is that for any pixel (j,k), if |G x |>|G y |, and G x ·G y >0, meaning θ ranges from (135°, 180°) ∪ (315°, 360°):

[0164] At this point, the intersection of pixel (i,j) with its two neighboring 8-bit neighbors (the second neighboring window uses a 3×3 window) along the gradient direction is as follows: Figure 12 As shown, for intersection point 1, the gradient value is obtained by interpolation between pixel (j-1,k-1) and pixel (j,k-1); for intersection point 2, the gradient value is obtained by interpolation between pixel (j,k+1) and pixel (j+1,k+1).

[0165] G1=d·G j―1,k―1 +(1―d)·G j,k―1 (40);

[0166] G2=d·G j+1,k+1 +(1―d)·G j,k+1 (41);

[0167] When G(j,k)≥G1 and G(j,k)≥G2, the point (j,k) is a local maximum and is selected; otherwise, it is discarded.

[0168] Specifically, when the gradient angle of pixel (j,k) is exactly 0° or 180°, intersection points 1 and 2 are pixel (j,k-1) and pixel (j,k+1). In this case, if G(j,k)≥G(j,k-1) and G(j,k)≥G(j,k+1), then G(j,k) is a maximum point and is selected; otherwise, it is discarded. When the gradient angle of pixel (j,k) is exactly 90° or 270°, intersection points 1 and 2 are pixel (j-1,k) and pixel (j+1,k). In this case, if G(j,k)≥G(j-1,k) and G(j,k)≥G(j+1,k), then G(j,k) is a maximum point and is selected; otherwise, it is discarded.

[0169] In one embodiment, for each maximum point, numerical point refinement and completion processing are performed to obtain a boundary line, including: classifying each gradient magnitude value into levels to obtain the number of magnitude values ​​contained in each level; obtaining a sequence of magnitude values ​​by accumulating the number of magnitude values; determining a first threshold and a second threshold based on the magnitude of the values ​​in the sequence of magnitude values, wherein the first threshold is greater than the second threshold; adding each maximum point greater than the first threshold to the boundary point set; sequentially using each maximum point greater than the first threshold as the center point of a third neighborhood window; using the temperature values ​​of points greater than the second threshold in the third neighborhood window as third temperature values, and calculating the gradient magnitude of the third temperature values; if the gradient magnitude of the third temperature value is greater than the second threshold, then adding the third temperature to the boundary point set; constructing an initial boundary line based on the boundary point set; if the initial boundary line includes open endpoints, completing the initial boundary line based on the open endpoints to obtain a closed boundary line.

[0170] In this embodiment, the main process is double threshold hysteresis processing, which specifically involves edge refinement and padding.

[0171] In this embodiment, a dual threshold is first generated, and the result obtained from Gm is converted into a histogram for statistical analysis. The calculation result is divided into several levels; optionally, 64 levels are used as an example. The number of elements contained in each level can then be denoted as:

[0172] {l n}=l1,l2,l3……,l 63 ,l 64 (42);

[0173] And the following formula holds, where m is the number of rows in I and n is the number of columns in I.

[0174]

[0175] Logarithmic sequence {l n Perform cumulative summation to obtain the sequence L of counts. n, that is, the i-th term of the number sequence {L n} satisfies:

[0176]

[0177] Examine each term of the sequence {L}. If the i-th term Li satisfies:

[0178] L i > p·(m·n) (45);

[0179] where p is a parameter used to adjust the selection level of the gradient modulus. Optionally, 0.75 < p < 0.85. Different values of p can select different i. The larger the value of p, the larger the selected i, and the larger the first threshold and the second threshold obtained later will be;

[0180] then the first threshold of the double thresholds is: ht = i ÷ 64; the second threshold is: lt = r·ht

[0181] Let the point set filtered by non-maximum suppression be represented by U. Further filtering is performed using the first threshold ht and the second threshold lt respectively to generate the point sets E and H:

[0182]

[0183]

[0184] For each point q in H, for Search for the 8-neighborhood of point q ∈ H (the third neighborhood window uses a 3×3 window). If there is at least one point p among them, that is point p, satisfying G(p) ∈ E, then add p to the point set H as well. Continuously iterate the above steps until no new points are added to the point set H. At this point, the finally generated point set H is the initial boundary line obtained by the boundary detection algorithm.

[0185] In this embodiment, since the temperatures of the positive and negative electrode parts of the heating wire are low, it may cause the initial boundary line obtained by the boundary detection algorithm to be unclosed at the electrodes. Therefore, it is necessary to complete and close the initial boundary line according to the positions of the electrodes. The outermost edge of the initial boundary line at the electrodes can be found, and the points inside the outer edge can be filled in at intervals to make the generated initial boundary line complete and closed, obtaining the final boundary line.

[0186] In one embodiment, based on the heating wire temperature domain, the substrate temperature determination domain, and the substrate temperature calculation domain, the energy conservation residual during the heat conduction process from the heating wire to the substrate is calculated. This includes: for any first pixel in the innermost layer of the substrate temperature determination domain, determining the n nearest neighboring pixels, wherein the innermost layer of the substrate temperature determination domain includes every pixel located in the substrate temperature determination domain and adjacent to the substrate temperature calculation domain, where n is a positive integer, and the neighboring pixels are located in either the substrate temperature determination domain or the substrate temperature calculation domain; the point temperature value of each first pixel and the point temperature values ​​of the corresponding neighboring pixels are input into the energy conservation equation for calculation to obtain the energy conservation residual.

[0187] In this embodiment, the heat generated by the heating wire is conducted to other parts of the substrate through the substrate temperature calculation domain and the innermost layer of the substrate temperature determination domain. Since the point temperature values ​​within the substrate temperature calculation domain are inaccurate, the thermal energy conservation calculation is primarily performed on the innermost layer of the substrate temperature determination domain. Specifically, for any first pixel in the innermost layer of the substrate temperature determination domain, neighboring pixels are determined. These neighboring pixels are located within either the substrate temperature determination domain or the substrate temperature calculation domain. This allows for better verification of energy conservation, and the resulting energy conservation residuals are more representative.

[0188] In one embodiment, for each neighboring pixel in the substrate temperature calculation domain, the following processing is performed: in the substrate temperature determination domain, the second pixel closest to the neighboring pixel is determined, and in the heating wire temperature domain, the third pixel closest to the neighboring pixel is determined; the point temperature values ​​of the second pixel and the third pixel are interpolated, and the interpolation result is used as the point temperature value of the neighboring pixel.

[0189] In this embodiment, since the point temperature values ​​of neighboring pixels in the substrate temperature calculation domain are inaccurate, the point temperature values ​​of the second pixel in the substrate temperature determination domain are more accurate, and the point temperature values ​​of the third pixel in the heating wire temperature domain are more accurate. Interpolation is then used to obtain more accurate point temperature values ​​of neighboring pixels, thereby improving the accuracy of the energy conservation residual and thus improving the accuracy of the final target heating wire emissivity.

[0190] In one embodiment, the energy conservation equation is obtained by discretizing the energy conservation formula based on the innermost layer of the matrix temperature determination domain.

[0191] In this embodiment, when performing thermal energy conservation calculations mainly for the innermost layer of the substrate temperature determination domain, an energy conservation equation is set based on the innermost layer of the substrate temperature determination domain. This makes the energy conservation equation more suitable for the processing of the innermost layer of the substrate temperature determination domain, thereby improving processing efficiency.

[0192] In a specific embodiment, the specific calculation principle and process of the energy conservation residual are as follows:

[0193] During the temperature rise test of the heating element under test, the heating wire generates Joule heat due to the overcurrent, causing the heating element to heat up while simultaneously conducting heat, which must satisfy the conservation of heat conduction energy. Therefore, an iterative algorithm for heating wire emissivity based on energy conservation calculation is adopted. When the energy conservation residual reaches the convergence criterion, the temperature of the heating wire is considered to be true and reasonable, and the corresponding measured heating wire emissivity value is the target heating wire emissivity.

[0194] Furthermore, the temperature rise process of the tested heat-generating body conforms to a two-dimensional unsteady-state heat conduction model with a local internal heat source, and the differential form of the energy conservation equation can be described by the following equation:

[0195]

[0196]

[0197] Equation (48) is the energy conservation equation for the heating wire temperature domain; Equation (49) is the energy conservation equation for the substrate temperature domain. ρ2 is the density of the heating wire, C p2 denoted as , where is the specific heat capacity of the heating wire, is the source term representing the heat generated per unit volume and per unit time, is temperature, is time, ...

[0198] For the heating wire temperature domain, the complete temperature field of the heating wire temperature domain at each acquisition moment has been obtained through layered calculation and superposition methods. The thermal conductivity diffusing into the substrate temperature domain can be described by the overall energy equation. The unsteady terms in the energy equation are then discretized using finite difference methods, as follows:

[0199]

[0200] Based on equation (50) above, the heat flow rate conducted from the heating wire to the substrate from time j to time j+1 is equal to the heat flow rate of the heating wire minus the temperature rise of the heating wire at each point within that infinitesimal time interval. Where I is the current through the heating wire, R0 is the resistivity of the heating wire (which can be determined based on the material selected for the heating wire), and s is the characteristic dimension of the heating wire in its cross-section. For the temperature domain of the heating wire, assuming there are m pixels, the temperature value of the i-th pixel at time n is denoted as... Δt is the infinitesimal time interval, which can generally be taken as 1s.

[0201] For the matrix temperature domain, the thermal energy conservation calculation is mainly performed on the innermost layer of the matrix temperature domain, and the energy conservation equation is discretized:

[0202]

[0203] Among them, set Let be the grid Fourier numbers in the x-direction and the grid Fourier numbers in the y-direction, respectively. Therefore, the above equation can be simplified to:

[0204]

[0205] In the above formula, the action occurs in the innermost layer of the matrix-defined domain, i.e. This represents a temperature point within a defined domain of the ceramic matrix, with horizontal coordinates of x and vertical coordinates of y. The two adjacent layers are the innermost adjacent layer of the defined matrix domain and the outermost layer of the matrix temperature calculation domain, respectively. The innermost adjacent layer includes every pixel located within and immediately adjacent to the innermost layer of the defined matrix temperature domain, and includes the second pixel. The outermost layer of the matrix temperature calculation domain includes every pixel located within and immediately adjacent to the matrix temperature calculation domain. For the outermost layer of the matrix temperature calculation domain, an approximate value is obtained by interpolation between the outermost layer of the heating wire region and the innermost layer of the defined matrix domain, as detailed below:

[0206] Let the temperature of a certain pixel in the outermost layer of the matrix temperature calculation domain be the target value. have:

[0207]

[0208] Here, 2° is used to determine the second pixel closest to a neighboring pixel in the substrate temperature determination domain, and the third pixel closest to a neighboring pixel in the heating wire temperature domain. (x,y) represents any neighboring pixel in the substrate temperature calculation domain, and (x1,y1) and (x2,y2) represent the second and third pixels, respectively.

[0209] Based on equation (53), the point temperature of any neighboring pixel in the matrix temperature calculation domain is obtained by interpolation of the temperature points in the outermost layer of the heating wire region and the innermost layer of the matrix temperature determination domain, which are basically aligned in the same direction. Therefore, in equation (52), for any temperature point in the innermost layer of the matrix temperature determination domain... Its 4-neighborhood (taking a neighborhood of 4 pixels as an example) surrounding area All can be determined, and the energy conservation equation of equation (52) can be calculated.

[0210] The energy conservation equation (52) is calculated using the temperature data obtained from all previous tests. Assuming that the innermost layer of the matrix temperature determination domain is represented by D and has N pixels, the energy conservation residual E is:

[0211]

[0212] Based on the calculated energy conservation residual, the emissivity of the test heating wire set in the infrared thermometry can be adjusted. The heating wire temperature data is updated through the infrared thermal imager temperature measurement mathematical model. Then, the heating wire temperature calculation domain is corrected and the energy conservation residual E is recalculated. This forms an iterative calculation of the emissivity setting. When the energy conservation residual E no longer decreases, the calculation ends and the emissivity of the test heating wire set at this time is output, which is the final target emissivity of the heating wire.

[0213] In a specific embodiment, such as Figure 13 As shown, the process for determining the emissivity of the target heating wire is as follows:

[0214] Step 1301: For the heating element under test, input its matching voltage and power to perform a heating and temperature rise test, and obtain the original temperature cloud map at multiple consecutive acquisition moments during the heating period.

[0215] Step 1302: Capture the initial temperature measurement cloud map. For the original temperature measurement cloud map of the first acquisition time out of multiple consecutive acquisition times, the initial temperature measurement cloud map containing the complete temperature domain of the heating wire, suitable for subsequent calculations, is extracted by setting and adjusting the temperature parameters. Then, based on the location information of the target area to be measured, the initial temperature measurement cloud map for each acquisition time is captured.

[0216] Step 1303 involves filtering and denoising the initial temperature measurement cloud image. The filtering method employs median filtering and Gaussian filtering to generate corresponding filtering matrix operators. These operators are then used to perform convolution operations on the initial temperature measurement cloud image, thus completing the data filtering and denoising process and obtaining the infrared temperature measurement cloud image, preventing data noise from reducing the interpretability of the model. In this invention, a denoising method of first performing median filtering and then Gaussian filtering is used to perform filtering and denoising processing on the initial temperature measurement cloud image at each acquisition time.

[0217] Step 1304: Determine the boundary line between the heating wire and the substrate in the infrared thermography cloud image. The boundary line determination process includes three steps: First, perform gradient calculation on the temperature field data: First, generate a gradient operator according to the gradient calculation method. The gradient operator performs convolution calculation on the temperature field data. The convolution calculation result is the gradient of each data point in the row and column directions of the temperature field. Second, gradient value filtering: Based on the gradient of each data point in the row and column directions, calculate its gradient magnitude and gradient direction. According to the gradient magnitude and gradient direction of each data point, filter each data point by determining the maximum value, and generate a set of filtered result points, which are the pre-selected boundary between the heating wire and the substrate. Third, use the gradient magnitude as a constraint condition to perform a second filtering on the filtered points. Points whose gradient magnitude meets the constraint condition are retained, and points that do not meet the constraint condition are suppressed. Then, fill the discontinuities between the points to finally complete the generation of the boundary line. Boundary detection is performed on the infrared thermogram at the first acquisition time to determine the boundary line between the substrate and the heating wire. Since the position information used in the above extraction is the same, this boundary line can be used for the infrared thermogram at each acquisition time.

[0218] Step 1305: The boundary line divides the whole into two parts: the substrate temperature domain and the heating wire temperature domain. Each individual part of the substrate temperature domain and the heating wire temperature domain is further divided into a temperature determination domain and a temperature calculation domain. This is because the emissivity of the substrate and the heating wire is very different, which causes the temperature measurement at the junction of the two parts to be affected by the emissivity, resulting in distorted temperature measurement data. Therefore, the pixels on the boundary of the substrate and the heating wire belong to the temperature calculation domain, while the pixels inside belong to the temperature determination domain.

[0219] Step 1306: Determine the substrate temperature domain. After determining the boundary lines between the substrate and the heating wire, the interior and edges of the substrate temperature domain can be further divided using edge detection methods to obtain the substrate temperature domain. The temperature field data within this region can then be used as input for subsequent calculations of the heating wire emissivity.

[0220] Step 1307: Determine the heating wire temperature domain. For the heating wire temperature domain, the interior and edges are divided using an edge detection method to obtain the heating wire temperature determination domain and the heating wire temperature calculation domain. Based on the lumped parameter characteristics of the heating wire in the radial direction, a layered calculation and superposition method is used to correct the point temperature values ​​in the heating wire temperature calculation domain, thereby calculating the complete temperature data within the heating wire temperature domain.

[0221] Step 1308: The overall heating process of the heating element must satisfy the conservation of heat transfer, meaning the Joule heat generated by the heating wire should equal the enthalpy increase of the heating wire itself and its thermal conductivity to the substrate. The thermal conductivity of the heating wire to the substrate can be reflected by the temperature rise of the innermost layer of the substrate temperature determination domain and the thermal conductivity of the adjacent outer layer of the innermost layer of the substrate temperature determination domain. Therefore, based on the iterative calculation method of heat transfer conservation, energy conservation calculations are performed on the temperature values ​​at each pixel. The heating wire temperature is iterated using the energy conservation residual from the energy conservation calculations.

[0222] Step 1309: When the energy conservation residual reaches the convergence criterion, the corresponding heating wire temperature is true and reasonable, and step 1310 is executed; if the energy conservation residual does not converge, step 1307 is repeated.

[0223] Step 1310: Output the emissivity of the target heating wire. Since temperature data in infrared thermometry is related to the emissivity of the object being measured, under certain basic parameters in the test environment, different measured temperature values ​​can be obtained by adjusting different emissivities. Therefore, the emissivity of the test heating wire can be adjusted through feedback using the energy conservation residual in step 1308, thereby achieving temperature iteration of the heating wire. When the heating wire temperature causes the energy conservation residual to converge, the corresponding emissivity of the test heating wire is the emissivity of the target heating wire.

[0224] In this embodiment, infrared thermograms of the target area to be tested are acquired at multiple consecutive acquisition times. The target area to be tested includes a heating wire and a substrate, with the heating wire arranged on the substrate. The infrared thermometer is configured with different test heating wire emissivity at different acquisition times. Starting from the infrared thermogram corresponding to the first acquisition time, the energy conservation residual during the heat conduction process from the heating wire to the substrate is acquired sequentially based on the infrared thermogram. If the energy conservation residual corresponding to the second acquisition time is greater than or equal to the energy conservation residual corresponding to the first acquisition time, the test heating wire emissivity corresponding to the second acquisition time is determined to be the target heating wire emissivity. The first acquisition time and the second acquisition time are two sequentially adjacent acquisition times. In the above process, infrared thermograms from multiple consecutive acquisition times are used to configure different test heating wire emissivities for the infrared thermometer at different acquisition times. Energy conservation is verified based on the principle of heat conduction. When the energy conservation residual at the second acquisition time is greater than or equal to the energy conservation residual at the first acquisition time, it indicates that the energy conservation residual is beginning to converge. At this point, the test heating wire emissivity is closer to the true emissivity of the heating wire. Therefore, the test heating wire emissivity at the second acquisition time is taken as the target heating wire emissivity. This target heating wire emissivity is more accurate, and thus, when infrared thermometry is performed based on this target heating wire emissivity, more accurate temperature measurement data can be obtained.

[0225] Exemplary device

[0226] Accordingly, embodiments of this application also provide an emissivity determination device, such as... Figure 14 As shown, the device may include:

[0227] The image acquisition module 1401 is used to acquire infrared thermograms of the target area under test at multiple consecutive acquisition times. The target area under test includes a heating wire and a substrate. The heating wire is arranged on the substrate. The infrared thermometer is configured with different test heating wire emissivity at different acquisition times.

[0228] Image processing module 1402 is used to obtain the energy conservation residual during the heat conduction process from the heating wire to the substrate, starting from the infrared temperature measurement cloud image corresponding to the first acquisition moment.

[0229] The emissivity determination module 1403 is used to determine the emissivity of the test heating wire at the second acquisition time as the target heating wire emissivity if the energy conservation residual at the second acquisition time is greater than or equal to the energy conservation residual at the first acquisition time. The first acquisition time and the second acquisition time are two sequentially adjacent acquisition times.

[0230] The emissivity determination apparatus provided in this embodiment belongs to the same concept as the emissivity determination method provided in the above embodiments of this application. It can execute the emissivity determination method provided in any of the above embodiments of this application and has the corresponding functional modules and beneficial effects of the method. Technical details not described in detail in this embodiment can be found in the specific processing content of the emissivity determination method provided in the above embodiments of this application, and will not be repeated here.

[0231] Exemplary electronic devices

[0232] This application also provides an electronic device, such as... Figure 15 As shown, the electronic device includes a memory 1500 and a processor 1501.

[0233] The memory 1500 is connected to the processor 1501 and is used to store programs.

[0234] The processor 1501 is used to implement the emissivity determination method in the above embodiments by running the program stored in the memory 1500.

[0235] Specifically, the aforementioned electronic device may also include: a communication interface 1502, an input device 1503, an output device 1504, and a bus 1505.

[0236] The processor 1501, memory 1500, communication interface 1502, input device 1503, and output device 1504 are interconnected via a bus. Among them:

[0237] Bus 1505 may include a pathway for transmitting information between various components of a computer system.

[0238] Processor 1501 can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present invention. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0239] Processor 1501 may include a main processor, as well as a baseband chip, modem, etc.

[0240] The memory 1500 stores a program that executes the technical solution of this invention, and may also store an operating system and other key business functions. Specifically, the program may include program code, which includes computer operation instructions. More specifically, the memory 1500 may include read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), other types of dynamic storage devices capable of storing information and instructions, disk storage, flash memory, etc.

[0241] Input device 1503 may include a device for receiving data and information input by the user, such as a keyboard, mouse, camera, scanner, light pen, voice input device, touch screen, pedometer or gravity sensor, etc.

[0242] Output device 1504 may include devices that allow information to be output to a user, such as a display screen, printer, speaker, etc.

[0243] The communication interface 1502 may include a device that uses any transceiver to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0244] The processor 1501 executes the program stored in the memory 1500 and calls other devices, which can be used to implement the various steps of the emissivity determination method provided in the above embodiments of this application.

[0245] Exemplary computer program products and storage media

[0246] In addition to the methods and devices described above, embodiments of this application may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the emissivity determination method described in the embodiments of this application.

[0247] The aforementioned computer program product can be implemented through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically embodied in a computer storage medium; in another optional embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0248] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0249] Furthermore, embodiments of this application may also be storage media storing a computer program, which is executed by a processor of the steps in the emissivity determination method described in the embodiments of this application.

[0250] For the foregoing method embodiments, in order to simplify the description, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0251] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For apparatus embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0252] The steps in the methods of the various embodiments of this application can be adjusted, merged, or deleted in order according to actual needs, and the technical features described in each embodiment can be replaced or combined.

[0253] The modules and sub-modules in the devices and terminals provided in the various embodiments of this application can be merged, divided, and deleted according to actual needs.

[0254] It should be understood that the disclosed terminals, devices, and methods can be implemented in other ways, given the several embodiments provided in this application. For example, the terminal embodiments described above are merely illustrative. For instance, the division of modules or sub-modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple sub-modules or modules may be combined or integrated into another module, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0255] The modules or submodules described as separate components may or may not be physically separate. The components that constitute a module or submodule may or may not be physical modules or submodules; that is, they may be located in one place or distributed across multiple network modules or submodules. Some or all of the modules or submodules can be selected to achieve the purpose of this embodiment's solution, depending on actual needs.

[0256] Furthermore, the functional modules or sub-modules in the various embodiments of this application can be integrated into one processing module, or each module or sub-module can exist physically separately, or two or more modules or sub-modules can be integrated into one module. The integrated modules or sub-modules described above can be implemented in hardware or in the form of software functional modules or sub-modules.

[0257] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0258] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software unit executed by a processor, or a combination of both. The software unit can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0259] Finally, 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.

[0260] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for determining emissivity, characterized in that, include: Infrared thermograms of a target area to be measured are acquired at multiple consecutive acquisition times. The target area to be measured includes a heating wire and a substrate. The heating wire is arranged on the substrate. The infrared thermometer is configured with different emissivity of the heating wire at different acquisition times. Starting from the infrared temperature measurement cloud image corresponding to the first acquisition time, the energy conservation residual during the heat conduction process from the heating wire to the substrate is obtained sequentially based on the infrared temperature measurement cloud image. If the energy conservation residual corresponding to the second acquisition time is greater than or equal to the energy conservation residual corresponding to the first acquisition time, the emissivity of the test heating wire corresponding to the second acquisition time is determined to be the emissivity of the target heating wire, wherein the first acquisition time and the second acquisition time are two sequentially adjacent acquisition times.

2. The emissivity determination method according to claim 1, characterized in that, The infrared temperature measurement cloud map includes the point temperature values ​​of multiple pixels corresponding to the target area to be measured; The step of obtaining the energy conservation residual during the heat conduction process from the heating wire to the substrate based on the infrared thermogram includes: Determine the boundary line between the heating wire and the substrate in the infrared thermography cloud image, wherein the boundary line is a closed curve; Based on the boundary line, in the infrared temperature measurement cloud map, the heating wire temperature domain corresponding to the heating wire, and the substrate temperature determination domain and substrate temperature calculation domain corresponding to the substrate are determined, wherein the accuracy of the point temperature value in the substrate temperature determination domain is greater than the accuracy of the point temperature value in the substrate temperature calculation domain. Based on the heating wire temperature domain, the substrate temperature determination domain, and the substrate temperature calculation domain, the energy conservation residual during the heat conduction process from the heating wire to the substrate is calculated.

3. The emissivity determination method according to claim 2, characterized in that, The calculation of the energy conservation residual during the heat conduction process from the heating wire to the substrate, based on the heating wire temperature domain, the substrate temperature determination domain, and the substrate temperature calculation domain, includes: For any first pixel in the innermost layer of the substrate temperature determination domain, determine the n nearest neighboring pixels. The innermost layer of the substrate temperature determination domain includes each pixel located in the substrate temperature determination domain and adjacent to the substrate temperature calculation domain, where n is a positive integer. The neighboring pixels are located in the substrate temperature determination domain or the substrate temperature calculation domain. The point temperature value of each first pixel and the point temperature value of the corresponding neighboring pixels are input into the energy conservation equation for calculation to obtain the energy conservation residual.

4. The emissivity determination method according to claim 3, characterized in that, For each of the neighboring pixels located in the matrix temperature calculation domain, the following processing is performed: In the substrate temperature determination domain, the second pixel closest to the neighboring pixel is determined, and in the heating wire temperature domain, the third pixel closest to the neighboring pixel is determined. The point temperature value of the second pixel and the point temperature value of the third pixel are interpolated, and the interpolation result is used as the point temperature value of the neighboring pixel.

5. The emissivity determination method according to claim 3, characterized in that, The energy conservation equation is obtained by discretizing the energy conservation formula based on the innermost layer of the matrix temperature determination domain.

6. The emissivity determination method according to claim 1, characterized in that, The acquisition of infrared thermograms of the target area under test acquired at multiple consecutive acquisition times includes: At each acquisition moment, by configuring the infrared temperature measurement device with the corresponding test heating wire emissivity, the original temperature measurement cloud map of the heat-generating body under test is acquired, wherein the heat-generating body under test includes the target area to be measured; By filtering the point temperature values ​​of each pixel in the original temperature measurement cloud map at the first acquisition time using the critical temperature value, the initial temperature measurement cloud map at the first acquisition time is obtained, as well as the location information of the target area to be measured is obtained. Based on the location information of the target area to be measured, the initial temperature measurement cloud map is obtained at each of the acquisition times except for the first acquisition time. Each initial temperature measurement cloud image is filtered to obtain the infrared temperature measurement cloud image at each acquisition time.

7. The emissivity determination method according to claim 1, characterized in that, Determining the boundary line between the heating wire and the substrate in the infrared thermometry cloud image includes: The infrared temperature measurement cloud image is convolved to obtain the gradient index corresponding to each pixel in the infrared temperature measurement cloud image. Based on the gradient index, at least one maximum point is selected from each of the pixels through non-maximum suppression processing. For each of the maximum points, numerical point refinement and completion processing are performed to obtain the boundary line.

8. An emissivity determination device, characterized in that, include: The image acquisition module is used to acquire infrared thermograms of the target area under test at multiple consecutive acquisition times. The target area under test includes a heating wire and a substrate. The heating wire is arranged on the substrate. The infrared thermometer is configured with different emissivity of the heating wire at different acquisition times. The image processing module is used to obtain the energy conservation residual during the heat conduction process from the heating wire to the substrate, starting from the infrared temperature measurement cloud image corresponding to the first acquisition time. The emissivity determination module is used to determine the emissivity of the test heating wire at the second acquisition time as the target heating wire emissivity if the energy conservation residual at the second acquisition time is greater than or equal to the energy conservation residual at the first acquisition time, wherein the first acquisition time and the second acquisition time are two sequentially adjacent acquisition times.

9. An electronic device, characterized in that, include: Memory and processor; The memory is connected to the processor and is used to store programs; The processor is used to implement the emissivity determination method as described in any one of claims 1-7 by running a program in the memory.

10. A computer program product, characterized in that, Includes computer program instructions; When the computer program instructions are executed by the processor, the processor causes the processor to perform the emissivity determination method as described in any one of claims 1-7.

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