Infrared fusion temperature measurement system

Abstract

The application discloses an infrared fusion temperature measurement system, which comprises a dot array temperature measurement unit, an infrared surface array imaging unit, a time sequence control unit, a space mapping unit and a calibration unit. The time sequence control unit is used for controlling the synchronization error of the acquisition time sequence of the reference temperature data and the infrared original gray data within a preset error. The space mapping unit is used for determining a central region in the infrared original gray data, which corresponds to the temperature measurement field of view of the dot array temperature measurement unit. The calibration unit comprises a reference construction module, a region division module and a temperature conversion module, which are used for constructing the average gray value of the central region and the reference temperature data into a calibration reference pair, dividing the imaging region of the infrared original gray data into a plurality of calibration units, and generating the calibrated surface array infrared data. The application can ensure the calibration consistency of the temperatures of the regions of the surface array and maintain stable calibration precision in a high-temperature dynamic scene.

Description

Technical Field

[0001] This application belongs to the field of temperature calibration technology, specifically relating to an infrared fusion temperature measurement system. Background Technology

[0002] Area array infrared thermometry technology has been widely used in industrial high-temperature monitoring and equipment thermal fault diagnosis because it can reveal the spatial temperature distribution characteristics of the measured target. However, the accuracy of traditional area array infrared thermometry has always been hampered by insurmountable bottlenecks, falling far short of the precision level of unit array thermometry.

[0003] Currently, the calibration method for area array infrared temperature measurement is mainly a pure algorithm correction scheme. The pure algorithm correction scheme only relies on the data collected by the area array detector itself and makes corrections through environmental temperature compensation, blackbody single-point calibration, etc. This type of method lacks the closed-loop participation of an external high-precision temperature measurement reference, making it difficult to meet the high-precision temperature measurement requirements in high-temperature environments.

[0004] To address this need, related technologies have proposed a unit-area array fusion temperature measurement scheme. However, such schemes can usually only achieve simple single-point value replacement, making it difficult to guarantee an effective correspondence between the unit array reference and the area array data. The calibration effect is unstable in high-temperature dynamic scenarios. At the same time, the correction of the entire area temperature measurement data is relatively simplified, and the correction of the entire area data is completed by simply scaling the scale. This results in poor temperature calibration consistency in different areas of the area array, and cannot ensure the accuracy and reliability of the area array temperature measurement data. Summary of the Invention

[0005] This application provides an infrared fusion temperature measurement system that can ensure the calibration consistency of temperature in each area of ​​the array and maintain stable calibration accuracy even in high-temperature dynamic scenarios.

[0006] To address the aforementioned technical problems, this application provides an infrared fusion temperature measurement system, comprising: The dot matrix temperature measurement unit is used to perform point-like temperature measurement on the target and output reference temperature data; The infrared external array imaging unit is used to perform area array imaging on the target under test and output raw infrared grayscale data. A timing control unit is used to simultaneously acquire the reference temperature data and the infrared raw grayscale data, and control the timing synchronization error of the acquisition of the reference temperature data and the infrared raw grayscale data within a preset error. A spatial mapping unit is used to determine the central region in the infrared raw grayscale data that corresponds to the temperature measurement field of view of the dot matrix temperature measurement unit, based on the spatial coordinate mapping relationship between the dot matrix temperature measurement unit and the infrared external array imaging unit. A calibration unit is connected to the dot matrix temperature measurement unit, the infrared external array imaging unit, the timing control unit, and the spatial mapping unit. The calibration unit includes: The reference construction module is used to extract the gray values ​​of each pixel in the central region from the raw infrared gray data, and construct a calibration reference pair by combining the average gray value of the central region with the reference temperature data. The region division module is used to divide the imaging area of ​​the infrared raw grayscale data into several calibration units, using the pixel area of ​​the central region as the standard unit. The temperature conversion module is used to calculate the average gray value of each calibration unit, and convert the average gray value of each calibration unit into the corresponding temperature value based on the calibration reference pair, thereby generating calibrated area array infrared data.

[0007] As a further improvement of this application, the timing control unit is used to obtain a first timestamp when the dot matrix temperature measurement unit collects reference temperature data, and a second timestamp when the infrared external array imaging unit collects infrared raw grayscale data. The first timestamp and the second timestamp are matched to ensure that the timing synchronization error between the matched reference temperature data and the original infrared grayscale data is ≤10ms.

[0008] As a further improvement of this application, the spatial mapping unit is used to establish a spatial coordinate mapping relationship between the temperature measurement field of view of the dot matrix temperature measurement unit and the pixel position of each pixel in the infrared raw grayscale data, based on the temperature measurement field of view of the dot matrix temperature measurement unit and the pixel resolution of the infrared array imaging unit. Furthermore, through the spatial coordinate mapping relationship, the pixel region corresponding to the light spot of the dot matrix temperature measuring unit in the original infrared grayscale data is determined as the central region.

[0009] As a further improvement of this application, the region division module is used to divide the imaging region into equal grids using the pixel area of ​​the central region as the standard unit, so that the pixel area of ​​each calibration unit is equal to the pixel area of ​​the central region.

[0010] As a further improvement of this application, the calibration unit further includes a normalization processing module, which is used to smooth the temperature values ​​converted by each calibration unit through an interpolation algorithm, so that the temperature value of the central region in the normalized and corrected area array infrared data deviates from the reference temperature data output by the dot matrix temperature measurement unit by ≤±0.5℃.

[0011] As a further improvement to this application, the infrared fusion temperature measurement system further includes an output unit connected to the calibration unit, the output unit comprising: A wireless communication module is used to send the calibrated area array infrared data to an external terminal, which may include an industrial MES system, a remote monitoring platform, or a smart terminal. The gradient map generation module is used to generate a temperature gradient distribution map based on the calibrated area array infrared data, and to mark isotherms in the temperature gradient distribution map. An alarm module is used to extract temperature feature parameters from the temperature gradient distribution map and generate alarm information when the temperature feature parameters exceed a preset threshold. The temperature characteristic parameters include the highest temperature, lowest temperature, maximum temperature difference, or location of hot spots of the target being measured.

[0012] As a further improvement of this application, the dot matrix temperature measuring unit is an indium gallium arsenide dot thermometer, and the infrared array imaging unit is an organic infrared array camera, a quantum dot infrared array camera, or an indium gallium arsenide infrared array camera. The dot matrix temperature measuring unit and the infrared array imaging unit are coaxially fixedly arranged.

[0013] As a further improvement of this application, the infrared fusion temperature measurement system further includes a computing power processing unit, in which the timing control unit, the spatial mapping unit and the calibration unit are all integrated, and the computing power processing unit is used to provide at least 6 TOPS of computing power resources.

[0014] As a further improvement of this application, the infrared fusion temperature measurement system further includes a housing, and the dot matrix temperature measurement unit, the infrared array imaging unit, the timing control unit, the spatial mapping unit, the calibration unit and the computing power processing unit are all disposed inside the housing; The housing has a temperature measurement window corresponding to the dot matrix temperature measurement unit and an imaging window corresponding to the infrared array imaging unit.

[0015] As a further improvement of this application, the infrared fusion temperature measurement system also includes a mounting bracket, on which the housing is fixed to adjust the orientation and pitch angle of the dot matrix temperature measurement unit and the infrared external array imaging unit.

[0016] This application provides an infrared fusion temperature measurement system that synchronously acquires the reference temperature data of the dot matrix temperature measurement unit and the raw infrared grayscale data of the infrared external array imaging unit through a timing control module. The timing synchronization error between the reference temperature data and the raw infrared grayscale data is controlled within a preset error, achieving accurate matching between the reference temperature data and the raw infrared grayscale data in the time dimension. The spatial mapping unit determines the central region corresponding to the dot matrix temperature measurement field of view based on the spatial coordinate mapping relationship, ensuring that the reference temperature data and the raw infrared grayscale data can accurately correspond to the same physical location of the measured target. Subsequently, the reference construction module of the calibration unit extracts the grayscale values ​​of each pixel in the central region and calculates the average grayscale value, constructing a calibration reference pair with the reference temperature data, thus mitigating the deviation caused by single pixel anomalies.

[0017] Furthermore, the region division module of the calibration unit divides the imaging area into several calibration units using the pixel area of ​​the central region as the standard unit, avoiding the problem of inconsistent calibration standards caused by differences in regional area. Finally, the temperature conversion module of the calibration unit calculates the average gray value of each calibration unit, converts it into the corresponding temperature value based on the calibration reference, and generates calibrated area array infrared data. This ensures that the temperature value of each calibration unit is corrected based on the high-precision temperature value of the central region, avoiding the problem of poor overall calibration consistency caused by only single-point replacement or linear scaling in traditional fusion schemes. This ensures the temperature calibration consistency of each region of the area array and maintains stable calibration accuracy even in high-temperature dynamic scenarios. Attached Figure Description

[0018] 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 a part of the embodiments of this application, and not all of the embodiments. For those skilled in the art, other drawings obtained from these drawings without creative effort are all within the scope of protection of this application.

[0019] Figure 1 This is a functional block diagram of the infrared fusion temperature measurement system provided in the embodiments of this application.

[0020] Figure 2 This is a schematic diagram of the structure of the dot matrix temperature measurement unit in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0021] Figure 3 This is a schematic diagram of the structure of the infrared array imaging unit in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0022] Figure 4 This is a schematic diagram of the structure of the light spot in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0023] Figure 5 This is a schematic diagram of the structure of the infrared fusion temperature measurement system provided in the embodiments of this application, which controls the timing synchronization error within a preset error.

[0024] Figure 6 This is a functional block diagram of the calibration unit in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0025] Figure 7 This is a functional block diagram of the output unit in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0026] Figure 8 This is a functional block diagram of the computing power processing unit in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0027] Figure 9 This is a schematic diagram of the housing structure in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0028] Figure 10 This is a schematic diagram of the structure of the imaging window and the temperature measurement window in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0029] Figure 11 This is a three-dimensional assembly drawing of the housing in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0030] Figure 12 This is a schematic diagram of the mounting bracket in the infrared fusion temperature measurement system provided in the embodiments of this application.

[0031] Figure 13 This is a diagram of a specific embodiment of the infrared fusion temperature measurement system provided in this application.

[0032] Figure 14 for Figure 13 The example diagram of normalization correction in the specific embodiment shown is shown.

[0033] Figure 15 for Figure 13 The temperature gradient distribution diagram of the specific embodiment is shown. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0035] To make the description of this disclosure more detailed and complete, illustrative descriptions of the implementation methods and specific embodiments of this application are provided below; however, this is not the only form of implementing or utilizing the specific embodiments of this application. The implementation methods cover the features of multiple specific embodiments and the method steps and their order for constructing and operating these specific embodiments. However, other specific embodiments can also be used to achieve the same or equivalent functions and step sequences. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0036] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in sequences other than those illustrated or described herein.

[0037] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The word "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more. Other quantifiers should be understood similarly. The preferred embodiments described herein are only for illustration and explanation of this application and are not intended to limit this application. Furthermore, the embodiments of this application and the features in the embodiments can be combined with each other without conflict.

[0038] Area array infrared thermometry technology has been widely used in industrial high-temperature monitoring and equipment thermal fault diagnosis because it can reveal the spatial temperature distribution characteristics of the measured target. However, the accuracy of traditional area array infrared thermometry has always been hampered by insurmountable bottlenecks, falling far short of the precision level of unit array thermometry.

[0039] Currently, the calibration method for area array infrared temperature measurement is mainly a pure algorithm correction scheme. The pure algorithm correction scheme only relies on the data collected by the area array detector itself and makes corrections through environmental temperature compensation, blackbody single-point calibration, etc. This type of method lacks the closed-loop participation of an external high-precision temperature measurement reference, making it difficult to meet the high-precision temperature measurement requirements in high-temperature environments.

[0040] To address this need, related technologies have proposed a unit-area array fusion temperature measurement scheme. However, such schemes can usually only achieve simple single-point value replacement, making it difficult to guarantee an effective correspondence between the unit array reference and the area array data. The calibration effect is unstable in high-temperature dynamic scenarios. At the same time, the correction of the entire area temperature measurement data is relatively simplified, and the correction of the entire area data is completed by simply scaling the scale. This results in poor temperature calibration consistency in different areas of the area array, and cannot ensure the accuracy and reliability of the area array temperature measurement data.

[0041] In view of this, please refer to Figures 1-15 This application proposes an infrared fusion temperature measurement system that can ensure the calibration consistency of temperature in each area of ​​the array and maintain stable calibration accuracy in high-temperature dynamic scenarios.

[0042] Please refer to Figure 1 The diagram below shows the functional modules of the infrared fusion temperature measurement system provided in this application embodiment. The infrared fusion temperature measurement system includes: a dot matrix temperature measurement unit, an infrared array imaging unit, a timing control unit, a spatial mapping unit, and a calibration unit.

[0043] In this embodiment, the dot matrix temperature measurement unit is used to perform point temperature measurement on the target and output reference temperature data; the infrared array imaging unit is used to perform area array imaging on the target and output infrared raw grayscale data; the timing control unit is used to simultaneously acquire the reference temperature data and the infrared raw grayscale data, and control the timing synchronization error between the acquisition of the reference temperature data and the infrared raw grayscale data within a preset error; the spatial mapping unit is used to determine the central region in the infrared raw grayscale data corresponding to the temperature measurement field of view of the dot matrix temperature measurement unit according to the spatial coordinate mapping relationship between the dot matrix temperature measurement unit and the infrared array imaging unit; the calibration unit is connected to the dot matrix temperature measurement unit, the infrared array imaging unit, the timing control unit and the spatial mapping unit.

[0044] Specifically, the aforementioned calibration unit includes a reference construction module, a region division module, and a temperature conversion module. The reference construction module extracts the grayscale values ​​of each pixel within the central region from the raw infrared grayscale data, and constructs a calibration reference pair by combining the average grayscale value of the central region with the reference temperature data. The region division module divides the imaging area of ​​the raw infrared grayscale data into several calibration units, using the pixel area of ​​the central region as the standard unit. The temperature conversion module calculates the average grayscale value of each calibration unit, converts the average grayscale value of each calibration unit into a corresponding temperature value based on the calibration reference pair, and generates calibrated area array infrared data.

[0045] Understandably, please refer to Figure 2This is a schematic diagram of the structure of the dot matrix temperature measurement unit in the infrared fusion temperature measurement system provided in the embodiments of this application. The dot matrix temperature measurement unit is a temperature measurement component with high-precision temperature measurement characteristics. It is usually used to measure the temperature of targets within a specific field of view and can output high-precision reference temperature data of the temperature measurement field of view corresponding to the measured target as a reference for subsequent temperature calibration.

[0046] Please refer to Figure 3 This is a schematic diagram of the infrared external array imaging unit in the infrared fusion temperature measurement system provided in this application embodiment. The infrared external array imaging unit is used to acquire the infrared radiation distribution information of the target being measured. Its output is the raw infrared grayscale data. The raw infrared grayscale data can intuitively reflect the infrared radiation intensity distribution at different locations of the target being measured.

[0047] During actual data acquisition, the dot matrix temperature measurement unit and the infrared array imaging unit operate independently. This application synchronously acquires the reference temperature data output by the dot matrix temperature measurement unit and the raw infrared grayscale data output by the infrared array imaging unit through a timing control unit. For example, by using hardware triggering or software timestamp matching, the acquired reference temperature data and the raw infrared grayscale data accurately correspond to the temperature measurement status of the target at the same moment, avoiding calibration deviations caused by inconsistent acquisition times.

[0048] It should be noted that although the timing control unit has completed the synchronous acquisition of the reference temperature data and the raw infrared grayscale data, the dot matrix temperature measurement unit and the infrared array imaging unit will still have slight timing synchronization errors during the actual acquisition process due to differences in hardware response speed and data transmission links.

[0049] Furthermore, if the timing synchronization error is not effectively controlled, in high-temperature dynamic temperature measurement scenarios, the temperature of the target being measured may change within the deviation time, which will cause the reference temperature data and the original infrared grayscale data to not accurately correspond to the same state of the target being measured, thereby affecting the accuracy of subsequent calibration. Therefore, it is necessary to align the acquisition timing of the reference temperature data and the original infrared grayscale data and control their timing synchronization error within the preset error.

[0050] Based on this, please refer to Figure 5 This is a schematic diagram of the structure of the infrared fusion temperature measurement system provided in this application embodiment, which controls the timing synchronization error within a preset error. This application sets a timing control unit to obtain a first timestamp when the dot matrix temperature measurement unit collects reference temperature data, and a second timestamp when the infrared external array imaging unit collects infrared raw grayscale data; and matches the first timestamp and the second timestamp so that the timing synchronization error between the matched reference temperature data and the infrared raw grayscale data is ≤10ms.

[0051] Understandably, a timestamp is a time identifier used to accurately record the actual moment when data is collected. It is necessary to first obtain the first timestamp when the dot matrix temperature measurement unit collects the reference temperature data, and the second timestamp when the infrared array imaging unit collects the infrared raw grayscale data.

[0052] Specifically, the first timestamp is the record of the moment when the dot matrix temperature measurement unit completes the acquisition of the reference temperature data and generates the data, and the second timestamp is the record of the moment when the infrared array imaging unit completes the acquisition of the infrared raw grayscale data and generates the data.

[0053] After obtaining the first and second timestamps, the timing control unit needs to compare and match the first and second timestamps. For example, it can select the reference temperature data and the original infrared grayscale data with the required timestamp difference through software filtering and data timing adjustment, or perform timing calibration on the reference temperature data and the original infrared grayscale data with a small time difference to ensure that the timing synchronization error between the matched reference temperature data and the original infrared grayscale data is ≤10ms.

[0054] It should be noted that the aforementioned timing synchronization error of ≤10ms is determined in conjunction with the temperature measurement requirements of high-temperature scenarios. This can effectively avoid the problem of deviation in the corresponding temperature state of the measured target due to excessive timing deviation, and ensure the accurate correspondence between the reference temperature data and the original infrared grayscale data in the time dimension. This application does not impose any restrictions on the specific value of the timing synchronization error.

[0055] In this embodiment of the application, after the timing alignment of the reference temperature data and the original infrared grayscale data is completed, it is necessary to further establish the spatial correspondence between the reference temperature data and the original infrared grayscale data through the spatial mapping unit.

[0056] The dot matrix temperature measurement unit usually has a specific temperature measurement field of view, which can perform high-precision temperature measurement on the specific temperature measurement field of the target. The infrared external array imaging unit collects the infrared raw grayscale data of the entire target surface and outputs a pixel array covering the entire target surface. Therefore, it is necessary to use the spatial mapping unit to determine the central region in the infrared raw grayscale data that corresponds to the temperature measurement field of view of the dot matrix temperature measurement unit.

[0057] In an optional embodiment, the aforementioned spatial mapping unit is used to establish a spatial coordinate mapping relationship between the temperature measurement field of view of the dot matrix temperature measurement unit and the pixel position of each pixel in the infrared raw grayscale data, based on the temperature measurement field of view of the dot matrix temperature measurement unit and the pixel resolution of the infrared array imaging unit.

[0058] Furthermore, through the spatial coordinate mapping relationship, the pixel region corresponding to the light spot of the dot matrix temperature measuring unit in the original infrared grayscale data is determined as the central region.

[0059] For example, the temperature measurement field of view of the dot matrix temperature measurement unit is usually a spot area with a specific angle range, while the infrared external array imaging unit images the entire surface area of ​​the target being measured through a pixel array.

[0060] Please refer to Figure 4 The diagram shows the structure of the light spot in the infrared fusion temperature measurement system provided in this application embodiment. In practical applications, the dot matrix temperature measurement unit and the infrared external array imaging unit are usually installed in a coaxial or fixed relative position, so that the spatial positional relationship between the dot matrix temperature measurement unit and the infrared external array imaging unit is determined. Therefore, the spatial mapping unit can map the temperature measurement field boundary of the dot matrix temperature measurement unit to the pixel coordinate system of the area array image through the principle of geometric optics.

[0061] As an optional implementation, the spatial mapping unit can calculate the pixel region corresponding to the temperature measurement field of view of the dot matrix temperature measurement unit in the area array image based on the field angle parameters of the dot matrix temperature measurement unit and the pixel resolution of the infrared external array imaging unit, thereby establishing a spatial coordinate mapping relationship between the temperature measurement field of view of the dot matrix temperature measurement unit and the pixel positions in the original infrared grayscale data.

[0062] Furthermore, the pixel region corresponding to the light spot of the dot matrix temperature measuring unit in the original infrared grayscale data can be determined through the above spatial coordinate mapping relationship.

[0063] Specifically, the light spot of the dot matrix temperature measuring unit is a light spot area with a certain area size. Through spatial coordinate mapping, the boundary contour of the light spot can be converted into pixel coordinates in the area array image. The pixels surrounded by the light spot boundary constitute a continuous pixel area, which is the pixel area corresponding to the light spot of the dot matrix temperature measuring unit in the infrared raw grayscale data, that is, the central area.

[0064] It is understandable that the reference temperature data output by the dot matrix temperature measurement unit reflects the overall temperature information within the coverage area of ​​its spot, rather than the temperature of a single pixel. Therefore, the corresponding central area should be the pixel area composed of all the pixels covered by the spot.

[0065] It should be noted that the reference temperature data output by the dot matrix temperature measurement unit is a specific temperature value, reflecting the overall temperature level within the area covered by the light spot; while the infrared raw grayscale data output by the infrared array imaging unit is the grayscale value of each pixel, which has not yet been converted into a temperature value.

[0066] The central region is the pixel area corresponding to the spot of the dot matrix temperature measurement unit in the area array image. This pixel area contains multiple pixels, each of which corresponds to a gray value. Therefore, the reference construction module needs to extract the gray values ​​of each pixel in the central region from the original infrared gray data, calculate the arithmetic mean of these gray values, and obtain the average gray value of the central region.

[0067] Furthermore, the reference construction module constructs a calibration reference pair by combining the average gray value of the central area with the reference temperature data, forming a one-to-one calibration reference pair. This allows the gray values ​​of other areas in the array to be converted to temperature based on the calibration reference pair, thereby achieving calibration of the entire surface temperature measurement data.

[0068] In this embodiment, the reference temperature data output by the dot matrix temperature measurement unit reflects the average temperature within the coverage area of ​​its spot. The central region corresponding to the spot in the area array image contains multiple pixels. The gray values ​​of these pixels are averaged and then used to establish a calibration reference pair with the reference temperature data.

[0069] For pixels in other areas of the area array image, if temperature conversion is performed directly on a single pixel basis, the calibration results will be unstable due to large fluctuations in the grayscale value of a single pixel. Therefore, it is necessary to divide the entire imaging area into several calibration units with an area equal to that of the central area.

[0070] As an optional implementation, the region segmentation module needs to first obtain the pixel area of ​​the central region, and then use the pixel area of ​​the central region as the standard unit to perform equal grid segmentation on the imaging area of ​​the entire infrared raw grayscale data.

[0071] Specifically, the region segmentation module divides the imaging region into several equal-sized calibration units according to rows and columns, ensuring that the pixel area of ​​each calibration unit is equal to the pixel area of ​​the central region. If the boundary of the imaging region cannot be completely divided by the standard unit, the boundary blocks can be appropriately processed, such as by partial overlap or zero padding, to ensure that the pixel area of ​​each calibration unit is as close as possible to the pixel area of ​​the central region.

[0072] It is understandable that since the average gray value of the central area and the reference temperature data have already established a calibration reference pair, and the other calibration units are the same in area as the central area, the average gray value of each calibration unit can be converted to temperature based on the same calibration reference pair, thereby ensuring that the temperature data of the entire surface has a unified reference during the calibration process.

[0073] In this embodiment, after the imaging area is divided into grids, the temperature conversion module needs to perform temperature conversion on each calibration unit. Based on the calibration reference, the average gray value of each calibration unit is converted into the corresponding temperature value to generate calibrated area array infrared data.

[0074] It should be noted that the correlation between the raw infrared grayscale data of the infrared external array imaging unit and the temperature of the target being measured is common knowledge in the field of infrared thermometry. That is, the infrared external array imaging unit receives the infrared radiation signal of the target being measured and converts it into grayscale data. The higher the temperature of the target being measured, the stronger the intensity of the infrared radiation emitted outward, and the stronger the radiation signal received by the infrared external array imaging unit, and the larger the corresponding output grayscale value. In other words, the grayscale value and temperature have a clear positive correlation.

[0075] Based on this common knowledge, theoretically, the corresponding temperature value can be calculated from the known gray value. However, when directly using the original gray value for temperature conversion, the conversion result often has significant deviations due to the characteristics of the infrared array imaging unit itself and environmental factors, which cannot meet the requirements of high-precision temperature measurement.

[0076] Based on this, since the reference temperature data has high temperature measurement accuracy and reflects the actual temperature of the target in the spot area, and the calibration reference pair is composed of the average gray value of the central area and the reference temperature data output by the dot matrix temperature measurement unit, the calibration of the entire infrared raw gray value data can be achieved when the calibration reference pair is known.

[0077] Specifically, for each calibration unit, the temperature conversion module needs to calculate the average gray value of all pixels within that calibration unit. The gray value is positively correlated with the temperature, and the calibration reference pair provides a precise correspondence between the average gray value of the central area and the actual temperature. Therefore, for other calibration units, the temperature value corresponding to that calibration unit can be determined based on the relative magnitude of its average gray value and the average gray value of the central area, combined with the positive correlation.

[0078] Furthermore, after completing the temperature value calculation and conversion of all calibration units, calibrated area array infrared data is generated. This calibrated area array infrared data not only retains the original temperature spatial distribution information of the area array imaging, but also matches the benchmark level of the dot matrix temperature measurement unit in terms of temperature measurement accuracy, providing an accurate data foundation for subsequent engineering applications such as temperature gradient map generation and intelligent alarm.

[0079] As an optional implementation method, please refer to Figure 6 The diagram shows the functional modules of the calibration unit in the infrared fusion temperature measurement system provided in this application embodiment. The infrared fusion temperature measurement system provided in this application embodiment also includes a normalization processing module. This normalization processing module is used to smooth the temperature values ​​converted by each calibration unit through an interpolation algorithm, so that the temperature value of the central region in the normalized and corrected area array infrared data deviates from the reference temperature data output by the dot array temperature measurement unit by ≤±0.5℃.

[0080] In this embodiment, after the temperature conversion of each calibration unit is completed, since each calibration unit performs temperature conversion independently, there may be discontinuities in the temperature values ​​between adjacent calibration units. This manifests as obvious blocky boundaries or step-like jumps in the temperature field, which do not match the actual temperature distribution characteristics of the measured target and will affect the accuracy of the subsequent temperature gradient map generation. Therefore, this application preferably uses a normalization processing module to smooth the converted temperature values ​​of each calibration unit to eliminate the boundary discontinuity problem caused by block calibration.

[0081] In an optional embodiment, the normalization processing module can smooth the converted temperature values ​​of each calibration unit using an interpolation algorithm. This interpolation algorithm is based on the temperature value differences between adjacent calibration units and performs transition processing on the temperature values ​​of the boundary region through interpolation calculation.

[0082] Specifically, for two adjacent calibration units, their converted temperature values ​​are obtained respectively. Linear interpolation, bilinear interpolation, or other interpolation algorithms are used to calculate the temperature values ​​of each pixel at the junction of the two calibration units, so that the temperature change in the junction area presents a smooth transition rather than a step jump. This effectively eliminates the discontinuity of the temperature field originally caused by block processing, and the spatial distribution of the temperature data of the whole surface is more in line with the actual temperature distribution of the target being measured.

[0083] After smoothing, it is also necessary to ensure that the deviation between the temperature value of the central area and the reference temperature data output by the dot matrix temperature measurement unit is controlled within ±0.5℃.

[0084] Thus, this application ensures that the normalized and corrected area array infrared data not only has good continuity in spatial distribution, but also achieves effective alignment with the reference level of the dot array temperature measurement unit in terms of temperature measurement accuracy through the smoothing processing of the interpolation algorithm and the limitation of the deviation threshold.

[0085] As an optional implementation method, please refer to Figure 7 The diagram below shows the functional block diagram of the output unit in the infrared fusion temperature measurement system provided in this application embodiment. The infrared fusion temperature measurement system provided in this application embodiment also includes an output unit connected to the calibration unit. The output unit further includes a wireless communication module, a gradient map generation module, and an alarm module.

[0086] Specifically, the aforementioned wireless communication module is used to send the calibrated area array infrared data to an external terminal, which includes an industrial MES system, a remote monitoring platform, or a smart terminal; the aforementioned gradient map generation module is used to generate a temperature gradient distribution map based on the calibrated area array infrared data, and to mark isotherms in the temperature gradient distribution map; the aforementioned alarm module is used to extract temperature feature parameters from the temperature gradient distribution map, and to generate alarm information when the temperature feature parameters exceed a preset threshold; wherein, the temperature feature parameters include the highest temperature, lowest temperature, maximum temperature difference, or hot spot location of the measured target.

[0087] In the embodiments of this application, after the normalization correction is completed and the calibrated area infrared data is obtained, the area infrared data will exist in the form of discrete pixels, each pixel corresponding to a temperature value. It is impossible to intuitively judge the overall temperature distribution trend, nor can it quickly identify hot spots and areas with drastic temperature changes.

[0088] Preferably, this application uses a gradient map generation module to convert discrete area array infrared data into a visualized temperature gradient distribution map, so as to intuitively present the temperature field information of the target under test.

[0089] For example, a corresponding temperature gradient distribution map can be generated using a bilinear interpolation algorithm, a commonly used image processing algorithm used to convert discrete pixel data into a continuous color level image.

[0090] Specifically, for calibrated area infrared data, each pixel has a temperature value, which can be mapped to a corresponding color. For example, high-temperature areas are mapped to red or bright colors, and low-temperature areas are mapped to blue or dark colors.

[0091] Using bilinear interpolation, for any two adjacent pixels, the temperature value at the midpoint is calculated linearly based on the temperature values ​​of these two pixels and their distance relationship. This fills the discrete pixels into a continuous temperature-gradient image. After bilinear interpolation, a temperature gradient distribution map is generated. In this map, temperature changes are presented as smooth color-gradient transitions, rather than discrete color block boundaries, making the spatial distribution of the temperature field of the measured target immediately clear.

[0092] Based on the generated temperature gradient distribution map, the gradient map generation module can also mark isotherms on the map using an isotherm fitting algorithm. For example, a specific temperature threshold can be selected, and the isotherm fitting algorithm can be used to find all points with temperature values ​​equal to the threshold and connect these points into a smooth curve, thereby intuitively reflecting the temperature distribution.

[0093] In an optional embodiment, the temperature gradient distribution map includes information such as the spatial distribution of the temperature field of the target being measured, hotspot locations, and temperature difference ranges. The spatial distribution of the temperature field reflects the overall temperature distribution of the target's surface; hotspot locations refer to local areas where the temperature is significantly higher than the surrounding area, which can be quickly located by the darkest areas or the areas with the densest isotherms in the image; the temperature difference range refers to the difference between the highest and lowest temperatures on the target's surface, which can be intuitively determined by comparing the color levels of the highest and lowest temperature areas in the image, allowing for a quick and accurate understanding of the target's temperature state.

[0094] Furthermore, the alarm module extracts temperature characteristic parameters reflecting the temperature distribution characteristics from the calibrated area array infrared data or temperature gradient distribution map.

[0095] Optionally, the temperature characteristic parameters here may include the highest temperature, lowest temperature, maximum temperature difference, and location of hotspot areas of the target being measured.

[0096] Among them, the highest temperature refers to the maximum value of the temperature of all pixels in the calibrated area infrared data, reflecting the point with the highest temperature on the target being measured; the lowest temperature refers to the minimum value of the temperature of all pixels, reflecting the point with the lowest temperature; the maximum temperature difference is the difference between the highest temperature and the lowest temperature, reflecting the uniformity of the overall temperature distribution of the target being measured; the hot spot area refers to the local area with a temperature significantly higher than the surrounding area, which can be determined by identifying the set of pixels whose temperature values ​​exceed a certain range. All of the above temperature characteristic parameters can be directly calculated from the calibrated area infrared data.

[0097] Based on this, the alarm module sets a corresponding preset threshold for each temperature characteristic parameter.

[0098] For example, for the highest temperature, an upper limit threshold can be set. When the highest temperature of the target being measured exceeds the upper limit threshold, it indicates that there is a risk of overheating. For the lowest temperature, a lower limit threshold can be set. When the lowest temperature is below the lower limit threshold, it indicates that there may be an abnormal cold zone. For the maximum temperature difference, an allowable temperature difference range can be set. When the actual temperature difference exceeds the temperature difference range, it indicates that the temperature distribution is uneven and there may be local defects. For the location of hot spots, an area or temperature intensity threshold for the hot spot can be set. When the hot spot exceeds the allowable range, an alarm is triggered.

[0099] Of course, the type of temperature characteristic parameters and the size of the preset threshold corresponding to each temperature characteristic parameter can be adjusted according to the specific needs of the actual application scenario. This application does not impose any restrictions on this.

[0100] When the extracted temperature characteristic parameters exceed the corresponding preset threshold, the alarm module will automatically generate alarm information so that operators can promptly grasp the abnormal temperature status of the measured target and take corresponding measures to achieve rapid response to thermal failures, process abnormalities and other situations in industrial field equipment.

[0101] In this embodiment of the application, after completing the calibration of the area array infrared data, the generation of the temperature gradient map, and the determination of the intelligent alarm, the wireless communication module can output these area array infrared data, temperature gradient maps, or alarm information to the corresponding external terminal so that the operator can provide timely feedback.

[0102] It should be noted that the specific type of external terminal mentioned above can be selected according to the needs of the application scenario, such as an industrial MES (Manufacturing Execution System), a remote monitoring platform, or a smart terminal. Flexible data output configuration can meet the needs of different industrial scenarios for temperature measurement data applications. This application does not impose too many restrictions on this.

[0103] As an optional implementation, the dot matrix temperature measuring unit is an indium gallium arsenide dot thermometer, and the infrared array imaging unit is an organic infrared array camera, a quantum dot infrared array camera, or an indium gallium arsenide infrared array camera. The dot matrix temperature measuring unit and the infrared array imaging unit are coaxially fixed.

[0104] In this embodiment, the dot matrix temperature measurement unit preferably uses an indium gallium arsenide (IGaAs) dot thermometer. The IGaAs dot thermometer is a high-precision temperature measurement device that can perform single-point temperature measurement on targets within a specific field of view. By introducing the IGaAs dot thermometer as an external temperature measurement reference, the problem of insufficient calibration accuracy of the infrared array imaging unit itself can be effectively compensated.

[0105] Furthermore, the infrared array imaging unit preferably employs an organic infrared array camera or a quantum dot infrared array camera. Organic infrared array cameras are based on organic infrared detection technology, while quantum dot infrared array cameras are based on quantum dot infrared detection technology. Compared to traditional indium gallium arsenide infrared array detectors, these two types of detectors have the advantage of lower cost and are key components for realizing a low-cost, high-precision area array temperature measurement solution.

[0106] However, organic infrared detectors and quantum dot infrared detectors suffer from problems such as uneven responsivity between pixels and dark current drift in applications. This leads to a deviation in the correspondence between the gray values ​​of each pixel and the actual temperature of the target when they directly output raw infrared grayscale data. Moreover, this deviation is inconsistent between different pixels, making it difficult for traditional calibration algorithms to adapt effectively.

[0107] Based on this, this application combines a unit dot array thermometer with an organic infrared array camera or a quantum dot infrared array camera. While ensuring the temperature measurement accuracy of the entire surface, the overall cost is only 50% of that of a traditional pure indium gallium arsenide array thermometer, which greatly reduces the equipment cost.

[0108] Optionally, this application uses an organic infrared array camera to achieve precise measurement in the 1000nm band, and simultaneously uses a quantum dot infrared array camera to achieve precise measurement in the 1600nm band.

[0109] It should be noted that the 1000nm band refers to the infrared band range with a center wavelength of 1000nm and a bandwidth of no more than 100nm, that is, 950nm to 1050nm; the 1600nm band refers to the infrared band range with a center wavelength of 1600nm and a bandwidth of no more than 100nm, that is, 1550nm to 1650nm.

[0110] The selection of the above-mentioned bands is based on the fact that organic infrared detectors and quantum dot infrared detectors have high response sensitivity and good environmental adaptability in this band range, which can effectively reduce background radiation interference and improve the signal-to-noise ratio.

[0111] In an optional embodiment, the infrared array imaging unit can also be configured as an indium gallium arsenide infrared array camera.

[0112] It is understandable that indium gallium arsenide detectors have higher sensitivity and accuracy. The calibration reference of the calibration unit can still use the same processing logic as in the above embodiments for construction, region division and temperature conversion, so as to be suitable for high-end industrial scenarios with more stringent requirements for temperature measurement accuracy.

[0113] As an optional implementation method, please refer to Figure 8 The diagram below shows the functional block diagram of the computing power processing unit in the infrared fusion temperature measurement system provided in this application. The infrared fusion temperature measurement system provided in this application also includes a computing power processing unit. The timing control unit, the spatial mapping unit, and the calibration unit are all integrated into the computing power processing unit. The computing power processing unit is used to provide at least 6 TOPS (Tera Operations Per Second) of computing power resources.

[0114] In one specific embodiment, the aforementioned computing power processing unit can be configured as an AI (Artificial Intelligence) computing power board, which should integrate computing power resources of more than 6 TOPS and have a pre-installed algorithm model optimized for infrared fusion temperature measurement tasks.

[0115] Furthermore, this application deploys the timing control unit, spatial mapping unit, and calibration unit as software modules or firmware on the AI ​​computing power board. The AI ​​computing power board uniformly schedules computing resources to complete the timing synchronization, spatial mapping, grid calibration, and subsequent temperature gradient map generation and intelligent alarm judgment of the data.

[0116] Understandably, the 6TOPs computing power provided by the AI ​​computing board can process the high-frequency data streams of the dot matrix temperature measurement unit and the infrared array imaging unit in parallel. When the calibration unit performs gridded temperature conversion, it can simultaneously perform grayscale averaging calculation and temperature mapping on hundreds or thousands of calibration units, greatly reducing data processing latency and ensuring that the system can output calibrated area array infrared data in real time under high temperature dynamic scenarios.

[0117] As an optional implementation method, please refer to Figure 9 The diagram shows the structure of the housing in the infrared fusion temperature measurement system provided in this application embodiment. The infrared fusion temperature measurement system further includes the housing, and the dot matrix temperature measurement unit, the infrared external array imaging unit, the timing control unit, the spatial mapping unit, the calibration unit, and the computing power processing unit are all located inside the housing.

[0118] Further, please refer to Figure 10 This is a schematic diagram of the imaging window and the temperature measurement window in the infrared fusion temperature measurement system provided in the embodiment of this application. The present application has a temperature measurement window on the housing that corresponds to the dot matrix temperature measurement unit and an imaging window that corresponds to the infrared external array imaging unit.

[0119] In industrial high-temperature monitoring scenarios, the targets being measured are often distributed in different production stations or equipment areas. Therefore, this application integrates the dot matrix temperature measurement unit, infrared array imaging unit, timing control unit, spatial mapping unit, calibration unit and computing power processing unit into the same housing to improve the overall portability of the system and the flexibility of on-site deployment.

[0120] Furthermore, the housing can protect the internal precision optical components and electronic devices from harsh environmental factors such as dust, oil, vibration and temperature fluctuations in industrial environments, thereby improving the system's environmental adaptability and long-term operational reliability.

[0121] It should be noted that this application has separate temperature measurement windows corresponding to the dot matrix temperature measurement unit and imaging windows corresponding to the infrared array imaging unit on the housing, instead of setting the dot matrix temperature measurement unit and the infrared array imaging unit to share a single window. This is an optimized design based on the differences in working principle and optical path between the dot matrix temperature measurement unit and the infrared array imaging unit.

[0122] Specifically, dot matrix temperature measurement units typically use point-type temperature measurement. Their optical systems are quite sensitive to transmittance and the flatness of the window surface. If they share a window with other units, dirt or scratches on the window surface may directly interfere with the quality of the light spot and affect the accuracy of the reference temperature data acquisition.

[0123] The infrared array imaging unit needs to receive the infrared radiation distribution from the entire surface of the target being measured. Its imaging quality is closely related to the uniformity of transmission of the window and the field of view. The imaging window can be set separately to customize the window size and position according to the field of view of the area array camera, so as to ensure unobstructed and distortion-free full-frame imaging.

[0124] Furthermore, by setting the two windows separately, optical filters or protective lenses with different characteristics can be installed inside the windows. For example, a high-transmittance infrared filter can be added to the temperature measurement window to enhance the signal-to-noise ratio of the dot matrix temperature measurement, and a broadband anti-reflection film can be added to the imaging window to improve the grayscale response consistency of the area array imaging. This allows for targeted optimization of the performance of each unit, which will not be elaborated further in this application.

[0125] Further, please refer to Figure 12 This is a schematic diagram of the structure of the mounting bracket in the infrared fusion temperature measurement system provided in this application embodiment. The infrared fusion temperature measurement system also includes a mounting bracket. In this application, the housing is fixed on the mounting bracket so as to adjust the orientation and pitch angle of the dot matrix temperature measurement unit and the infrared external array imaging unit through the mounting bracket.

[0126] In practical applications, the aforementioned mounting brackets can be tripods or pan-tilt units. Tripods provide a stable support platform for the system, which is especially suitable for long-term fixed-point monitoring scenarios. They can effectively prevent the housing from shaking due to ground vibration or environmental disturbances, ensuring the long-term stability of the temperature measurement optical path and the imaging optical path.

[0127] The gimbal has multi-degree-of-freedom adjustment capabilities, allowing operators to flexibly adjust the horizontal rotation angle and vertical pitch angle of the housing according to the spatial position of the target being measured. This enables the light spot of the dot matrix temperature measurement unit and the field of view of the infrared array imaging unit to be quickly aligned with the target area, allowing for continuous scanning and monitoring of multiple angles and targets without moving the entire tripod.

[0128] Thus, the infrared fusion temperature measurement system provided in this application can not only meet the stringent stability requirements of long-term fixed monitoring, but also adapt to the actual needs of mobile inspection for flexibility, further expanding the applicability of the system in industrial high-temperature scenarios.

[0129] As an optional implementation method, please continue to refer to Figure 9This application also includes a display screen and buttons on the housing. The display screen is usually an industrial-grade LCD screen or an OLED (Organic Light Emitting Diode) screen, which is embedded in the back or side of the housing. It is used to display calibrated area array infrared data, temperature gradient distribution map, current highest temperature, lowest temperature, temperature difference and alarm status in real time, so that on-site operators can directly obtain temperature measurement results without relying on external terminals.

[0130] The buttons can be set as physical buttons or touch buttons to realize interactive functions such as power on / off, parameter setting, alarm threshold adjustment, image freezing and storage, and display brightness adjustment, so that the system has independent human-computer interaction capabilities.

[0131] In an optional embodiment, the present application also provides a battery and a charging power supply inside the housing, with the battery fixed inside the housing to provide working power for various functional modules such as the dot matrix temperature measurement unit, the infrared array imaging unit, the computing power processing unit, and the display screen.

[0132] Furthermore, the charging power supply includes a charging management circuit and a charging interface, which supports charging the battery when connected to an external power source, or directly powering the system, ensuring that the system can still operate stably under grid fluctuations or power outages, and avoiding the loss of critical temperature measurement data due to power outages.

[0133] Please refer to Figure 11 The above is a three-dimensional assembly drawing of the housing in the infrared fusion temperature measurement system provided in this application embodiment. Even if the above-mentioned dot matrix temperature measurement unit, infrared array imaging unit, timing control unit, spatial mapping unit, calibration unit, computing power processing unit, battery and charging power supply are all located inside the housing, the volume of the housing can still be controlled within the range of 230 mm × 217 mm × 100 mm (length × width × height), realizing the miniaturization and lightweight design of the system.

[0134] This compact size design allows the entire infrared fusion temperature measurement system to be easily packed into a portable bag or carried by hand, making it easy to install on a tripod or gimbal, and to be flexibly arranged and applied according to actual working conditions.

[0135] In one specific embodiment, please refer to Figure 13This is a specific embodiment of the infrared fusion temperature measurement system provided in this application. This application uses a sample heated to 1000℃ as the target to be measured. It sets up a dot matrix temperature measurement unit composed of an indium gallium arsenide dot thermometer and an infrared array imaging unit composed of an organic infrared array camera, a quantum dot infrared array camera, or an indium gallium arsenide infrared array camera. Combined with an AI computing power board (6TOPs computing power) equipped with a timing control unit, a spatial mapping unit, a calibration unit, and an output unit of the infrared fusion temperature measurement system of this application, and an industrial display terminal for receiving data, the following calibration and testing were performed.

[0136] Specifically, this application coaxially fixes the unit-array precision temperature measuring instrument and the infrared array imaging unit. A spatial coordinate mapping relationship is established between the unit-array temperature measuring instrument and the infrared array imaging unit through a spatial mapping unit, determining the central region in the raw infrared grayscale data corresponding to the temperature measuring field of view of the unit-array temperature measuring instrument. The basic response characteristics of the infrared array imaging unit are pre-calibrated according to the equipment parameters and written into the algorithm configuration file.

[0137] Meanwhile, alarm rules can be preset through the alarm module in the output unit according to the test requirements, such as the maximum sample temperature not exceeding 1000℃ and the maximum temperature difference not exceeding 50℃, and an alarm will be triggered immediately when the temperature or the difference exceeds the limit.

[0138] Furthermore, the high-temperature sample is heated to 1000℃ and kept at a stable temperature. The timing control module synchronously acquires the reference temperature data output by the dot matrix temperature measurement unit and the infrared raw grayscale data output by the infrared array imaging unit, and controls the timing synchronization error between the reference temperature data and the infrared raw grayscale data to within 5ms, ensuring the time consistency of the acquired data.

[0139] Based on this, please refer to Figure 14 ,for Figure 13 The example diagram of normalization correction in the specific embodiment shown is as follows: the gray value of each pixel in the central area is extracted by the reference construction module in the calibration unit, the average gray value of the central area is calculated, and the reference temperature value (1000℃) output by the dot matrix temperature measurement unit is obtained at the same time. The average gray value of the central area and the reference temperature value are used to construct a calibration reference pair.

[0140] Furthermore, the region division module of the calibration unit uses the pixel area of ​​the central region as the standard unit to divide the imaging area of ​​the infrared raw grayscale data into several calibration units, and the pixel area of ​​each calibration unit is the same as the pixel area of ​​the central region.

[0141] Under the same exposure conditions, the temperature conversion module of the calibration unit completes the temperature calibration of all calibration units on the entire surface based on the calibration reference and pre-calibration parameters.

[0142] After completing the temperature conversion of each calibration unit, the normalization processing module of the calibration unit smooths the converted temperature values ​​of each calibration unit through an interpolation algorithm to achieve normalization correction. After correction, the deviation between the temperature value of the central area and the reference temperature value output by the dot matrix temperature measurement unit does not exceed ±0.5℃.

[0143] Please refer to Figure 15 ,for Figure 13 The temperature gradient distribution map shown in the specific embodiment is generated by the gradient map generation module of the output unit through bilinear interpolation based on the calibrated area array infrared data, and isotherms are fitted to determine the hot spot location, highest temperature, lowest temperature and overall temperature difference on the sample surface.

[0144] Meanwhile, the alarm module of the output unit intelligently judges the temperature data and extracts the temperature characteristic parameters of the target from the calibrated area array infrared data. In this test, the highest temperature was 1000℃ and the maximum temperature difference was 22℃, and the preset alarm rules were not triggered.

[0145] Furthermore, the wireless communication module of the output unit outputs the calibrated area array infrared data and temperature gradient distribution map to the industrial display terminal in real time, and uploads the data to the factory MES system through the communication module to complete the accurate temperature measurement and monitoring of high-temperature samples.

[0146] Overall, this embodiment verifies the feasibility and effectiveness of the area array infrared data temperature calibration method of this application through a complete practical process. The entire process, from system initialization to data output, achieves high-precision area array temperature measurement of high-temperature samples.

[0147] It should be noted that the above embodiments are merely one specific implementation of this application, intended to help understand the technical solution of this application, and do not constitute a limitation on the scope of protection of this application. Those skilled in the art, based on reading this application, can make equivalent substitutions, combinations, or modifications to the technical features described in the embodiments, or adaptively adjust the specific parameters, hardware selection, and step sequence according to the actual application scenario.

[0148] In the infrared fusion temperature measurement system provided in this application, the dot matrix temperature measurement unit and the infrared array imaging unit are respectively connected to the timing control unit. The timing control unit, the spatial mapping unit, and the calibration unit are all integrated into the computing power processing unit. The calibration unit is connected to the dot matrix temperature measurement unit, the infrared array imaging unit, the timing control unit, and the spatial mapping unit.

[0149] Furthermore, the calibration unit includes a reference construction module, a region division module, a temperature conversion module, and a normalization processing module. The reference construction module and the region division module are respectively connected to the temperature conversion module, and the normalization processing module is connected to the temperature conversion module.

[0150] Furthermore, the output unit is connected to the calibration unit. The output unit includes a wireless communication module, a gradient map generation module, and an alarm module. The gradient map generation module and the alarm module are respectively connected to the wireless communication module.

[0151] Based on this, this application houses the dot matrix temperature measurement unit, the infrared array imaging unit, the timing control unit, the spatial mapping unit, the calibration unit, the computing power processing unit, the battery, and the charging power supply inside the housing. The housing has a temperature measurement window corresponding to the dot matrix temperature measurement unit and an imaging window corresponding to the infrared array imaging unit. The housing also has a display screen and buttons, which are connected to the computing power processing unit or the output unit, respectively.

[0152] It should be noted that the connections between the aforementioned units can be electrical connections, such as signal and power transmission via wires or ribbon cables, or wireless communication connections, such as data interaction via Bluetooth, Wi-Fi (Wireless Fidelity), or ZigBee (a low-power wireless communication protocol). The specific connection methods are common knowledge in the field, and those skilled in the art can flexibly choose based on factors such as the deployment environment, communication distance, anti-interference requirements, and cost budget of the actual application scenario. This application does not impose any restrictions in this regard.

[0153] This application provides an infrared fusion temperature measurement system that synchronously acquires the reference temperature data of the dot matrix temperature measurement unit and the raw infrared grayscale data of the infrared external array imaging unit through a timing control module. The timing synchronization error between the reference temperature data and the raw infrared grayscale data is controlled within a preset error, achieving accurate matching between the reference temperature data and the raw infrared grayscale data in the time dimension. The spatial mapping unit determines the central region corresponding to the dot matrix temperature measurement field of view based on the spatial coordinate mapping relationship, ensuring that the reference temperature data and the raw infrared grayscale data can accurately correspond to the same physical location of the measured target. Subsequently, the reference construction module of the calibration unit extracts the grayscale values ​​of each pixel in the central region and calculates the average grayscale value, constructing a calibration reference pair with the reference temperature data, thus mitigating the deviation caused by single pixel anomalies.

[0154] Furthermore, the region division module of the calibration unit divides the imaging area into several calibration units using the pixel area of ​​the central region as the standard unit, avoiding the problem of inconsistent calibration standards caused by differences in regional area. Finally, the temperature conversion module of the calibration unit calculates the average gray value of each calibration unit, converts it into the corresponding temperature value based on the calibration reference, and generates calibrated area array infrared data. This ensures that the temperature value of each calibration unit is corrected based on the high-precision temperature value of the central region, avoiding the problem of poor overall calibration consistency caused by only single-point replacement or linear scaling in traditional fusion schemes. This ensures the temperature calibration consistency of each region of the area array and maintains stable calibration accuracy even in high-temperature dynamic scenarios.

[0155] It should be noted that, in the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed between each other can be through some interfaces, or indirect coupling or communication connection between devices or units, and can be electrical, mechanical, or other forms.

[0156] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0157] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. An infrared fusion temperature measurement system, characterized in that, include: The dot matrix temperature measurement unit is used to perform point-like temperature measurement on the target and output reference temperature data; The infrared external array imaging unit is used to perform area array imaging on the target under test and output raw infrared grayscale data. A timing control unit is used to simultaneously acquire the reference temperature data and the infrared raw grayscale data, and control the timing synchronization error of the acquisition of the reference temperature data and the infrared raw grayscale data within a preset error. A spatial mapping unit is used to determine the central region in the infrared raw grayscale data that corresponds to the temperature measurement field of view of the dot matrix temperature measurement unit, based on the spatial coordinate mapping relationship between the dot matrix temperature measurement unit and the infrared external array imaging unit. A calibration unit is connected to the dot matrix temperature measurement unit, the infrared external array imaging unit, the timing control unit, and the spatial mapping unit. The calibration unit includes: The reference construction module is used to extract the gray values ​​of each pixel in the central region from the raw infrared gray data, and construct a calibration reference pair by combining the average gray value of the central region with the reference temperature data. The region division module is used to divide the imaging area of ​​the infrared raw grayscale data into several calibration units, using the pixel area of ​​the central region as the standard unit. The temperature conversion module is used to calculate the average gray value of each calibration unit, and convert the average gray value of each calibration unit into the corresponding temperature value based on the calibration reference pair, thereby generating calibrated area array infrared data.

2. The infrared fusion temperature measurement system as described in claim 1, characterized in that, The timing control unit is used to acquire a first timestamp when the dot matrix temperature measurement unit collects reference temperature data, and to acquire a second timestamp when the infrared external array imaging unit collects infrared raw grayscale data. The first timestamp and the second timestamp are matched to ensure that the timing synchronization error between the matched reference temperature data and the original infrared grayscale data is ≤10ms.

3. The infrared fusion temperature measurement system as described in claim 1, characterized in that, The spatial mapping unit is used to establish a spatial coordinate mapping relationship between the temperature measurement field of view of the dot matrix temperature measurement unit and the pixel position of each pixel in the infrared raw grayscale data, based on the temperature measurement field of view of the dot matrix temperature measurement unit and the pixel resolution of the infrared array imaging unit. Furthermore, through the spatial coordinate mapping relationship, the pixel region corresponding to the light spot of the dot matrix temperature measuring unit in the original infrared grayscale data is determined as the central region.

4. The infrared fusion temperature measurement system as described in claim 1, characterized in that, The region division module is used to divide the imaging region into equal grids using the pixel area of ​​the central region as the standard unit, so that the pixel area of ​​each calibration unit is equal to the pixel area of ​​the central region.

5. The infrared fusion temperature measurement system as described in claim 1, characterized in that, The calibration unit also includes a normalization processing module, which is used to smooth the temperature values ​​converted by each calibration unit through an interpolation algorithm, so that the temperature value of the central region in the normalized area infrared data deviates from the reference temperature data output by the dot matrix temperature measurement unit by ≤±0.5℃.

6. The infrared fusion temperature measurement system as described in claim 1, characterized in that, The infrared fusion temperature measurement system further includes an output unit connected to the calibration unit, the output unit comprising: A wireless communication module is used to send the calibrated area array infrared data to an external terminal, which may include an industrial MES system, a remote monitoring platform, or a smart terminal. The gradient map generation module is used to generate a temperature gradient distribution map based on the calibrated area array infrared data, and to mark isotherms in the temperature gradient distribution map. An alarm module is used to extract temperature feature parameters from the temperature gradient distribution map and generate alarm information when the temperature feature parameters exceed a preset threshold. The temperature characteristic parameters include the highest temperature, lowest temperature, maximum temperature difference, or location of hot spots of the target being measured.

7. The infrared fusion temperature measurement system as described in claim 1, characterized in that, The dot matrix temperature measurement unit is an indium gallium arsenide dot thermometer, and the infrared array imaging unit is an organic infrared array camera, a quantum dot infrared array camera, or an indium gallium arsenide infrared array camera. The dot matrix temperature measurement unit and the infrared array imaging unit are coaxially fixed.

8. The infrared fusion temperature measurement system as described in claim 1, characterized in that, The infrared fusion temperature measurement system also includes a computing power processing unit. The timing control unit, the spatial mapping unit, and the calibration unit are all integrated into the computing power processing unit, which provides at least 6 TOPS of computing power resources.

9. The infrared fusion temperature measurement system as described in claim 8, characterized in that, The infrared fusion temperature measurement system also includes a housing, and the dot matrix temperature measurement unit, the infrared array imaging unit, the timing control unit, the spatial mapping unit, the calibration unit and the computing power processing unit are all located inside the housing; The housing has a temperature measurement window corresponding to the dot matrix temperature measurement unit and an imaging window corresponding to the infrared array imaging unit.

10. The infrared fusion temperature measurement system as described in claim 9, characterized in that, The infrared fusion temperature measurement system also includes a mounting bracket, on which the housing is fixed to adjust the orientation and pitch angle of the dot matrix temperature measurement unit and the infrared array imaging unit.

Images