Infrared temperature measurement method and infrared temperature measurement system based on laser ranging

Abstract

The invention provides an infrared temperature measurement method and an infrared temperature measurement system based on laser ranging, and relates to the technical field of infrared temperature measurement. According to the method, the clear contour and detail information of the target object in the target scene can be obtained through the visible light image acquisition assembly, so that the target object can be accurately identified and positioned; accurate distance information of a target object is collected through the laser ranging assembly, an infrared temperature measurement image of a target scene is collected through the infrared temperature measurement assembly, and temperature distribution information of the target scene is provided; through an image fusion algorithm, the distance information of the visible light image, the infrared temperature measurement image and the target object is subjected to data fusion, and the distance information of the target object is further fused in the fused image of the visible light image and the infrared temperature measurement image, so that the calibration of the infrared temperature measurement image is realized, and the influence of distance change on temperature measurement is eliminated; and the temperature measurement data is more accurate and reliable.

Description

Technical Field

[0001] The present application relates to the field of infrared temperature measurement technology, and in particular to an infrared temperature measurement method and an infrared temperature measurement system based on laser ranging. Background Art

[0002] In inspection and maintenance scenarios, a dual-light gimbal that integrates visible light and thermal imaging is usually installed on a mobile robot to measure the temperature of the equipment in the use scenario, and to detect temperature anomalies in a timely manner to monitor the operating status of the equipment. However, since the infrared thermal imaging measurement results are greatly affected by the measurement distance, the actual measurement results will be unreliable.

[0003] Therefore, how to improve the temperature measurement accuracy of infrared temperature measurement has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The present application provides an infrared temperature measurement method, device, equipment and storage medium based on laser ranging, aiming to improve the temperature measurement accuracy of infrared temperature measurement.

[0005] In a first aspect, the present application provides an infrared temperature measurement method based on laser ranging, and the infrared temperature measurement method based on laser ranging comprises the following steps:

[0006] Based on the visible light image acquisition component, a visible light image of the target scene is acquired to identify the target object in the target scene;

[0007] Based on the laser ranging component, the distance of the target object is measured to obtain the distance information corresponding to the target object;

[0008] Based on the infrared temperature measurement component, the infrared temperature measurement image of the target scene is collected;

[0009] Based on an image fusion algorithm, the visible light image, the infrared temperature measurement image and the distance information corresponding to the target object are fused to obtain the temperature measurement data corresponding to the target object.

[0010] In a second aspect, the present application also provides an infrared temperature measurement system, the system comprising:

[0011] Infrared temperature measurement component, used to collect visible light images and infrared temperature measurement images of the target object, and perform laser ranging on the target object;

[0012] A pan / tilt platform, used for carrying the infrared temperature measurement component and adjusting the measurement direction and angle of the infrared temperature measurement component;

[0013] The processor is used for data processing and analysis of the visible light image, the infrared temperature measurement image and the laser ranging result.

[0014] In a third aspect, the present application also provides a computer device, comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of the infrared temperature measurement method based on laser ranging as described above are implemented.

[0015] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, the steps of the infrared temperature measurement method based on laser ranging as described above are implemented.

[0016] The present application provides an infrared temperature measurement method, device, computer equipment and storage medium based on laser ranging. The method of the present application includes collecting a visible light image of a target scene based on a visible light image acquisition component to identify a target object in the target scene; measuring the distance of the target object based on a laser ranging component to obtain distance information corresponding to the target object; collecting an infrared temperature measurement image of the target scene based on an infrared temperature measurement component; and fusing the visible light image, the infrared temperature measurement image and the distance information corresponding to the target object based on an image fusion algorithm to obtain temperature measurement data corresponding to the target object. Through the above-mentioned method, the present application can obtain the clear outline and detail information of the target object in the target scene through the visible light image acquisition component, so as to facilitate the accurate identification and positioning of the target object; the precise distance information of the target object is acquired through the laser ranging component, and the infrared temperature measurement image of the target scene is acquired through the infrared temperature measurement component, thereby providing the temperature distribution information of the target scene; through the image fusion algorithm, the visible light image, the infrared temperature measurement image and the distance information of the target object are fused, and the distance information of the target object is further fused in the fused image of the visible light image and the infrared temperature measurement image, thereby realizing the calibration of the infrared temperature measurement image, eliminating the influence of distance change on temperature measurement, and making the temperature measurement data more accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0018] Figure 1 A schematic diagram of the structure of an infrared temperature measurement system provided in this application;

[0019] Figure 2 Schematic diagram of the temperature measurement process of the infrared temperature measurement system provided for this application;

[0020] Figure 3A schematic diagram of a flow chart of a first embodiment of an infrared temperature measurement method based on laser ranging provided in the present application;

[0021] Figure 4 A schematic diagram of a visible light image provided in an embodiment of the present application;

[0022] Figure 5 A schematic diagram of a fused image of a visible light image and an infrared temperature measurement image provided in an embodiment of the present application;

[0023] Figure 6 A schematic diagram of an infrared temperature measurement process based on laser ranging provided in an embodiment of the present application;

[0024] Figure 7 A schematic flow chart of a second embodiment of an infrared temperature measurement method based on laser ranging provided in the present application;

[0025] Figure 8 A schematic diagram for comparing multiple sets of temperature measurement data of a target object at different positions and in different states provided in an embodiment of the present application;

[0026] Fig. 9 A schematic diagram of the analysis and feedback process of the temperature measurement data by the impact factor data model provided in the embodiment of the present application;

[0027] Fig.10 It is a structural schematic diagram of a first embodiment of an infrared temperature measuring device based on laser ranging provided by the present application;

[0028] Fig.11 It is a schematic block diagram of the structure of a computer device provided in an embodiment of the present application.

[0029] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0031] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0032] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0033] Please refer to Figure 1 , Figure 1 A schematic diagram of the structure of an infrared temperature measurement system provided in this application.

[0034] like Figure 1 As shown, the infrared temperature measurement system includes an infrared temperature measurement component 101, a pan / tilt platform 102 and a processor 103.

[0035] Among them, the infrared temperature measurement component 101 is used to collect visible light images and infrared temperature measurement images of the target object, and to perform laser ranging on the target object; the gimbal 102 is used to carry the infrared temperature measurement component, and to adjust the measurement direction and measurement angle of the infrared temperature measurement component; the processor 103 is used to process and analyze the data of the visible light image, the infrared temperature measurement image and the laser ranging result.

[0036] In one embodiment, the gimbal 102 may be a mobile gimbal, and the user may move the gimbal 102. For example, the gimbal 102 may be mounted on a mobile vehicle (such as a car, a mobile robot, etc.), and the user may drive the mobile vehicle to move the gimbal 102. The gimbal 102 may also be fixedly installed at a certain location to ensure that the gimbal does not shake or fall over.

[0037] In one embodiment, continue to refer to Figure 1 The infrared temperature measurement component 101 includes a visible light image sensor 1011 , an infrared temperature measurement sensor 1012 and a laser ranging module 1013 .

[0038] Among them, the visible light image sensor 1011 is used to collect the visible light image of the target object. The visible light image sensor 1011 with different device parameters can be configured according to the application scenario requirements. For example, in the scenario where high-definition images are required, such as surface defects such as cracks and scratches on the surface of parts, a high-resolution visible light image sensor can be used; in the scenario where low-resolution images are required, such as traffic flow analysis, monitoring, etc., a low-resolution visible light image sensor can be used.

[0039] The infrared temperature measurement sensor 1012 is used to collect the infrared temperature measurement image of the target object; the infrared temperature measurement sensor can detect the infrared radiation emitted by the target object, thereby realizing non-contact temperature measurement.

[0040] The laser ranging module 1013 is used to collect the distance information of the target object. The laser ranging module calculates the distance to the target object by emitting laser pulses and measuring the time it takes for them to reflect back. Laser ranging technology can provide high-precision distance measurement and is suitable for occasions where accurate distance information is required.

[0041] In one embodiment, the sensor planes of the visible light image sensor 1011, the infrared temperature measurement sensor 1012 and the laser ranging module 1013 need to be on the same plane to ensure that the image acquisition distance of the visible light image and the infrared temperature measurement image is equal to the laser measurement distance, thereby improving the measurement accuracy.

[0042] In one embodiment, the visible light image sensor 1011 and the infrared temperature sensor 1012 may use the same sensor size and resolution, and may use the same acquisition parameters (including focal length, resolution, etc.) to facilitate more accurate image fusion operations.

[0043] In one embodiment, if Figure 2 As shown, the processor 103 can be communicatively connected with the infrared temperature measurement component 101, and the communication connection method may include but is not limited to wired communication connection (such as USB, network cable, etc.) and wireless communication connection (such as Bluetooth, WiFi, etc.). The infrared temperature measurement component 101 can transmit the collected visible light image, infrared temperature measurement image, and distance information obtained by laser ranging to the processor 103 through the data channel of the communication connection. The processor 103 can process and analyze the visible light image, infrared temperature measurement image, and distance information, and output the infrared temperature measurement result.

[0044] For example, the visible light image and the infrared temperature measurement image are matched and fused in the same proportion, and the distance information is added to the fused image to realize the fusion processing of the visible light image, the infrared temperature measurement image and the distance information to obtain a fused image. The fused image is analyzed and the infrared temperature measurement results of the target object in the fused image are collected. The infrared temperature measurement results of the target position at different positions are analyzed and fed back to optimize the infrared temperature measurement process of the fused image.

[0045] In addition, the processor 103 may be configured with a database or the processor 103 may be connected to an external database for communication. The collected visible light images, infrared temperature measurement images, and distance information collected by the laser ranging module may be stored in the database, and the data results processed and analyzed by the processor 103 may be stored in the database.

[0046] The infrared temperature measurement system provided in this embodiment integrates a visible light image sensor, an infrared temperature measurement sensor and a laser distance measurement module to achieve high-precision, non-contact temperature and distance measurement of the target object. By matching and fusing the visible light image and the infrared temperature measurement image in the same proportion and fusing the distance information, the data analysis result of the fused image is more accurate, the infrared temperature measurement process is optimized, and the measurement accuracy and efficiency are improved.

[0047] Please refer to Figure 3 , Figure 3 A schematic flow chart of a first embodiment of an infrared temperature measurement method based on laser ranging provided in the present application.

[0048] like Figure 3 As shown, the infrared temperature measurement method based on laser ranging includes steps S101 to S104.

[0049] S101, based on the visible light image acquisition component, collect a visible light image of a target scene and identify a target object in the target scene;

[0050] Exemplarily, the visible light image acquisition component may be a camera or other image sensor composed of sensor components such as CCD (Charge Coupled Device), CMOS (Complementary Metal Oxide Semiconductor) image sensor, etc. The visible light image acquisition component may convert light signals into electrical signals, thereby acquiring a visible light image of a target scene.

[0051] In one embodiment, image data preprocessing may be performed on the collected visible light image, including denoising, contrast enhancement, color correction, and the like.

[0052] In one embodiment, a feature extraction method (such as Haar feature, SIFT, HOG, SURF, etc.) can be used to extract feature information in the visible light image, and feature recognition can be performed through a target monitoring and recognition algorithm (such as Haar feature + Adaboost algorithm, Hog feature + Svm algorithm, DPM algorithm, R-CNN series, YOLO, etc.) to identify the target object in the visible light image.

[0053] In one embodiment, the identification of the target object may include the identification of the contour features of the target object, the image coordinates in the visible light image, and the category of the target object.

[0054] S102, measuring the distance of the target object based on the laser ranging component to obtain the distance information corresponding to the target object;

[0055] In one embodiment, the laser ranging component can emit a laser pulse in the direction of the target object. After the laser pulse propagates to the surface of the target object, it will be reflected by the target object, and the receiver of the laser ranging component captures the reflected laser signal. By measuring the time difference from the emission to the reception of the laser pulse, the time required for the laser pulse to travel to and from the target object can be calculated.

[0056] In one embodiment, the speed of light (approximately 299,792,458 m / s) and the measured time difference are used to calculate the distance between the target object and the laser ranging component according to the formula "distance = speed of light × (round-trip time / 2)" to obtain the distance information corresponding to the target object.

[0057] S103, collecting an infrared temperature measurement image of the target scene based on the infrared temperature measurement component;

[0058] In one embodiment, the infrared temperature measurement component is generally composed of a main controller (such as an Arduino microcontroller), an infrared sensor module, a temperature detection module, a display module, etc.

[0059] Specifically, the infrared sensor detects the surface temperature of an object by detecting the size and wavelength distribution of the infrared radiation energy of the object. After the main controller receives the data from the infrared sensor module, it needs to perform interpolation calculations, RGB encoding and other processing, including converting the collected temperature information into digital signals, and performing necessary calibration and compensation to ensure the accuracy of the data. The processed data can be converted into a thermal image and displayed on a display module (such as a TFTLCD screen), so that the user can intuitively see the temperature distribution of the target scene.

[0060] S104: Based on an image fusion algorithm, the visible light image, the infrared temperature measurement image, and the distance information corresponding to the target object are fused to obtain temperature measurement data corresponding to the target object.

[0061] Generally speaking, infrared temperature measurement images and visible light images have different image features. Infrared images provide temperature distribution information of the target, while visible light images provide rich color and texture details. The goal of fusing these two images is to retain the thermal radiation information of the infrared image while enhancing the texture and contour details of the visible light image.

[0062] In one embodiment, the image fusion algorithm of the visible light image and the infrared temperature measurement image can generally adopt deep learning technology, an image fusion algorithm based on thermal radiation information retention, and an infrared and visible light image fusion algorithm based on structural texture decomposition, etc.

[0063] For example, the image fusion algorithm can extract and match the features of the visible light image and the infrared temperature measurement image, identify the feature information (such as texture information, edge information, etc.) corresponding to the same object in the two images, and then locally fuse the infrared temperature measurement image with the visible light image by using a feature weight fusion method, etc. The local fused image is feature matched and spliced ​​with the grayscale image to obtain an overall fused image.

[0064] In the image fusion process, the visible light image and the infrared temperature measurement image need to be matched in the same proportion, and the image fusion algorithm is used to crop and stitch the images, and finally the fused image is output with the same image proportion and size. Figure 4 and Figure 5 As shown, Figure 4 For a single visible light image, Figure 5 It is a fusion image of visible light image and infrared temperature measurement image.

[0065] Specifically, since visible light images and infrared images may have differences in perspective, scale and position, image registration is required to ensure that the two are consistent in spatial position. Image registration can be achieved by fitting an affine transformation curve, that is, the image acquisition device is optically calibrated in advance, and the visible light image and infrared thermal imaging image of the calibration plate are collected at multiple different distance points within the working range. By calculating the corresponding affine transformation matrix and fitting the affine transformation curve using the least squares polynomial curve, the geometric transformation of pixel coordinates is achieved. After image registration, the features of the visible light and infrared images are extracted, including edge, texture and thermal radiation information. The extracted features are fused, and a fusion method based on deep learning can be used, such as the NestFuse model, which uses a spatial attention model and a channel attention model to describe the importance of deep features at each spatial position and channel to achieve multi-scale feature fusion. After feature fusion, image reconstruction is performed to obtain the final fused image. After image fusion, the fused image is cropped and spliced ​​as needed to ensure that the output fused image is in the same image ratio and size.

[0066] Generally, in image acquisition, different measuring distances can also obtain the same proportional picture through scaling, so different infrared temperature measurement results may be obtained for the same picture but different distances.

[0067] In this regard, the embodiment of the present application introduces distance information collected by the laser ranging component in the process of fusing the visible light image and the infrared temperature measurement image.

[0068] Furthermore, based on the distance information corresponding to the target object, the visible light image and the infrared temperature measurement image are matched in the same proportion to obtain a fused image; based on the fusion information of the fused image, the temperature measurement data corresponding to the target object is obtained.

[0069] Specifically, the distance information can be synchronously fused with the visible light image and the infrared temperature measurement image to form a unique fused image. In this output image, each time the object is measured, the result can be output at the same distance, the same viewing angle, and the same image ratio, achieving the effect of correcting the measurement error caused by different distances.

[0070] Specifically, Figure 6 As shown in the figure, after the target in the target scene is initially identified and located by the visible light image, the distance of the target is measured by the laser ranging component to obtain the distance information of the target. With the addition of the distance information, the target image at this time has positional uniqueness. At this time, infrared thermal imaging temperature measurement is performed according to the distance information corresponding to the target, and finally accurate temperature measurement data is output.

[0071] The measurement errors caused by different distances can be corrected by this fusion method. Without the introduction of laser ranging information, the temperature measurement results of the infrared thermal imager may be affected by the change in the distance between the target and the thermal imager. However, the distance information obtained by the laser ranging component can correct these errors, thereby improving the accuracy of temperature measurement. With the assistance of distance information, infrared thermal imaging temperature measurement is performed according to the distance information corresponding to the target, and the output temperature measurement data will be more accurate.

[0072] The present embodiment provides an infrared temperature measurement method based on laser ranging. The present method can obtain clear outlines and detail information of a target object in a target scene through a visible light image acquisition component, so as to accurately identify and locate the target object; the precise distance information of the target object is acquired through the laser ranging component, and the infrared temperature measurement image of the target scene is acquired through the infrared temperature measurement component, thereby providing the temperature distribution information of the target scene; the visible light image, the infrared temperature measurement image and the distance information of the target object are fused through an image fusion algorithm, and the distance information of the target object is further fused in the fused image of the visible light image and the infrared temperature measurement image, thereby realizing the calibration of the infrared temperature measurement image, eliminating the influence of distance changes on temperature measurement, and making the temperature measurement data more accurate and reliable.

[0073] Please refer to Figure 7 , Figure 7 A schematic flow chart of a second embodiment of an infrared temperature measurement method based on laser ranging provided in the present application.

[0074] In this embodiment, Figure 7 As shown, based on the above Figure 3 In the embodiment shown, after S104, the following steps are further included:

[0075] S201, obtaining temperature measurement data of the same target object at different positions in the target scene;

[0076] In one embodiment, the same target object is placed at different positions in the target scene, and then Figure 3 The temperature measurement method of the illustrated embodiment collects temperature measurement data at different positions of the target scene.

[0077] The different positions may be the same distance but different directions, the same direction but different distances, or different directions but different distances.

[0078] For a target object at the same position, temperature measurement data may be collected multiple times, and the average value of the temperature measurement data may be used as the temperature measurement data of the target object at that position.

[0079] S202, based on preset influencing factors, comparing and analyzing the temperature measurement data of the target object at different positions, and constructing an influencing factor mathematical model;

[0080] In one embodiment, the influencing factors include device usage time, device usage status, and the environment in which the device is located.

[0081] The device usage time may be the time from when the device was shipped to the present, or the time from when the device was put into use in the current environment to the present, or the time the device has been running continuously, or the total time the device has been running.

[0082] The equipment usage status may include load conditions, degree of wear, historical faults (including fault type, fault frequency, maintenance information, etc.), operating modes (such as intermittent operation or continuous operation, etc.), and performance indicators (such as efficiency, output power, etc.).

[0083] The environment in which the equipment is located may include ambient temperature, humidity, wind speed and airflow, sunlight and radiation, etc.

[0084] In one embodiment, depending on application requirements and equipment types, the influencing factors may also include other factors, such as material properties of the target object, surface conditions of the target object, etc.

[0085] In one embodiment, after obtaining the temperature measurement data of the target object at different positions and distances, multiple sets of temperature measurement data can be compared. Figure 8 As shown in the figure, assuming that A, B, C, and D are the same target objects installed in different locations, at this time, the temperature measurement data results of the target object in different states (such as usage time, equipment status, surrounding environment, etc.) can be compared based on the data comparison of A, B, C, and D, and the influencing factors that may affect the temperature measurement data results can be analyzed and formulated. This information is further fed back to the entire temperature measurement system, and the data is fed back to the single-point temperature measurement to further improve the confidence of the temperature measurement results. Fig. 9 as shown in .

[0086] Specifically, it is necessary to collect data from targets at four different locations, A, B, C, and D, including visible light images, infrared temperature measurement images, and distance information. These data may contain noise and incomplete information, so data cleaning and preprocessing are required to ensure data quality and integrity.

[0087] In one embodiment, the data is comprehensively analyzed and correlated to find out the main factors affecting the state of the target object. For example, a comparative analysis method can be used to compare the state differences of the target objects at different locations, or a group analysis method can be used to analyze the state of the target objects at different usage times or device states.

[0088] For example, by using the comparative analysis method, the abnormal values, trends and patterns of the data can be found by comparing the state differences of the target objects at different locations. For example, the temperature changes of the target objects at four locations A, B, C, and D in the same time period can be compared to identify which locations may be more affected by environmental factors.

[0089] For example, according to the characteristics and attributes of the data, the group analysis method is used to classify and group the data, and then each group is analyzed. This method can discover the internal structure and rules of the data. For example, the target objects can be grouped according to the usage time or equipment status, and then the status changes of the target objects in each group can be analyzed.

[0090] It is understandable that one or more different analysis methods can be used to analyze multiple sets of temperature measurement data according to the actual model construction requirements. For example, the data can be classified and summarized according to different classification standards and dimensions through structural analysis, thereby revealing the structural characteristics and laws of the data; the internal relationship and correlation of the data can be discovered by analyzing and cross-comparing multiple dimensions of the data, such as analyzing the cross-relationship between the state of the target object and environmental factors (such as temperature and humidity) to identify which environmental factors have the greatest impact on the state of the target object, and so on.

[0091] In one embodiment, appropriate algorithms and models may be selected for training and optimization based on the data analysis results of the temperature measurement data. For example, a linear regression model, a logistic regression model, or a support vector machine model may be used, which can help understand how different influencing factors affect the state of the target object.

[0092] In one embodiment, an influencing factor data model is established based on the influence of the influencing factors on the temperature measurement results of the target object, which is used to predict the temperature measurement data of the target object under different states. The analysis results are fed back to the processor for adjusting and optimizing the temperature measurement strategy. For example, if it is found that the ambient temperature has a significant impact on the temperature measurement results, measures can be taken to control the ambient temperature, or the influence of the ambient temperature can be considered during analysis. Using the comparison results of multiple groups of data, the single-point temperature measurement results are corrected to improve the confidence of the temperature measurement results. For example, if it is found that the temperature measurement data of target A in a specific environment is generally higher than that of other targets, the temperature measurement results of A can be adjusted.

[0093] Furthermore, based on preset influencing factors, the temperature measurement data of the target object at different positions are compared and analyzed to determine the temperature difference correction parameters corresponding to the influencing factors; and based on the temperature difference correction parameters, the influencing factor data model is constructed.

[0094] Specifically, the temperature measurement data of the target at different positions are collected and preprocessed, including geometric correction, radiation calibration, atmospheric correction and image cropping, to ensure the reliability of the data and the comparability of the results. Possible influencing factors are preset, such as environmental conditions, characteristics of the measuring equipment and variability during operation. Single factor analysis is performed on the preset influencing factors, and the temperature changes under different factors are compared to determine the degree of influence of each factor on the temperature measurement.

[0095] Based on the preset influencing factors, the temperature measurement data at different positions are compared and analyzed, and the temperature difference correction parameters corresponding to each influencing factor are calculated. The temperature difference correction coefficient formula is used to determine the temperature difference correction parameters, which will be used to construct the data model.

[0096] In one embodiment, the influencing factors can be quantified. For example, the device usage time can be quantified by the device's running time or the number of startups, etc.; the device usage status can be defined in different states (such as standby, working, fault, etc.), and a quantitative value can be assigned to each state; the environment in which the device is located includes environmental parameters such as temperature, humidity, and light intensity, which need to be monitored and quantified in real time through sensors.

[0097] According to the quantified impact factor and temperature measurement data, an impact factor data model is established. The impact factor data model can be expressed as:

[0098] T=f(Tuse,Sstatus,Eenv)

[0099] Among them, T is the temperature measurement data of the target object, Tuse is the influence of the equipment usage time, Sstatus is the influence of the equipment usage status, and Eenv is the influence of the environment in which the equipment is located.

[0100] Exemplarily, an influencing factor data model is constructed according to the determined temperature difference correction parameters. The model can adopt a star model, a snowflake model or a constellation model, and the most appropriate data organization type is selected according to the actual situation. Optionally, during the model construction process, different modeling methodologies such as a paradigm model or a Data Vault model can be used to achieve data integration and decision analysis.

[0101] In one embodiment, historical data can be used to estimate the parameters in the model, which can be achieved by statistical methods such as the least square method. The influencing factor mathematical model is trained until the model can accurately predict or simulate temperature measurement data under different conditions.

[0102] In one embodiment, the constructed influencing factor data model is verified, and the accuracy of the model is determined by comparison with known standard temperature values. Based on the verification results, the model is optimized and adjusted, which may include fine-tuning of parameters or improvement of model structure to improve the prediction accuracy of the model.

[0103] S203: Based on the influencing factor mathematical model, feedback correction is performed on the temperature measurement data of the target object so that the temperature measurement data adapts to the state change of the target object.

[0104] In one embodiment, the temperature measurement results are corrected according to the influencing factor data model during the actual infrared temperature measurement application process. The analysis results are fed back to the single-point temperature measurement system to adjust and optimize the temperature measurement parameters. For example, if it is found that the temperature measurement error of the target object at a certain location is caused by the high ambient temperature, the calibration parameters of the infrared temperature measurement system at that location can be adjusted to reduce the error.

[0105] For example, according to the analysis results, if it is found that the target object at a certain location has a temperature measurement error due to a high ambient temperature, the calibration parameters of the temperature measurement system at that location can be adjusted to reduce the error. For example, if the ambient temperature is higher than the temperature of the object being measured, a larger error will be caused, while when the ambient temperature is lower than the temperature of the object being measured, a higher measurement accuracy will be guaranteed. Therefore, the calibration parameters of the temperature measurement system can be adjusted based on these data to adapt to different environmental conditions.

[0106] In one embodiment, a continuous monitoring system is established to collect data in real time and update the model to adapt to changes in the state of the target object, which can ensure that the temperature measurement system always maintains a high degree of confidence and accuracy.

[0107] In one embodiment, the analysis results and the effects of the feedback mechanism can be visualized so that operators can intuitively understand data changes and system performance. At the same time, reports are generated regularly to summarize system performance and provide improvement suggestions.

[0108] This embodiment analyzes the influence of the influencing factors on the temperature difference of multiple sets of temperature measurement data at different positions of the target object, constructs an influencing factor mathematical model, analyzes and corrects the infrared temperature measurement results through the influencing factor mathematical model, and feeds it back to the single-point infrared temperature measurement system to correct the single-point temperature measurement data, thereby improving the confidence of the temperature measurement results. This method not only improves the accuracy of temperature measurement, but also enhances the adaptability and robustness of the system.

[0109] See also Fig.10 , Fig.10It is a structural schematic diagram of a first embodiment of an infrared temperature measuring device based on laser ranging provided in the present application. The infrared temperature measuring device based on laser ranging is used to execute the aforementioned infrared temperature measuring method based on laser ranging.

[0110] like Fig.10 As shown, the infrared temperature measurement device 300 based on laser ranging includes: a visible light image acquisition module 301, a laser ranging module 302, an infrared temperature measurement image acquisition module 303 and an image fusion module 304.

[0111] The visible light image acquisition module 301 is used to acquire a visible light image of a target scene based on a visible light image acquisition component, and identify a target object in the target scene;

[0112] The laser distance measurement module 302 is used to measure the distance of the target object based on the laser distance measurement component to obtain the distance information corresponding to the target object;

[0113] The infrared temperature measurement image acquisition module 303 is used to acquire the infrared temperature measurement image of the target scene based on the infrared temperature measurement component;

[0114] The image fusion module 304 is used to fuse the visible light image, the infrared temperature measurement image and the distance information corresponding to the target object based on an image fusion algorithm to obtain the temperature measurement data corresponding to the target object.

[0115] It should be noted that technicians in the relevant field can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described device and each module can refer to the corresponding process in the aforementioned infrared temperature measurement method embodiment based on laser ranging, and will not be repeated here.

[0116] The apparatus provided in the above embodiment may be implemented in the form of a computer program. The computer program may be Fig.11 Runs on the computer device shown.

[0117] See also Fig.11 , Fig.11 1 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device may be a server.

[0118] See also Fig.11 The computer device includes a processor, a memory and a network interface connected through a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0119] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any infrared temperature measurement method based on laser ranging.

[0120] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0121] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any infrared temperature measurement method based on laser ranging.

[0122] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0123] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0124] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0125] Based on the visible light image acquisition component, a visible light image of the target scene is acquired to identify the target object in the target scene;

[0126] Based on the laser ranging component, the distance of the target object is measured to obtain the distance information corresponding to the target object;

[0127] Based on the infrared temperature measurement component, the infrared temperature measurement image of the target scene is collected;

[0128] Based on an image fusion algorithm, the visible light image, the infrared temperature measurement image and the distance information corresponding to the target object are fused to obtain the temperature measurement data corresponding to the target object.

[0129] A computer-readable storage medium is also provided in an embodiment of the present application, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and the processor executes the program instructions to implement any infrared temperature measurement method based on laser ranging provided in the embodiment of the present application.

[0130] The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc., equipped on the computer device.

[0131] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. An infrared temperature measurement method based on laser ranging, characterized in that: The method comprises: Based on the visible light image acquisition component, a visible light image of the target scene is acquired to identify the target object in the target scene; Based on the laser ranging component, the distance of the target object is measured to obtain the distance information corresponding to the target object; Based on the infrared temperature measurement component, the infrared temperature measurement image of the target scene is collected; Based on an image fusion algorithm, the visible light image, the infrared temperature measurement image and the distance information corresponding to the target object are fused to obtain the temperature measurement data corresponding to the target object.

2. The infrared temperature measurement method based on laser ranging according to claim 1 is characterized in that: After fusing the visible light image, the infrared temperature measurement image and the distance information corresponding to the target object based on the image fusion algorithm to obtain the temperature measurement data corresponding to the target object, the method further includes: Acquire temperature measurement data of the same target object at different positions in the target scene; Based on the preset influencing factors, the temperature measurement data of the target object at different positions are compared and analyzed to construct an influencing factor mathematical model; Based on the influencing factor mathematical model, feedback correction is performed on the temperature measurement data of the target object so that the temperature measurement data adapts to the state change of the target object.

3. The infrared temperature measurement method based on laser ranging according to claim 2 is characterized in that: The temperature measurement data of the target object at different positions are compared and analyzed based on the preset influencing factors to construct an influencing factor mathematical model, including: Based on the preset influencing factors, comparative analysis is performed on the temperature measurement data of the target object at different positions to determine the temperature difference correction parameters corresponding to the influencing factors; Based on the temperature difference correction parameter, the influencing factor data model is constructed.

4. The infrared temperature measurement method based on laser ranging according to claim 2 is characterized in that: The impact factor data model is expressed as: T=f(Tuse,Sstatus,Eenv) Among them, T is the temperature measurement data of the target object, Tuse is the influence of the equipment usage time, Sstatus is the influence of the equipment usage status, and Eenv is the influence of the environment in which the equipment is located.

5. The infrared temperature measurement method based on laser ranging according to claim 2 is characterized in that: The influencing factors include device usage time, device usage status, and the environment in which the device is located.

6. The infrared temperature measurement method based on laser ranging according to claim 1 is characterized in that: The method of fusing the visible light image, the infrared temperature measurement image and the distance information corresponding to the target object based on the image fusion algorithm to obtain the temperature measurement data corresponding to the target object includes: Based on the distance information corresponding to the target object, the visible light image and the infrared temperature measurement image are matched in the same proportion to obtain a fused image; Based on the fusion information of the fused image, the temperature measurement data corresponding to the target object is obtained.

7. An infrared temperature measurement system, characterized in that: The system comprises: Infrared temperature measurement component, used to collect visible light images and infrared temperature measurement images of the target object, and perform laser ranging on the target object; A pan / tilt platform, used for carrying the infrared temperature measurement component and adjusting the measurement direction and angle of the infrared temperature measurement component; The processor is used for data processing and analysis of the visible light image, the infrared temperature measurement image and the laser ranging result.

8. The infrared temperature measurement system according to claim 7, characterized in that: The infrared temperature measurement component comprises: A visible light image sensor, used for collecting a visible light image of the target object; An infrared temperature measurement sensor, used for collecting an infrared temperature measurement image of the target object; The laser ranging module is used to collect the distance information of the target object.

9. A computer device, characterized in that: The computer device includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of the infrared temperature measurement method based on laser ranging as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the infrared temperature measurement method based on laser ranging as described in any one of claims 1 to 6 are implemented.

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