High-temperature melt temperature monitoring method and device, storage medium and system

Abstract

The invention discloses a high-temperature melt temperature monitoring method and device, a storage medium and a system, relates to the technical field of smelting process control, and mainly aims at solving the problems that existing melt temperature monitoring is low in accuracy, contact type temperature measurement is delayed, and a sensor is prone to corrosion. The method mainly comprises the following steps: acquiring a target monitoring image of a to-be-monitored high-temperature melt acquired by visible light image acquisition equipment; taking a to-be-monitored high-temperature melt as an identification object, and performing target identification on the target monitoring image to obtain a high-temperature melt area image; converting the pixel value of each pixel in the high-temperature melt region image into monochromatic radiation intensity based on a predetermined black body calibration coefficient; and according to the monochromatic radiation intensity, algorithm optimization is carried out on the basis of a two-color temperature measurement principle and on the basis of field conditions, so that temperature distribution data of the high-temperature melt region are calculated. The device is mainly used for monitoring the temperature of high-temperature melt.

Description

Technical Field

[0001] The present invention relates to the technical field of smelting process control, and in particular to a high-temperature melt temperature monitoring method and device, a storage medium, and a system. Background Art

[0002] In the copper smelting process, the temperature of high-temperature melts (such as matte) is a core parameter that determines smelting efficiency and product quality. As a key intermediate product in copper pyrometallurgy, the temperature of matte directly affects slag separation, sulfur oxidation, and the stability of subsequent blowing processes. Improper temperature control can lead to increased copper content in the slag, increased energy consumption, or a decrease in the grade of crude copper. For example, when the temperature of matte is too low, the increased viscosity affects fluidity, resulting in insufficient component stratification; excessively high temperatures can cause equipment corrosion or safety hazards. Therefore, real-time and accurate monitoring of high-temperature melt temperature is of great significance for optimizing the smelting process, reducing energy consumption, and improving product consistency.

[0003] The current mainstream high-temperature melt temperature measurement technologies mainly include thermocouple contact temperature measurement and infrared thermal imaging non-contact temperature measurement, but both have significant drawbacks. Thermocouple technology requires direct insertion into the melt, resulting in a delayed response due to thermal inertia and an inability to capture temperature fluctuations in real time (such as transient changes during melt stirring or feeding). Long-term high-temperature exposure can easily induce oxidation and sulfidation corrosion, leading to temperature measurement deviations and even equipment damage, high maintenance costs, and safety hazards. Although infrared thermal imaging technology avoids direct contact, problems such as radiation reflection from the melt surface, interference from dust and smoke, and complex equipment calibration lead to insufficient temperature resolution accuracy. Its high cost and difficulty in band optimization also limit its universal applicability in industrial scenarios. In summary, due to its complex structure, susceptibility to environmental interference, or reliance on manual operation, existing technologies are difficult to achieve high-precision, real-time, and stable temperature monitoring in the high-temperature and highly corrosive environment of matte smelting, resulting in low temperature monitoring accuracy of high-temperature melts. Summary of the Invention

[0004] In view of this, the present invention provides a high-temperature melt temperature monitoring method and device, storage medium, and system, the main purpose of which is to solve the problem of low accuracy in existing high-temperature melt temperature monitoring.

[0005] According to one aspect of the present invention, a method for monitoring high-temperature melt temperature is provided, comprising: Acquiring a target monitoring image of the high-temperature melt to be monitored acquired by a visible light image acquisition device; Taking the high-temperature melt to be monitored as the identification object, performing target recognition on the target monitoring image to obtain a high-temperature melt area image; Converting the pixel value of each pixel in the high-temperature melt region image into a monochromatic radiation intensity based on a predetermined blackbody calibration coefficient; According to the monochromatic radiation intensity, the temperature distribution data of the high-temperature melt area is obtained based on the two-color temperature measurement principle.

[0006] Furthermore, the high-temperature melt to be monitored is used as the identification object, target recognition is performed on the target monitoring image to obtain the high-temperature melt area image, including: performing noise reduction processing on the target monitoring image, cropping a local image containing the high-temperature melt from the noise-reduced target monitoring image, and performing image smoothing processing on the local image to obtain a preprocessed target monitoring image; Based on the pixel grayscale difference of the preprocessed target monitoring image, the high-temperature melt area and the background area are segmented using a threshold segmentation algorithm. The melt contour is extracted from the image of the high-temperature melt area using an edge detection algorithm. The segmented areas are connected using a region generation algorithm to obtain a high-temperature melt segmentation image: Target recognition is performed on the high-temperature melt segmentation image to obtain a high-temperature melt region image.

[0007] Furthermore, the performing target recognition on the high-temperature melt segmentation image to obtain a high-temperature melt region image includes: Extracting a high-temperature melt region image that matches the high-temperature melt feature by performing geometric feature extraction and melt feature matching on the high-temperature melt segmentation image and performing target recognition using a deep learning model; Performing feature extraction on the high-temperature melt region image to obtain pixel values of each pixel, including channel values of red light and green light; Furthermore, the monochromatic radiation intensity includes red light radiation intensity and green light radiation intensity, the blackbody calibration coefficient includes a red light band blackbody calibration coefficient and a green light band blackbody calibration coefficient, and the pixel value of each pixel in the high-temperature melt area image is converted into monochromatic radiation intensity based on the blackbody calibration coefficient, including: Constructing a red light channel calibration equation based on the blackbody calibration coefficient of the red light band, and constructing a green light channel calibration equation based on the blackbody calibration coefficient of the green light band; For each pixel of the high-temperature melt area image, extracting a red light pixel value and a green light pixel value respectively; Substitute the ratio of the red light pixel value to the exposure time into the red light channel calibration equation to obtain the red light radiation intensity within the central wavelength of the red light channel. Substitute the ratio of the green light pixel value to the exposure time into the green light channel calibration equation to obtain the green light radiation intensity within the central wavelength of the green light channel. The central wavelength of the red light channel and the central wavelength of the green light channel are central wavelength parameters of the corresponding channels of the visible light image acquisition device.

[0008] Furthermore, before converting the pixel value of each pixel in the high-temperature melt region image into a monochromatic radiation intensity based on the blackbody calibration coefficient, the method further includes: Acquire images of the interior of a blackbody furnace acquired by the visible light image acquisition device at different blackbody furnace temperatures and exposure times of the images of the interior of the blackbody furnace; For each blackbody furnace image, calculating the average red light channel and the average green light channel of the central area of the image, wherein the central area of the image is used to represent the area where the blackbody radiation light source is located; According to the red light channel average value, the green light channel average value and the exposure time, the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures are calculated using Planck's law; Polynomial fitting correction is performed on the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures, and the fitting correction curves are solved to obtain the blackbody calibration coefficients corresponding to the red light band and the green light band, respectively.

[0009] Furthermore, the temperature distribution data of the high-temperature melt region is obtained based on the monochromatic radiation intensity and the two-color temperature measurement principle, including: For each pixel, the temperature value of the pixel is calculated using a dual-color temperature measurement formula based on the monochromatic radiation intensity, the central wavelength of the red light channel and the central wavelength of the green light channel of the visible light image acquisition device, and the red light band emissivity and the green light band emissivity of the high-temperature melt; Obtaining temperature distribution data of the high-temperature melt region based on the temperature value of each pixel; The dual-color temperature measurement formula is expressed as: ;in, Indicates temperature value, represents the second radiation constant, represents the central wavelength of the red channel, represents the central wavelength of the green channel, Represents the red light radiation intensity at the central wavelength of the red light channel, Represents the green light radiation intensity at the central wavelength of the green light channel, represents the red light band emissivity of the high temperature melt, Represents the green light band emissivity of high-temperature melt.

[0010] Furthermore, after obtaining the temperature distribution data of the high-temperature melt region based on the two-color temperature measurement principle according to the monochromatic radiation intensity, the method further includes: Temperature display data is generated based on the temperature distribution data, and the temperature display data is sent to a display terminal to display the temperature state and distribution of the high-temperature melt to be monitored, wherein the temperature display data includes at least one of a two-dimensional temperature field map and a temperature distribution curve.

[0011] According to another aspect of the present invention, a high-temperature melt temperature monitoring device is provided, comprising: an acquisition module, configured to acquire a target monitoring image acquired by a visible light image acquisition device, wherein the visible light image acquisition device is deployed at a preset position above a melt channel through which the high-temperature melt to be monitored flows; An image processing module is used to locate the pixel coverage area of the high-temperature melt in the target monitoring image through target recognition to obtain a high-temperature melt area image; a conversion module, configured to convert the pixel value of each pixel in the high-temperature melt region image into a monochromatic radiation intensity within a band parameter range based on a predetermined blackbody calibration coefficient; A generation module is used to obtain temperature distribution data of the high-temperature melt area based on the two-color temperature measurement principle according to the monochromatic radiation intensity.

[0012] Furthermore, the image processing module includes: a preprocessing unit, configured to perform noise reduction processing on the target monitoring image, crop a local image containing the high-temperature melt from the noise-reduced target monitoring image, and perform image smoothing processing on the local image to obtain a preprocessed target monitoring image; An image segmentation unit is configured to segment the high-temperature melt region and the background region using a threshold segmentation algorithm based on the pixel grayscale difference of the preprocessed target monitoring image, extract the melt contour from the image of the high-temperature melt region using an edge detection algorithm, and connect the segmented regions using a region generation algorithm to obtain a high-temperature melt segmentation image: The target recognition unit is used to perform target recognition on the high-temperature melt segmentation image to obtain a high-temperature melt region image.

[0013] Furthermore, in a specific application scenario, the target recognition unit is specifically used to extract a high-temperature melt area image that matches the high-temperature melt features by performing geometric feature extraction and melt feature matching on the high-temperature melt segmentation image, and to perform target recognition using a deep learning model; and to extract pixel values from the high-temperature melt area image to obtain pixel values of each pixel, including channel values of red light and green light.

[0014] Furthermore, the conversion module includes: A construction unit, configured to construct a red light channel calibration equation based on the blackbody calibration coefficient of the red light band, and to construct a green light channel calibration equation based on the blackbody calibration coefficient of the green light band; an extraction unit, configured to extract a red pixel value and a green pixel value for each pixel of the high-temperature melt region image; A solving unit is used to substitute the ratio of the red light pixel value to the exposure time into the red light channel calibration equation to obtain the red light radiation intensity within the center wavelength of the red light channel, and substitute the ratio of the green light pixel value to the exposure time into the green light channel calibration equation to obtain the green light radiation intensity within the center wavelength of the green light channel; The central wavelength of the red light channel and the central wavelength of the green light channel are central wavelength parameters of the corresponding channels of the visible light image acquisition device.

[0015] Furthermore, the device further comprises: The acquisition module is used to acquire the blackbody furnace interior images acquired by the visible light image acquisition device at different blackbody furnace temperatures and the exposure time of the blackbody furnace interior images; A first calculation module is configured to calculate, for each blackbody furnace image, a red light channel average value and a green light channel average value of a central area of the image, wherein the central area of the image is used to represent an area where a blackbody radiation source is located; a second calculation module, configured to calculate, based on the red light channel average value, the green light channel average value, and the exposure time, the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures using Planck's law; The fitting module is used to perform polynomial fitting correction on the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures, and solve the fitting correction curve to obtain the blackbody calibration coefficients corresponding to the red light band and the green light band respectively.

[0016] Furthermore, the generation module includes: a first calculation unit, configured to calculate, for each pixel, a temperature value of the pixel using a dual-color temperature measurement formula based on the monochromatic radiation intensity, the central wavelength of the red light channel and the central wavelength of the green light channel of the visible light image acquisition device, and the red light band emissivity and the green light band emissivity of the high-temperature melt; A second calculation unit is used to obtain temperature distribution data of the high-temperature melt area according to the temperature value of each pixel; The dual-color temperature measurement formula is expressed as: ;in, Indicates temperature value, represents the second radiation constant, represents the central wavelength of the red channel, represents the central wavelength of the green channel, Represents the red light radiation intensity at the central wavelength of the red light channel, Represents the green light radiation intensity at the central wavelength of the green light channel, represents the red light band emissivity of the high temperature melt, Represents the green light band emissivity of high-temperature melt.

[0017] Furthermore, the device further comprises: A display module is used to generate temperature display data based on the temperature distribution data, and send the temperature display data to a display terminal to display the temperature state and distribution of the high-temperature melt to be monitored, wherein the temperature display data includes at least one of a two-dimensional temperature field diagram and a temperature distribution curve.

[0018] According to another aspect of the present invention, a storage medium is provided, wherein the storage medium stores at least one executable instruction, and the executable instruction enables a processor to execute operations corresponding to the above-mentioned high-temperature melt temperature monitoring method.

[0019] According to another aspect of the present invention, a system is provided, comprising: a visible light image acquisition device, a cooling device, an industrial computer, and a communication bus, wherein the visible light image acquisition device and the industrial computer communicate with each other via the communication bus; The visible light image acquisition device is used to acquire a target monitoring image of the high-temperature melt to be monitored; The cooling device is used to protect the visible light image acquisition device and cool the visible light image acquisition device; The industrial computer is used to store at least one executable instruction and execute the operations corresponding to the above-mentioned high-temperature melt temperature monitoring method through the executable instruction.

[0020] By means of the above technical solution, the technical solution provided by the embodiment of the present invention has at least the following advantages: The present invention provides a high-temperature melt temperature monitoring method and device, storage medium, and system. The embodiments of the present invention obtain a target monitoring image of the high-temperature melt to be monitored acquired by a visible light image acquisition device; use the high-temperature melt to be monitored as the identification object, perform target recognition on the target monitoring image, and obtain a high-temperature melt area image; convert the pixel value of each pixel in the high-temperature melt area image into a monochromatic radiation intensity based on a predetermined blackbody calibration coefficient; and obtain temperature distribution data of the high-temperature melt area based on the principle of two-color temperature measurement according to the monochromatic radiation intensity. Acquiring the target monitoring image through the visible light image acquisition device does not require direct contact with the high-temperature melt, thus avoiding safety risks such as equipment damage and personnel burns caused by direct contact, and is particularly suitable for temperature monitoring in high-temperature and dangerous environments. At the same time, the temperature distribution data of the high-temperature melt area obtained based on the principle of two-color temperature measurement can intuitively display the temperature conditions of different positions of the high-temperature melt, thereby improving the accuracy of temperature monitoring.

[0021] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings: Figure 1 A flow chart of a high-temperature melt temperature monitoring method provided by an embodiment of the present invention is shown; Figure 2 A schematic diagram showing the installation relationship between a camera and a cooling device provided by an embodiment of the present invention is shown; Figure 3 A flow chart of another high-temperature melt temperature monitoring method provided by an embodiment of the present invention is shown; Figure 4 The following is a block diagram showing the composition of a high-temperature melt temperature monitoring device provided by an embodiment of the present invention; Figure 5 A schematic structural diagram of a system provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0023] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0024] Aiming at the problem of low accuracy of existing high-temperature melt temperature monitoring, the embodiment of the present invention provides a high-temperature melt temperature monitoring method, such as Figure 1 As shown, the method includes: 101. Acquire a target monitoring image of the high-temperature melt to be monitored by a visible light image acquisition device.

[0025] In an embodiment of the present invention, to achieve non-contact, real-time temperature monitoring of a high-temperature melt, an image of the melt is captured by a visible light image acquisition device, i.e., the target monitoring image. The visible light image acquisition device can be a color CCD or CMOS industrial camera, and is not specifically limited in this embodiment. To ensure the quality of the captured image, thorough environmental research and planning of the visible light image acquisition device's selection, installation location, and shooting angle are required based on the environment of the high-temperature melt to be monitored. For example, if the high-temperature melt to be monitored is matte from a copper smelting process, the environmental research requires a thorough examination of the ambient temperature fluctuation range, the optimal shooting angle, and possible interference factors such as smoke and dust within the viewing area. Analyze the ambient temperature fluctuation range: Continuously monitor the on-site environment to obtain high and low ambient temperature thresholds over a period of time to determine the ambient temperature fluctuation range. Based on the estimated temperature range of the high-temperature melt and the operating temperature range of the temperature measurement device, ensure that the ambient temperature at the deployment location does not exceed the tolerance range of the temperature measurement device to prevent excessively high ambient temperatures from affecting normal operation and measurement accuracy. Assess the impact of interference factors: A detailed assessment of possible interference factors such as smoke and dust within the viewing area is conducted. Smoke and dust absorb and scatter thermal radiation, causing measurement errors. Observe the main sources and drift directions of the smoke and dust, and analyze the extent to which these interference factors affect the temperature measurement device's field of view at the current shooting angle.

[0026] The selection of visible light image acquisition equipment requires comprehensive consideration of factors such as temperature measurement accuracy, environmental adaptability, and durability. On the one hand, it is necessary to select lenses with high-temperature coatings, which can effectively reduce the impact of high temperatures on the optical performance of the lens and prevent lens deformation, film peeling, and other problems. On the other hand, it is necessary to consider whether the equipment can work stably in a high-temperature environment. In the embodiment of the present invention, in order to ensure the stable operation of the camera, the visible light image acquisition equipment is equipped with the following Figure 2 The cooling device shown in the figure is made of high temperature resistant materials and design. It can cool the camera by water cooling or air cooling to ensure that the image quality is not affected at high temperatures. Taking air cooling as an example, the installation diagram of the camera and cooling device is as follows: Figure 3As shown. Furthermore, in humid or dusty environments, lenses and cameras with good sealing properties are required to prevent moisture and dust from entering, which could affect optical performance and image quality. Regarding camera resolution selection: The higher the resolution, the clearer the details of the object, which facilitates more accurate temperature measurement. The required camera resolution can be calculated based on the required temperature measurement accuracy using the formula: "Camera pixel accuracy = Unidirectional field of view / Camera unidirectional resolution." When selecting the shooting angle, it is important to ensure that the temperature measurement equipment can fully and clearly capture the thermal radiation image of the high-temperature melt. Avoid shooting at too large or too small an angle, which could cause image distortion and affect temperature measurement accuracy. For example, shooting from an angle horizontal to the high-temperature melt and perpendicular to its main direction of motion ensures image integrity while minimizing image distortion.

[0027] After completing the construction of the temperature measurement hardware system, the camera shooting parameters need to be finely configured for the high-temperature melt detection scene to achieve coordinated optimization of image quality and temperature measurement accuracy. The specific implementation process follows the closed-loop process of "feature matching-parameter tuning-dynamic verification": First, determine the parameter optimization direction based on the melt surface temperature gradient, motion characteristics and degree of ambient light interference. For example, for high dynamic range melt scenes, it is necessary to prioritize balancing depth of field and light intensity, use manual aperture control to ensure full clarity of the melt surface, and combine active fill light equipment to compensate for ambient light fluctuations; secondly, through the "white balance-contrast-brightness" three-level linkage adjustment, precise control of image color and grayscale distribution is achieved, and contrast adjustment is combined with the histogram equalization algorithm to avoid melt edge information. The brightness setting uses dynamic threshold monitoring to prevent the overexposed area from exceeding 5%; to address the problem of melt motion blur, based on the principle of matching melt flow rate with camera frame rate, a global shutter and inter-frame interpolation algorithm are used to suppress smear; at the same time, the signal-to-noise ratio is improved through hardware-level semiconductor refrigeration and software-level spatiotemporal domain noise reduction; ultimately, a configuration template containing 12 core parameters (aperture, ISO, shutter, white balance mode, etc.) is formed, and the parameters are solidified after multiple rounds of on-site "melt state-image quality-temperature measurement error" cross-validation to ensure the long-term stability of the temperature measurement system under complex working conditions.

[0028] 102. Taking the high-temperature melt to be monitored as an identification object, target recognition is performed on the target monitoring image to obtain a high-temperature melt area image.

[0029] In an embodiment of the present invention, in order to accurately identify the high-temperature melt area from the target monitoring image, the image needs to be preprocessed, such as denoising, image cropping, etc., to remove the influence of noise and background, improve image quality and the accuracy of subsequent processing. The preprocessing process may also include image smoothing to reduce image noise interference caused by the shooting environment or equipment. After image preprocessing, the high-temperature melt area is accurately segmented from the background through an image segmentation algorithm. This process may include image processing techniques such as threshold segmentation and edge detection to achieve accurate identification of the high-temperature melt area. Based on image segmentation, the target recognition algorithm is further used to accurately identify the specific position and shape of the high-temperature melt. Through target recognition, it can be ensured that the subsequent temperature calculation targets the correct high-temperature melt area, thereby improving the accuracy of temperature measurement.

[0030] 103. Convert the pixel value of each pixel in the high-temperature melt area image into monochromatic radiation intensity based on a predetermined blackbody calibration coefficient.

[0031] In an embodiment of the present invention, to extract temperature distribution data from a visible light image, a pixel-level conversion is performed on the high-temperature melt region image. Specifically, for each pixel in the high-temperature melt region image, the corresponding pixel value is converted into a monochromatic radiation intensity, which includes red and green radiation intensities. To achieve this conversion, a blackbody calibration is performed on the visible light image acquisition device before capturing the image. Based on the data generated during the blackbody calibration process, a blackbody calibration coefficient is derived to establish a conversion relationship between image pixel values and monochromatic radiation intensities. Based on this conversion relationship, the monochromatic radiation intensity represented by the pixel value of each pixel is extracted. By converting pixel values to monochromatic radiation intensities, energy representation is extracted from the visible light image, providing data support for subsequent temperature calculations.

[0032] 104. According to the monochromatic radiation intensity, the temperature distribution data of the high-temperature melt area is obtained based on the two-color temperature measurement principle.

[0033] In this embodiment of the present invention, the principle of two-color temperature measurement is utilized to eliminate the influence of uncertainty in the melt surface emissivity by comparing the ratio of radiation intensities at two wavelengths (without requiring precise pre-measurement of the emissivity). The temperature value of each pixel on the high-temperature melt surface is calculated by combining known radiation constants and wavelength parameters. The calculated temperature data is then mapped to the corresponding position in the melt region image to generate temperature distribution data. This mapping of pixel values to temperatures achieved using the two-color temperature measurement method enables real-time temperature data collection while avoiding the low measurement stability and high equipment costs associated with contact-based temperature acquisition, as well as the timeliness issues associated with thermocouple temperature measurement. This ensures accurate and timely monitoring of high-temperature melt temperature.

[0034] In one embodiment of the present invention, for further illustration and limitation, the method further includes: Acquire images of the interior of a blackbody furnace acquired by the visible light image acquisition device at different blackbody furnace temperatures and exposure times of the images of the interior of the blackbody furnace; For each blackbody furnace image, calculating the average value of the red light channel and the average value of the green light channel in the central area of the image; According to the red light channel average value, the green light channel average value and the exposure time, the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures are calculated using Planck's law; Polynomial fitting correction is performed on the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures, and the fitting correction curves are solved to obtain the blackbody calibration coefficients corresponding to the red light band and the green light band, respectively.

[0035] In this embodiment of the present invention, a standard blackbody furnace is used to calibrate the visible light image acquisition device. For example, using a CCD industrial camera as the visible light image acquisition device, the calibration process requires laboratory-level testing based on the relative spectral response efficiency curves of the selected CCD industrial camera's RGB channels and the established CCD camera parameters, combined with the thermal radiation characteristic curve of the high-temperature melt. The specific calibration experimental steps include: 1) setting the blackbody furnace temperature to a preset temperature, shooting according to the camera parameters, and repeatedly adjusting the exposure time t based on the captured image to determine the optimal exposure time for capturing images inside the blackbody furnace; 2) reading and calculating the average R (red light) and G (green light) values in the center area of the image as the R and G values of the entire flame image, and dividing them by the previously determined exposure time to obtain the R / t and G / t of the flame image; 3) calculating the monochromatic radiation intensities Ir and Ig based on R / t and G / t using Planck's law; 4) resetting the blackbody furnace temperature at a certain temperature interval, and at each set temperature, calculating the R / t, G / t, Ir, and Ig values based on steps 1) to 3) to obtain the red and green radiation intensities at different blackbody furnace temperatures (red and green radiation intensity data sets).

[0036] Polynomial fitting (such as a cubic or quartic polynomial) is performed on the red and green light radiation intensity data sets respectively, with temperature as the independent variable and radiation intensity as the dependent variable. The fitting parameters are optimized using the least squares method to generate a radiation intensity-temperature correction curve. This curve can compensate for system errors such as sensor nonlinear response and lens transmittance fluctuations. Finally, based on the fitted correction curve, the calibration coefficients corresponding to the red and green light bands (such as the coefficients of each order in the polynomial) are extracted. These coefficients will be used in the subsequent conversion calculation of monochromatic radiation intensity and temperature values.

[0037] In one embodiment of the present invention, for further explanation and limitation, as Figure 3As shown, in step 102, the high-temperature melt to be monitored is used as the identification object, and target recognition is performed on the target monitoring image to obtain a high-temperature melt area image, including: 201. Perform noise reduction processing on the target monitoring image, crop a local image containing the high-temperature melt from the noise-reduced target monitoring image, and perform image smoothing processing on the local image to obtain a pre-processed target monitoring image.

[0038] 202. Based on the pixel grayscale difference of the preprocessed target monitoring image, a threshold segmentation algorithm is used to segment the high-temperature melt area and the background area. The melt contour is extracted from the image of the high-temperature melt area through an edge detection algorithm, and the segmented areas are connected through a region generation algorithm to obtain a high-temperature melt segmentation image.

[0039] 203. Perform target recognition on the high-temperature melt segmentation image to obtain a high-temperature melt region image.

[0040] In this embodiment of the present invention, noise is first suppressed on the original target monitoring image using methods such as median filtering (suitable for salt and pepper noise), Gaussian filtering (for Gaussian noise), or frequency-domain Fourier transform filtering (for separating periodic interference). An adaptive algorithm is selected based on the image noise characteristics (the specific method is not limited in this embodiment of the present invention) to enhance the contrast between the melt edge and the background while avoiding loss of detail due to oversmoothing. Based on the spatial distribution characteristics of the high-temperature melt (such as relatively fixed position or distinct morphological features), a preliminary ROI is located using manual annotation or automatic thresholding and cropped to encompass only the melt and its surrounding area. To meet the input requirements of subsequent algorithms, the ROI is scaled and normalized (e.g., to 256×256 pixels). A bilateral filtering algorithm is then used to smooth background noise while preserving grayscale transitions at the melt edge, providing clear boundaries for subsequent segmentation. Adaptive threshold segmentation (such as the Otsu algorithm) is used to separate the melt from the background based on grayscale differences, generating a preliminary binary mask. To address fuzzy edges or holes in the segmentation results, the Canny edge detection algorithm is used to extract the melt contour. Morphological closing operations (filling internal pores) and opening operations (removing edge burrs) are combined to optimize contour integrity. Finally, connected region analysis (such as 8-neighborhood labeling) is used to remove discrete noise points, retaining the largest connected region as the melt region, ensuring that the recognition results closely match the actual melt morphology. Finally, based on image segmentation, target recognition is performed. This ensures that subsequent temperature field calculations target the correct high-temperature melt region, improving temperature measurement accuracy.

[0041] In one embodiment of the present invention, for further explanation and limitation, the step of performing target recognition on the high-temperature melt segmentation image to obtain a high-temperature melt region image includes: Extracting a high-temperature melt region image that matches the high-temperature melt feature by performing geometric feature extraction and melt feature matching on the high-temperature melt segmentation image and performing target recognition using a deep learning model; Pixel value extraction is performed on the high-temperature melt area image to obtain the pixel value of each pixel, including the channel values of red light and green light.

[0042] In an embodiment of the present invention, to accurately locate the high-temperature melt region and construct its image, geometric feature extraction (e.g., calculation of shape parameters such as area, perimeter, and eccentricity) and melt feature matching are performed on the high-temperature melt segmentation image. A deep learning model is then used for target recognition to extract the high-temperature melt region image from the high-temperature melt segmentation image. The deep learning model can be constructed based on a convolutional neural network or a deep residual network, trained with a large amount of high-temperature melt image data, and can accurately locate and identify high-temperature melt targets in the image. Through the coordinated optimization of geometric feature pre-screening and deep learning target recognition, the accuracy and robustness of high-temperature melt recognition are effectively improved, providing reliable target region data for subsequent temperature field calculations.

[0043] In one embodiment of the present invention, for further explanation and limitation, as Figure 3 As shown, step 103 converts the pixel value of each pixel in the high-temperature melt area image into a monochromatic radiation intensity based on the blackbody calibration coefficient, including: 204. Construct a red light channel calibration equation based on the red light band blackbody calibration coefficient, and construct a green light channel calibration equation based on the green light band blackbody calibration coefficient.

[0044] 205. For each pixel of the high-temperature melt region image, extract a red pixel value and a green pixel value respectively.

[0045] 206. Substitute the ratio of the red light pixel value to the exposure time into the red light channel calibration equation to obtain the red light radiation intensity within the center wavelength of the red light channel. Substitute the ratio of the green light pixel value to the exposure time into the green light channel calibration equation to obtain the green light radiation intensity within the center wavelength of the green light channel.

[0046] In the embodiment of the present invention, the monochromatic radiation intensity includes red light radiation intensity and green light radiation intensity. The blackbody calibration coefficient includes a blackbody calibration coefficient for the red light band and a blackbody calibration coefficient for the green light band. The center wavelength of the red light channel and the center wavelength of the green light channel are the center wavelength parameters of the corresponding channels of the visible light image acquisition device. The red light channel calibration equation is expressed as: ; The green channel calibration equation is expressed as: ; Where R is the brightness value of the corresponding image pixel in the red light channel, and G is the brightness value of the corresponding image pixel in the green light channel; is the absolute radiation intensity of red light calculated by Planck's law, is the absolute radiation intensity of red light calculated by Planck's law; t is the exposure time; 、 、 、 、 is the blackbody calibration coefficient in the red light band, 、 、 、 、 is the blackbody calibration coefficient in the green light band.

[0047] In one embodiment of the present invention, for further explanation and limitation, as Figure 4 As shown, step 104 obtains temperature distribution data of the high-temperature melt region based on the monochromatic radiation intensity and the two-color temperature measurement principle, including: 207. For each pixel, the temperature value of the pixel is calculated using a dual-color temperature measurement formula based on the monochromatic radiation intensity, the central wavelength of the red light channel and the central wavelength of the green light channel of the visible light image acquisition device, and the red light band emissivity and the green light band emissivity of the high-temperature melt.

[0048] 208. Obtain temperature distribution data of the high-temperature melt region based on the temperature value of each pixel.

[0049] In the embodiment of the present invention, in order to achieve a refined reconstruction of the temperature field in the high-temperature melt region, multi-parameter coordinated temperature calculation and spatial optimization are performed for each pixel: First, based on the central wavelengths of the red and green light channels calibrated by the visible light image acquisition device, combined with the monochromatic radiation intensity of each pixel and the emissivity of the high-temperature melt in this band, the temperature value is calculated pixel by pixel using the dual-color temperature measurement formula. The dual-color temperature measurement formula is expressed as: ;in, Indicates temperature value, represents the second radiation constant, represents the central wavelength of the red channel, represents the central wavelength of the green channel, Represents the red light radiation intensity at the central wavelength of the red light channel, Represents the green light radiation intensity at the central wavelength of the green light channel, represents the red light band emissivity of the high temperature melt, Represents the green light band emissivity of high-temperature melt.

[0050] After calculating the pixel-by-pixel temperature value, spatially continuous temperature distribution data for the high-temperature melt region is generated. Using the dual-color temperature measurement principle, the radiant brightness is measured at two specific wavelengths, eliminating interfering factors such as emissivity to calculate the temperature value. Based on the device-calibrated mapping relationship between pixel value and temperature, the temperature corresponding to each pixel is calculated, providing high-fidelity data support for melt state monitoring and process control.

[0051] It should be noted that the dual-color temperature measurement formula is dynamically updated, allowing customized optimization of the temperature measurement algorithm used in the field based on site conditions and user experience. By adjusting algorithm parameters and improving algorithm structure, the precision and accuracy of the temperature measurement algorithm can be improved, ensuring that the temperature measurement results are closer to actual values. At the same time, the real-time and stability of the algorithm must also be considered to ensure that the temperature measurement system can continue to operate stably in harsh high-temperature environments. By combining on-site environmental parameters, high-temperature melt characteristics, and user experience, the temperature measurement algorithm is customized and optimized from data acquisition and preprocessing, algorithm adaptation and adjustment, error correction, to field testing iterations to improve accuracy and adaptability.

[0052] In one embodiment of the present invention, for further explanation and limitation, after obtaining the temperature distribution data of the high-temperature melt region based on the two-color temperature measurement principle according to the monochromatic radiation intensity, the method further includes: Temperature display data is generated according to the temperature distribution data, and the temperature display data is sent to a display terminal to display the temperature state and distribution of the high-temperature melt to be monitored.

[0053] In an embodiment of the present invention, the calculated temperature field data (temperature distribution data) is visualized to facilitate users' intuitive understanding of the temperature distribution of the high-temperature melt. This temperature display data includes at least one of a two-dimensional temperature field map and a temperature distribution curve. The two-dimensional temperature field map visually displays the global temperature distribution using pseudo-color or isotherms, enabling on-site operators to quickly locate abnormal areas and monitor overall temperature trends. This temperature field display allows users to understand the temperature status of the high-temperature melt in real time, providing an important reference for temperature control and safety management during the production process.

[0054] The present invention provides a method for monitoring the temperature of a high-temperature melt. In an embodiment of the present invention, a target monitoring image of the high-temperature melt to be monitored is acquired by a visible light image acquisition device; the target monitoring image is subjected to target recognition with the high-temperature melt to be monitored as the identification object to obtain a high-temperature melt area image; the pixel value of each pixel in the high-temperature melt area image is converted into a monochromatic radiation intensity based on a predetermined blackbody calibration coefficient; and the temperature distribution data of the high-temperature melt area is obtained based on the principle of two-color temperature measurement according to the monochromatic radiation intensity. By acquiring the target monitoring image through the visible light image acquisition device, there is no need for direct contact with the high-temperature melt, thus avoiding safety risks such as equipment damage and personnel burns caused by direct contact, and the method is particularly suitable for temperature monitoring in high-temperature and dangerous environments. At the same time, the temperature distribution data of the high-temperature melt area obtained based on the principle of two-color temperature measurement can intuitively display the temperature conditions of different positions of the high-temperature melt and improve the accuracy of temperature monitoring.

[0055] Furthermore, as a response to the above Figure 1 The embodiment of the present invention provides a high temperature melt temperature monitoring device, such as Figure 4 As shown, the device includes: An acquisition module 31 is configured to acquire a target monitoring image acquired by a visible light image acquisition device, wherein the visible light image acquisition device is deployed at a preset position above a melt channel through which the high-temperature melt to be monitored flows; An image processing module 32 is configured to locate the pixel coverage area of the high-temperature melt in the target monitoring image through target recognition to obtain a high-temperature melt area image; A conversion module 33 is configured to convert the pixel value of each pixel in the high-temperature melt region image into a monochromatic radiation intensity within a band parameter range based on a predetermined blackbody calibration coefficient; The generating module 34 is configured to obtain temperature distribution data of the high-temperature melt region based on the monochromatic radiation intensity and the two-color temperature measurement principle.

[0056] Furthermore, the image processing module 32 includes: a preprocessing unit, configured to perform noise reduction processing on the target monitoring image, crop a local image containing the high-temperature melt from the noise-reduced target monitoring image, and perform image smoothing processing on the local image to obtain a preprocessed target monitoring image; An image segmentation unit is configured to segment the high-temperature melt region and the background region using a threshold segmentation algorithm based on the pixel grayscale difference of the preprocessed target monitoring image, extract the melt contour from the image of the high-temperature melt region using an edge detection algorithm, and connect the segmented regions using a region generation algorithm to obtain a high-temperature melt segmentation image: The target recognition unit is used to perform target recognition on the high-temperature melt segmentation image to obtain a high-temperature melt region image.

[0057] Furthermore, in a specific application scenario, the target recognition unit is specifically used to extract a high-temperature melt area image that matches the high-temperature melt features by performing geometric feature extraction and melt feature matching on the high-temperature melt segmentation image, and to perform target recognition using a deep learning model; and to extract pixel values from the high-temperature melt area image to obtain the pixel values of each pixel, including red and green light channels.

[0058] Furthermore, the conversion module 33 includes: A construction unit, configured to construct a red light channel calibration equation based on the blackbody calibration coefficient of the red light band, and to construct a green light channel calibration equation based on the blackbody calibration coefficient of the green light band; an extraction unit, configured to extract a red pixel value and a green pixel value for each pixel of the high-temperature melt region image; A solving unit is used to substitute the ratio of the red light pixel value to the exposure time into the red light channel calibration equation to obtain the red light radiation intensity within the center wavelength of the red light channel, and substitute the ratio of the green light pixel value to the exposure time into the green light channel calibration equation to obtain the green light radiation intensity within the center wavelength of the green light channel; The central wavelength of the red light channel and the central wavelength of the green light channel are central wavelength parameters of the corresponding channels of the visible light image acquisition device.

[0059] Furthermore, the device further comprises: The acquisition module is used to acquire the blackbody furnace interior images acquired by the visible light image acquisition device at different blackbody furnace temperatures and the exposure time of the blackbody furnace interior images; A first calculation module is configured to calculate, for each blackbody furnace image, a red light channel average value and a green light channel average value of a central area of the image, wherein the central area of the image is used to represent an area where a blackbody radiation source is located; a second calculation module, configured to calculate, based on the red light channel average value, the green light channel average value, and the exposure time, the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures using Planck's law; The fitting module is used to perform polynomial fitting correction on the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures, and solve the fitting correction curve to obtain the blackbody calibration coefficients corresponding to the red light band and the green light band respectively.

[0060] Furthermore, the generating module 34 includes: a first calculation unit, configured to calculate, for each pixel, a temperature value of the pixel using a dual-color temperature measurement formula based on the monochromatic radiation intensity, the central wavelength of the red light channel and the central wavelength of the green light channel of the visible light image acquisition device, and the red light band emissivity and the green light band emissivity of the high-temperature melt; A second calculation unit is used to obtain temperature distribution data of the high-temperature melt area according to the temperature value of each pixel; The dual-color temperature measurement formula is expressed as: ;in, Indicates temperature value, represents the second radiation constant, represents the central wavelength of the red channel, represents the central wavelength of the green channel, Represents the red light radiation intensity at the central wavelength of the red light channel, Represents the green light radiation intensity at the central wavelength of the green light channel, represents the red light band emissivity of the high temperature melt, Represents the green light band emissivity of high-temperature melt.

[0061] Furthermore, the device further comprises: A display module is used to generate temperature display data based on the temperature distribution data, and send the temperature display data to a display terminal to display the temperature state and distribution of the high-temperature melt to be monitored, wherein the temperature display data includes at least one of a two-dimensional temperature field diagram and a temperature distribution curve.

[0062] The present invention provides a high-temperature melt temperature monitoring device. The embodiment of the present invention obtains a target monitoring image of the high-temperature melt to be monitored acquired by a visible light image acquisition device; takes the high-temperature melt to be monitored as the identification object, performs target recognition on the target monitoring image, and obtains a high-temperature melt area image; converts the pixel value of each pixel in the high-temperature melt area image into a monochromatic radiation intensity based on a predetermined blackbody calibration coefficient; and obtains the temperature distribution data of the high-temperature melt area based on the two-color temperature measurement principle according to the monochromatic radiation intensity. Acquiring the target monitoring image through the visible light image acquisition device does not require direct contact with the high-temperature melt, thus avoiding safety risks such as equipment damage and personnel burns caused by direct contact, and is particularly suitable for temperature monitoring in high-temperature and dangerous environments. At the same time, the temperature distribution data of the high-temperature melt area obtained based on the two-color temperature measurement principle can intuitively display the temperature conditions of different positions of the high-temperature melt, thereby improving the accuracy of temperature monitoring.

[0063] According to one embodiment of the present invention, a storage medium is provided, wherein the storage medium stores at least one executable instruction. The computer executable instruction can execute the high-temperature melt temperature monitoring method in any of the above method embodiments.

[0064] Figure 5 A schematic structural diagram of a system provided according to an embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the system.

[0065] like Figure 5 As shown, the system may include: According to another aspect of the present invention, a system is provided, including: a visible light image acquisition device 41, a cooling device 42, an industrial computer 43 and a communication bus 44, wherein the visible light image acquisition device and the industrial computer communicate with each other via the communication bus; The visible light image acquisition device 41 is used to acquire a target monitoring image of the high-temperature melt to be monitored; The cooling device 42 is used to protect the visible light image acquisition device and cool the visible light image acquisition device; The industrial computer 43 is used to store at least one executable instruction and execute operations corresponding to the above-mentioned high-temperature melt temperature monitoring method through the executable instruction.

[0066] Obviously, those skilled in the art will appreciate that the various modules or steps of the present invention described above can be implemented using a general-purpose computing device, centralized on a single computing device, or distributed across a network of multiple computing devices. Alternatively, they can be implemented using program code executable by a computing device, which can then be stored in a storage device and executed by the computing device. In some cases, the steps shown or described can be performed in a different order than that shown, or can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0067] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A high-temperature melt temperature monitoring method, characterized in that: include: Acquiring a target monitoring image of the high-temperature melt to be monitored acquired by a visible light image acquisition device; Taking the high-temperature melt to be monitored as the identification object, performing target recognition on the target monitoring image to obtain a high-temperature melt area image; Converting the pixel value of each pixel in the high-temperature melt region image into a monochromatic radiation intensity based on a predetermined blackbody calibration coefficient; According to the monochromatic radiation intensity, the temperature distribution data of the high-temperature melt area is obtained based on the two-color temperature measurement principle.

2. The method according to claim 1, characterized in that The method of taking the high-temperature melt to be monitored as the identification object and performing target identification on the target monitoring image to obtain a high-temperature melt area image includes: performing noise reduction processing on the target monitoring image, cropping a local image containing the high-temperature melt from the noise-reduced target monitoring image, and performing image smoothing processing on the local image to obtain a preprocessed target monitoring image; Based on the pixel grayscale difference of the preprocessed target monitoring image, the high-temperature melt area and the background area are segmented using a threshold segmentation algorithm. The melt contour is extracted from the image of the high-temperature melt area using an edge detection algorithm. The segmented areas are connected using a region generation algorithm to obtain a high-temperature melt segmentation image: Target recognition is performed on the high-temperature melt segmentation image to obtain a high-temperature melt region image.

3. The method according to claim 2, characterized in that The performing target recognition on the high-temperature melt segmentation image to obtain a high-temperature melt region image includes: Extracting a high-temperature melt region image that matches the high-temperature melt feature by performing geometric feature extraction and melt feature matching on the high-temperature melt segmentation image and performing target recognition using a deep learning model; Pixel value extraction is performed on the high-temperature melt area image to obtain the pixel value of each pixel, including the channel values of red light and green light.

4. The method according to claim 1, wherein The monochromatic radiation intensity includes red light radiation intensity and green light radiation intensity, the blackbody calibration coefficient includes a red light band blackbody calibration coefficient and a green light band blackbody calibration coefficient, and the pixel value of each pixel in the high-temperature melt area image is converted into monochromatic radiation intensity based on the predetermined blackbody calibration coefficient, including: Constructing a red light channel calibration equation based on the blackbody calibration coefficient of the red light band, and constructing a green light channel calibration equation based on the blackbody calibration coefficient of the green light band; For each pixel of the high-temperature melt area image, extracting a red light pixel value and a green light pixel value respectively; Substitute the ratio of the red light pixel value to the exposure time into the red light channel calibration equation to obtain the red light radiation intensity within the central wavelength of the red light channel. Substitute the ratio of the green light pixel value to the exposure time into the green light channel calibration equation to obtain the green light radiation intensity within the central wavelength of the green light channel. The central wavelength of the red light channel and the central wavelength of the green light channel are central wavelength parameters of the corresponding channels of the visible light image acquisition device.

5. The method according to claim 4, characterized in that Before converting the pixel value of each pixel in the high-temperature melt region image into a monochromatic radiation intensity based on a predetermined blackbody calibration coefficient, the method further includes: Acquire images of the interior of a blackbody furnace acquired by the visible light image acquisition device at different blackbody furnace temperatures and exposure times of the images of the interior of the blackbody furnace; For each blackbody furnace image, calculating the average red light channel and the average green light channel of the central area of the image, wherein the central area of the image is used to represent the area where the blackbody radiation light source is located; According to the red light channel average value, the green light channel average value and the exposure time, the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures are calculated using Planck's law; Polynomial fitting correction is performed on the red light radiation intensity and the green light radiation intensity at different blackbody furnace temperatures, and the fitting correction curves are solved to obtain the blackbody calibration coefficients corresponding to the red light band and the green light band, respectively.

6. The method according to claim 4, characterized in that The method of obtaining the temperature distribution data of the high-temperature melt region based on the two-color temperature measurement principle according to the monochromatic radiation intensity includes: For each pixel, the temperature value of the pixel is calculated using a dual-color temperature measurement formula based on the monochromatic radiation intensity, the central wavelength of the red light channel and the central wavelength of the green light channel of the visible light image acquisition device, and the red light band emissivity and the green light band emissivity of the high-temperature melt; Obtaining temperature distribution data of the high-temperature melt region based on the temperature value of each pixel; The dual-color temperature measurement formula is expressed as: ;in, Indicates temperature value, represents the second radiation constant, represents the central wavelength of the red channel, represents the central wavelength of the green channel, Represents the red light radiation intensity at the central wavelength of the red light channel, Represents the green light radiation intensity at the central wavelength of the green light channel, represents the red light band emissivity of the high temperature melt, Represents the green light band emissivity of high-temperature melt.

7. The method according to any one of claims 1 to 6, characterized in that After obtaining the temperature distribution data of the high-temperature melt region based on the two-color temperature measurement principle according to the monochromatic radiation intensity, the method further includes: Temperature display data is generated based on the temperature distribution data, and the temperature display data is sent to a display terminal to display the temperature state and distribution of the high-temperature melt to be monitored, wherein the temperature display data includes at least one of a two-dimensional temperature field map and a temperature distribution curve.

8. A high-temperature melt temperature monitoring device, characterized in that: include: An acquisition module, configured to acquire a target monitoring image of the high-temperature melt to be monitored acquired by a visible light image acquisition device; An image processing module is used to perform target recognition on the target monitoring image by taking the high-temperature melt to be monitored as the recognition object, and obtain an image of the high-temperature melt area; a conversion module, configured to convert the pixel value of each pixel in the high-temperature melt region image into a monochromatic radiation intensity based on a predetermined blackbody calibration coefficient; A generation module is used to obtain temperature distribution data of the high-temperature melt area based on the two-color temperature measurement principle according to the monochromatic radiation intensity.

9. A storage medium, characterized in that: The storage medium stores at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the high-temperature melt temperature monitoring method according to any one of claims 1 to 7.

10. A system, characterized in that: include: A visible light image acquisition device, a cooling device, an industrial computer and a communication bus, wherein the visible light image acquisition device and the industrial computer communicate with each other via the communication bus; The visible light image acquisition device is used to acquire a target monitoring image of the high-temperature melt to be monitored; The cooling device is used to protect the visible light image acquisition device and cool the visible light image acquisition device; The industrial computer is used to store at least one executable instruction and execute the operation corresponding to the high-temperature melt temperature monitoring method according to any one of claims 1 to 7 through the executable instruction.

Images