Solar tracking method based on light spot contour detection

Abstract

The invention discloses a sun tracking method based on light spot contour detection, and relates to the technical field of light spot contour detection and tracking. According to the solar tracking method based on light spot contour detection, image data of a solar spot contour area are obtained and analyzed in real time, and a light spot position deviation index, a light spot shape distortion index, a light spot brightness uniformity index and a light spot contrast uniformity index of the solar spot contour area are obtained and comprehensively analyzed; the method comprises the steps of obtaining a light spot comprehensive deviation index of a solar light spot contour area, judging and analyzing the comprehensive deviation index of the solar light spot contour area and a preset deviation threshold range, and adjusting and analyzing sunlight receiving equipment when the comprehensive deviation index of the solar light spot contour area is out of the preset deviation threshold range. Through multi-dimensional comprehensive analysis on the solar facula, the deviation condition of the facula can be accurately evaluated, so that a tracking system can capture fine deviation in real time, and the tracking direction and amplitude are adjusted in time.

Description

Technical Field

[0001] The invention relates to the technical field of light spot profile detection and tracking, and in particular to a sun tracking method based on light spot profile detection. Background Art

[0002] Solar tracking technology is to adjust the orientation of the sunlight receiving device in real time so that it always faces the sun. Traditional solar tracking methods mainly rely on mechanical structures (such as single-axis or dual-axis tracking systems) for adjustment. These methods measure the position of the sun through sensors or use preset algorithms for calculation. However, these methods are often limited by factors such as weather conditions, equipment accuracy and sensor costs, and complex mechanical structures may increase the difficulty of system maintenance.

[0003] In recent years, image processing technology has been widely used in the field of sun tracking. Image-based sun tracking methods use cameras or optical sensors to capture sun spots in the sky, and then estimate the exact position of the sun by analyzing image features (such as the shape, position or brightness distribution of the spot). Compared with traditional sensor methods, image processing technology has higher flexibility and accuracy, especially when dealing with obstructions or environmental changes.

[0004] As a technology based on image analysis, spot profile detection can infer the actual position of the sun by capturing the shape and characteristics of the spot formed by the sun at different positions. The advantage of this method is that it does not rely on the measurement of external light intensity, but achieves efficient tracking of the sun through precise spot profile capture and analysis. In addition, spot profile detection can avoid interference caused by solar reflection or scattered light, providing a relatively stable and reliable tracking method.

[0005] The limitations of the existing technology include at least the following problems. First, in the solar tracking system, traditional methods mostly rely on models or simplified assumptions. The detection and analysis of the light spot contour are often not precise enough, and it is difficult to fully reflect the multi-dimensional changes of the light spot, which can easily lead to the difficulty of accurately adjusting the tracking system, and then cause the accumulation of tracking errors in actual operation. Secondly, when analyzing the deviation of the solar spot, the existing technology often simplifies multiple influencing factors into a single indicator for processing, ignoring the relationship and importance of each factor, which can easily lead to the system being difficult to respond or adjust in time when the solar spot deviates slightly, thereby delaying equipment adjustment, increasing energy waste and reducing tracking accuracy. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a solar tracking method based on light spot profile detection, which solves the problem that in the solar tracking system, traditional methods mostly rely on models or simplified assumptions, and the detection and analysis of the light spot profile are often not precise enough, and it is difficult to fully reflect the multi-dimensional changes of the light spot, which easily leads to the difficulty in accurately adjusting the tracking system, and then causes the accumulation of tracking errors in actual operation. Secondly, when performing deviation analysis on the solar spot, the prior art often simplifies multiple influencing factors into a single indicator for processing, ignoring the relationship and importance of each factor, which easily leads to the system being difficult to respond or adjust in time when the solar spot deviates slightly, thereby delaying equipment adjustment, increasing energy waste and reducing tracking accuracy.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a sun tracking method based on spot contour detection, comprising the following steps: real-time acquisition of sun spot imaging surface data of a sunlight receiving device, and preprocessing, the sun spot imaging surface data including the pixel value and position coordinates of each pixel point in the aperture imaging surface; identification, detection and analysis of the preprocessed sun spot imaging surface data to obtain sun spot contour area image data, the sun spot area image data including the pixel value and position coordinates of each sun spot pixel point in the sun spot contour area image; comprehensive analysis of the sun spot contour area image data to obtain a sun spot wheel The light spot position deviation index, light spot shape distortion index, light spot brightness uniformity index and light spot contrast uniformity index of the solar spot contour area are comprehensively analyzed to obtain the light spot comprehensive deviation index of the solar spot contour area; the comprehensive deviation index of the solar spot contour area is judged and analyzed with the preset deviation threshold range; when the comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, the sunlight receiving device is adjusted and analyzed until the comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range.

[0008] Furthermore, the specific steps of preprocessing the sunlight spot imaging surface data of the sunlight receiving device are as follows: dividing the sunlight spot imaging surface data of the sunlight receiving device into a plurality of sunlight imaging surface area data, and each sunlight imaging surface area data includes a plurality of pixel points; performing comprehensive analysis on each sunlight imaging surface area data respectively to obtain the pixel variance value of each sunlight imaging surface area; performing judgment analysis on the pixel variance value of each sunlight imaging surface area and the preset variance threshold interval respectively; if the pixel variance value is within the preset variance threshold interval, the corresponding sunlight imaging surface area will be subjected to pixel retention processing, that is, the pixel value will be retained; if the pixel variance value is outside the preset variance threshold interval and is lower than the preset variance threshold interval lower limit, the corresponding sunlight imaging surface area will be subjected to Gaussian filtering processing; if the pixel variance value is outside the preset variance threshold interval and is higher than the preset variance threshold interval upper limit, the corresponding sunlight imaging surface area will be subjected to median filtering processing.

[0009] Furthermore, the specific steps of identifying, detecting and analyzing the preprocessed sunlight spot imaging surface data to obtain the sunlight spot contour area image data are as follows: comprehensively analyzing each sunlight imaging surface area data respectively to obtain the pixel mean of each sunlight imaging surface area, and marking it as the pixel division threshold of each sunlight imaging surface area; binarizing each sunlight imaging surface area data based on the pixel division threshold to obtain a binary image of each sunlight imaging surface area; performing edge detection and contour extraction on each sunlight imaging surface area binary image to obtain sunlight spot contour area image data.

[0010] Furthermore, the specific formula for calculating the comprehensive deviation index of the sun spot contour area is as follows: Among them, ZpL is the comprehensive deviation index of the sun spot contour area, GpL is the spot position deviation index of the sun spot contour area, α 1 is the deviation coefficient stored in the database, GsZ is the spot shape distortion index of the sun spot contour area, α 2 is the distortion coefficient stored in the database, GjY is the spot brightness uniformity index of the sun spot contour area, α 3 is the brightness uniformity coefficient stored in the database, GdB is the spot contrast uniformity index of the sun spot contour area, α 4 is the contrast uniformity coefficient stored in the database, α 1 +α 2 +α 3 +α 4 =1, e is a natural constant.

[0011] Furthermore, the specific steps of obtaining the spot position deviation index of the solar spot contour area are as follows: read the horizontal coordinate value, vertical coordinate value, and pixel value of each spot pixel point in the solar spot contour area image, and perform comprehensive analysis respectively to obtain the spot geometric center coordinates, including the center horizontal coordinate value and the center vertical coordinate value; obtain the spot reference center coordinates of the solar spot contour area, and perform comprehensive analysis with the spot geometric center coordinates to obtain the spot position deviation index of the solar spot contour area, wherein the spot reference center coordinates include the reference center horizontal coordinate value and the reference center vertical coordinate value; wherein the specific formula for calculating the center horizontal coordinate value and the center vertical coordinate value of the spot geometric center coordinate is as follows: Among them, x′ is the central abscissa value of the geometric center coordinate of the light spot, x i is the horizontal coordinate value of the i-th spot pixel point in the sun spot contour area image, XsZ i is the pixel value of the i-th spot pixel in the solar spot contour area image, y′ is the central ordinate value of the spot geometric center coordinate, y i is the ordinate value of the i-th spot pixel in the solar spot contour area image, i = 1, 2, 3, ..., i 0 ,i 0 It is the number of spot pixels in the sun spot contour area image.

[0012] Furthermore, the specific formula for calculating the spot position deviation index of the sun spot contour area is as follows: Among them, GpL is the spot position deviation index of the solar spot contour area, x′ is the central horizontal coordinate value of the spot geometric center coordinates, x″ is the reference center horizontal coordinate value of the spot reference center coordinates, y′ is the central vertical coordinate value of the spot geometric center coordinates, y″ is the reference center vertical coordinate value of the spot reference center coordinates, and DjX is the diagonal length of the solar spot contour area.

[0013] Furthermore, the specific steps of obtaining the spot shape distortion index of the solar spot contour area are as follows: counting the number of spot pixels in the solar spot contour area image, and marking them as the solar spot contour area area value; and counting the number of boundary spot pixels in the solar spot contour area image, and marking them as the solar spot contour area perimeter value; performing a comprehensive analysis on the solar spot contour area area value and the solar spot contour area perimeter value to obtain the spot shape distortion index of the solar spot contour area; wherein, the specific formula for calculating the spot shape distortion index of the solar spot contour area is as follows: Among them, GsZ is the spot shape distortion index of the sun spot contour area, π is the pi, MjZ is the area value of the sun spot contour area, and ZcZ is the circumference value of the sun spot contour area.

[0014] Furthermore, the specific steps for obtaining the spot brightness uniformity index of the solar spot contour area are as follows: for each spot pixel in the solar spot contour area image, respectively identify the number of adjacent spot pixels in the set neighborhood; comprehensively analyze the pixel value of each spot pixel in the solar spot contour area image in combination with the pixel value of each adjacent spot pixel in the set neighborhood, and obtain the spot brightness neighborhood mean and spot brightness neighborhood standard deviation value of each spot pixel in the solar spot contour area image; comprehensively analyze the spot brightness neighborhood mean and spot brightness neighborhood standard deviation value of each spot pixel in the solar spot contour area image, and obtain the spot brightness uniformity index of the solar spot contour area; wherein, the specific formula for calculating the spot brightness neighborhood mean and spot brightness neighborhood standard deviation value of each spot pixel in the solar spot contour area image and the spot brightness uniformity index of the solar spot contour area is as follows: Among them, LjZ i is the neighborhood mean of the brightness of the i-th spot pixel in the sun spot contour area image, XsZ i is the pixel value of the i-th spot pixel in the sun spot contour area image, XsZ it is the pixel value of the tth adjacent spot pixel in the set neighborhood of the i-th spot pixel in the solar spot contour area image, LbC i is the standard deviation of the spot brightness neighborhood of the i-th spot pixel point in the sun spot contour area image, LjY is the spot brightness uniformity index of the sun spot contour area, i = 1, 2, 3, ..., i 0 ,i 0 is the number of spot pixels in the image of the sun spot contour area, t = 1, 2, 3, ..., t 0 , t 0 To set the number of adjacent spot pixels in the neighborhood.

[0015] Furthermore, the specific steps of obtaining the spot contrast uniformity index of the solar spot contour area are as follows: compare and analyze the pixel values ​​of each spot pixel point in the solar spot contour image data respectively to obtain the maximum spot pixel value and the minimum spot pixel value in the solar spot contour image; comprehensively analyze the maximum spot pixel value and the minimum spot pixel value in the solar spot contour image to obtain the comprehensive contrast index of the solar spot contour area; divide the solar spot contour image data into a number of solar spot contour divided area image data, and each solar spot contour divided area image data includes a number of spot pixel points; compare and analyze the pixel values ​​of each spot pixel point in each solar spot contour divided area image data respectively to obtain each The maximum spot pixel value and the minimum spot pixel value of the divided area in the solar spot contour divided area image; the maximum spot pixel value and the minimum spot pixel value of the divided area in each solar spot contour divided area image are comprehensively analyzed to obtain the divided area contrast index of each solar spot contour divided area; the comprehensive contrast index of the solar spot contour area and the divided area contrast index of each solar spot contour divided area are comprehensively analyzed to obtain the spot contrast uniformity index of the solar spot contour area; wherein, the specific formulas for calculating the comprehensive contrast index of the solar spot contour area, the divided area contrast index of each solar spot contour divided area, and the spot contrast uniformity index of the solar spot contour area are as follows: Among them, ZdB is the comprehensive contrast index of the sun spot contour area, XsZ′ Max is the maximum spot pixel value in the sun spot profile image, XsZ′ Min is the minimum spot pixel value in the sun spot profile image, QdB u is the contrast index of the divided area of ​​the u-th sun spot contour divided area, is the maximum spot pixel value of the divided area in the u-th sun spot contour divided area image, is the minimum spot pixel value of the divided area in the image of the u-th sun spot contour divided area, GdB is the spot contrast uniformity index of the sun spot contour area, u=1, 2, 3, …, u 0 ,u 0 The number of image data for dividing the sun spot contour into regions.

[0016] Furthermore, when the comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, the sunlight receiving device is adjusted and analyzed until the comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range, and the steps are as follows: when the comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, the abnormal index in the comprehensive deviation index of the solar spot contour area is identified, and corresponding adjustment measures are taken; and the adjusted comprehensive deviation index of the solar spot contour area is analyzed, and a judgment analysis is performed with the preset deviation threshold range; if the adjusted comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range, the adjustment is terminated; if the adjusted comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, the adjustment measures step, the step of analyzing the adjusted comprehensive deviation index of the solar spot contour area, and the judgment analysis step are repeated until the comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range.

[0017] The present invention has the following beneficial effects:

[0018] (1) The solar tracking method based on spot profile detection can accurately evaluate the deviation of the solar spot by comprehensively analyzing the spot position deviation index, spot shape distortion index, spot brightness uniformity index and spot contrast uniformity index. This multi-dimensional analysis method not only takes into account the position error of the spot, but also includes shape distortion, brightness and contrast uniformity, thereby ensuring that the tracking system can capture subtle deviations in real time and adjust the tracking direction and amplitude in time. Traditional solar tracking methods are often based only on position offset or simple brightness changes, while this comprehensive analysis method can provide a more accurate deviation index, which can ensure high-precision solar tracking under dynamic lighting conditions.

[0019] (2) The solar tracking method based on spot profile detection pre-processes the solar spot imaging surface data in a fine manner. First, the data is divided into several areas and the pixel variance value of each area is calculated. Then, different filtering methods are used according to the different variance values ​​to effectively suppress noise. Different from the traditional fixed filtering method, this adaptive filtering based on data variance can automatically select a suitable filtering method according to the change of image quality, further improving the data quality and providing a more reliable data source for subsequent spot profile recognition and deviation analysis.

[0020] (3) The solar tracking method based on spot profile detection calculates the comprehensive deviation index of the solar spot profile area and compares it with the preset deviation threshold, so as to determine whether equipment adjustment is needed. When the comprehensive deviation index exceeds the preset range, the system will identify the abnormal index and take corresponding adjustment measures until the deviation index returns to the normal range. This dynamic adjustment mechanism can be optimized and adjusted in real time according to different environmental conditions, avoiding the misjudgment or delayed reaction that may be caused by static threshold judgment, ensuring that the solar tracking equipment can always maintain the best working state.

[0021] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention is a flow chart of a sun tracking method based on spot profile detection.

[0023] Figure 2 The present invention is a flowchart of the specific steps of obtaining the spot position deviation index of the solar spot contour area in a solar tracking method based on spot contour detection. DETAILED DESCRIPTION

[0024] The embodiment of the present application solves the problem that in a solar tracking system, traditional methods rely on models or simplified assumptions, and the detection and analysis of the light spot profile are often not precise enough, and it is difficult to fully reflect the multi-dimensional changes of the light spot, which easily leads to difficulty in accurately adjusting the tracking system, and further causes the accumulation of tracking errors in actual operation. Secondly, when performing deviation analysis on the solar spot, the prior art often simplifies multiple influencing factors into a single indicator for processing, ignoring the relationship and importance of each factor, which easily leads to the system being difficult to respond or adjust in time when a slight deviation occurs in the solar spot, thereby delaying equipment adjustment, increasing energy waste and reducing tracking accuracy.

[0025] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0026] First, the system acquires the solar spot imaging surface data in real time, including the pixel value and position coordinates of each pixel point. Then, the data is divided into multiple areas for comprehensive analysis and calculation of the pixel variance value of each area. According to the size of the variance value, the system performs different types of processing on the pixels: if the variance is within the preset threshold range, the original pixel value is retained; if the variance is too high, median filtering is performed; if it is too low, Gaussian filtering is performed. Then, the pre-processed data is used to identify and detect the spot contour. The pixel value of each area will be binarized according to the set threshold, and then the image data of the spot contour area will be extracted through edge detection and contour extraction algorithms. Finally, the comprehensive deviation index is calculated by comprehensively analyzing multiple indicators such as the spot position deviation, shape distortion, brightness uniformity, contrast uniformity, etc. of the solar spot contour area. If the deviation index exceeds the preset threshold range, the system will adjust the device until the comprehensive deviation index returns to the predetermined range.

[0027] See also Figure 1 The embodiment of the present invention provides a technical solution: a sun tracking method based on spot contour detection, comprising the following steps: real-time acquisition of sun spot imaging surface data of a sunlight receiving device, and preprocessing, wherein the sun spot imaging surface data includes the pixel value and position coordinates of each pixel point in the aperture imaging surface; identification detection and analysis of the preprocessed sun spot imaging surface data to obtain sun spot contour area image data, wherein the sun spot area image data includes the pixel value and position coordinates of each sun spot pixel point in the sun spot contour area image; comprehensive analysis of the sun spot contour area image data to obtain Spot position deviation index, spot shape distortion index, spot brightness uniformity index, spot contrast uniformity index; conduct comprehensive analysis on the spot position deviation index, spot shape distortion index, spot brightness uniformity index, and spot contrast uniformity index of the solar spot contour area to obtain the comprehensive deviation index of the solar spot contour area; conduct judgment and analysis on the comprehensive deviation index of the solar spot contour area and the preset deviation threshold range; when the comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, adjust and analyze the sunlight receiving device until the comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range.

[0028] Specifically, the specific steps of preprocessing the solar spot imaging surface data of the sunlight receiving device are as follows: dividing the solar spot imaging surface data of the sunlight receiving device into a plurality of sunlight imaging surface area data (for example, 10x10 or 16x16 pixels), and each sunlight imaging surface area data includes a plurality of pixel points; performing comprehensive analysis on each sunlight imaging surface area data to obtain the pixel variance value of each sunlight imaging surface area; performing judgment analysis on the pixel variance value of each sunlight imaging surface area and the preset variance threshold interval; if the pixel variance value is within the preset variance threshold interval, the corresponding sunlight imaging surface area is The sunlight imaging surface area adopts pixel retention processing, that is, the pixel value is retained; if the pixel variance value is outside the preset variance threshold interval and is lower than the preset variance threshold interval lower limit, the corresponding sunlight imaging surface area will be subjected to Gaussian filtering processing. The specific steps are: assign a weight to each pixel in the sunlight imaging surface area, and its weight is determined by the Gaussian function, and then calculate the new value of each pixel, that is, multiply the values ​​of all pixels around the current pixel by the corresponding Gaussian weight, and then sum them up, and finally get the new pixel value. The specific implementation example is as follows: There is a 3x3 window, and there is a 3x3 window. The original pixel value matrix is ​​as follows: The Gaussian weight matrix (with a standard deviation of 1 in this implementation) is as follows: Then the original image matrix and the Gaussian weight matrix are multiplied one by one, and the products of each pixel are summed to obtain a new pixel. For example, for the center pixel position (2, 2), the pixel value of the 3x3 window is multiplied by the weight matrix one by one, and then the sum is obtained: new pixel value = (100*0.075) + (150*0.125) + (200*0.075) + (150*0.125) + (100*0.200) + (50*0.125) + (200*0.075) + (100*0.125) + (50*0.075) = 7.5 + 18.75 + 15 + 18.75 + 20 + 6.25 + 15 + 12.5 + 3.75 = 118.5.

[0029] If the pixel variance value is outside the preset variance threshold range and is higher than the preset upper limit of the variance threshold range, the corresponding sunlight imaging surface area will be subjected to median filtering. The specific steps are: sorting the pixels in the sunlight imaging surface area to obtain the median pixel value, and using it as the new pixel value of each pixel in the sunlight imaging surface area. The specific implementation example is as follows: There is a 3x3 window, and the original pixel values ​​are as follows: Then they are sorted and the result is: [50, 100, 100, 150, 200, 200, 255, 255]. The median pixel value is 150, so the new pixel value of each pixel in the sunlight imaging area is 150.

[0030] In this implementation, by analyzing the data of the sunlight imaging surface area, the processing method is adaptively selected according to the pixel variance value. For low-noise areas with small variance, the original pixel data is retained; and for high-noise areas with large variance, different filtering methods are used: Gaussian filtering is applied to low-noise areas to remove small noise and maintain smoothness; median filtering is used in high-noise areas to effectively remove salt and pepper noise and retain edge information. This adaptive processing method can adjust the filtering method according to local information, avoids the singleness and over-smoothing problems of traditional methods, and improves image quality. Through local processing, the pixels in each area are analyzed independently to ensure that the amount of calculation is reduced in low-noise areas and accurate denoising is performed in noisy areas, thereby balancing processing accuracy and efficiency. The data preprocessing step ensures more accurate spot contour recognition and deviation index calculation through denoising, especially under complex lighting and environmental changes, which improves the stability and robustness of the system.

[0031] Specifically, the specific steps of identifying, detecting and analyzing the preprocessed sunlight spot imaging surface data to obtain the sunlight spot contour area image data are as follows: comprehensively analyzing each sunlight imaging surface area data respectively to obtain the pixel mean of each sunlight imaging surface area, and marking it as the pixel division threshold of each sunlight imaging surface area; binarizing each sunlight imaging surface area data based on the pixel division threshold to obtain a binary image of each sunlight imaging surface area, that is, if the pixel value in the image is ≥ the pixel division threshold, the pixel is considered to belong to the spot area and is marked as 1, otherwise it is the background and is marked as 0; edge detection processing and contour extraction processing are performed on each sunlight imaging surface area binary image to obtain sunlight spot contour area image data.

[0032] Among them, the edge detection processing is specifically Canny edge detection, and its specific steps are: use the Sobel operator (or other gradient operators) to calculate the gradient value of each pixel point, the gradient value represents the amplitude of brightness change (including gradient amplitude, gradient direction), and the place with a large gradient value is the edge of the image.

[0033] In the gradient map, if the gradient value of a pixel is not the local maximum of the edge, the pixel is suppressed (that is, set to 0) and the edge point is retained. This process is used to reduce the number of detected edges and make the edges more accurate.

[0034] For each pixel point, in its gradient direction, if the gradient value of the pixel point is not the local maximum, it is set to 0.

[0035] Two thresholds (high threshold and low threshold) are used to determine whether it is an edge. Pixels above the high threshold are strong edges, pixels below the low threshold are weak edges, and pixels between the two are judged based on their connection with the strong edge. Strong edge pixels are directly marked as edges, and weak edge pixels are also marked as edges if they are connected to the strong edge, otherwise they are removed.

[0036] After Canny edge detection, a new binary image is obtained. The edge part of the image is 1 (white) and the other part is 0 (black). This image represents the edge of the light spot.

[0037] The specific steps of contour extraction processing are as follows: after edge detection, contour extraction is performed, that is, using a depth-first search (DFS) or breadth-first search (BFS) algorithm, starting from an edge pixel and propagating to the surrounding pixels until a complete connected area is found. Each time a connected area is found, a unique identifier is assigned to this area.

[0038] Each pixel in the image is checked to determine whether it has been marked as part of the light spot. If not, the area is expanded until all the light spot areas are marked.

[0039] Once connected regions are marked, contours can be extracted from these marked regions. Contours usually refer to the boundaries of the regions, or the collection of pixels adjacent to the background.

[0040] In this embodiment, by calculating the pixel mean of the sunlight imaging surface area and performing binarization processing, the spot area can be effectively separated from the background. The binarization is based on a preset pixel threshold, and the part greater than or equal to the threshold is marked as the spot area (1), and the rest is the background (0). This method is particularly suitable for the situation where the spot intensity changes greatly. It can clearly separate the spot and the background, and provide accurate area definition for subsequent edge detection and contour extraction. The Canny edge detection method is used, which can accurately identify the edge of the spot. The potential edge is determined by calculating the gradient value, and the local maximum value is suppressed to remove irrelevant edges. High and low thresholds are set to distinguish strong and weak edges to ensure the accuracy of edge extraction. This process can effectively eliminate noise, ensure the clarity of the spot edge, and improve the stability of subsequent contour extraction. After edge detection, the DFS or BFS algorithm is used to identify the connected area, and the complete spot contour is extracted by pixel-by-pixel scanning, and a unique identifier is assigned to each area. In this way, the real contour data of the spot can be accurately obtained, which provides a basis for deviation analysis and sun tracking error correction, thereby improving the response speed and accuracy of the system in dynamic spot changes.

[0041] Specifically, the specific formula for calculating the spot comprehensive deviation index of the sun spot contour area is as follows: Among them, ZpL is the comprehensive deviation index of the sun spot contour area, GpL is the spot position deviation index of the sun spot contour area, α 1 is the deviation coefficient stored in the database, GsZ is the spot shape distortion index of the sun spot contour area, α 2 is the distortion coefficient stored in the database, GjY is the spot brightness uniformity index of the sun spot contour area, α 3 is the brightness uniformity coefficient stored in the database, GdB is the spot contrast uniformity index of the sun spot contour area, α 4 is the contrast uniformity coefficient stored in the database, α 1 +α 2 +α 3 +α 4 =1, e is a natural constant, and in this embodiment, its value is 2.71.

[0042] It needs to be explained that when calculating the comprehensive deviation index of the sun spot contour area, the spot position deviation index, the spot shape distortion index, the spot brightness uniformity index and the spot contrast uniformity index of the sun spot contour area are all de-unitized, so they can be calculated directly.

[0043] α stored in the database 1 , α 2 , α 3 , α 4 The specific calculation process of is: obtain the reference spot position deviation index, reference spot shape distortion index, reference spot brightness uniformity index, and reference spot contrast uniformity index of the reference solar spot contour area (that is, the spot contour area does not deviate), and perform standardization processing, and then sum and analyze the reference spot position deviation index, reference spot shape distortion index, reference spot brightness uniformity index, and reference spot contrast uniformity index of the reference solar spot contour area (that is, the spot contour area does not deviate) after the standardization processing to obtain the index and value, and then perform proportion analysis on the reference spot position deviation index, reference spot shape distortion index, reference spot brightness uniformity index, and reference spot contrast uniformity index of the reference solar spot contour area (that is, the spot contour area does not deviate) after the standardization processing and the index and value, respectively, and the analysis result is the corresponding coefficient.

[0044] In this implementation scheme, by calculating the light spot position deviation index, shape distortion index, brightness uniformity index and contrast uniformity index, the method can comprehensively evaluate the light spot quality from multiple dimensions. Each index reflects the characteristics of the light spot such as spatial position, shape, brightness distribution and contrast distribution, and can accurately capture the changes of the light spot, thereby providing a basis for sun tracking adjustment. These comprehensive evaluations can avoid the misjudgment that may be caused by a single indicator, and improve the tracking accuracy and adaptability of the method. In order to improve the flexibility of the method, the coefficients stored in the database are used in the calculation of the deviation index, allowing the weights of each indicator to be dynamically adjusted according to different environmental conditions and needs, ensuring that the evaluation process is personalized according to the actual situation of the light spot. Weighted summation, this method can balance the influence of various deviation factors and obtain the final comprehensive deviation index of the light spot. This weighted summation method makes the deviation evaluation more in line with the needs of practical applications. In addition, this method introduces a natural constant (about 2.71) into the formula. This constant helps to enhance the stability of the calculation, so that the calculation results are not affected by unit and scale changes, and enhances the universality and consistency of the formula. All deviation indices are normalized during the calculation process, which simplifies the calculation process, improves the calculation efficiency, and avoids complex unit conversion and processing steps. This design improves the accuracy, flexibility and stability of the system, ensuring that the light spot evaluation process is more efficient and reliable, and adapts to different light spot changes and environmental conditions.

[0045] Specifically, Figure 2 As shown, the specific steps for obtaining the spot position deviation index of the solar spot contour area are as follows: read the horizontal coordinate value, vertical coordinate value, and pixel value of each spot pixel point in the solar spot contour area image, and perform comprehensive analysis respectively to obtain the spot geometric center coordinates, including the center horizontal coordinate value and the center vertical coordinate value; obtain the spot reference center coordinates of the solar spot contour area, and perform comprehensive analysis with the spot geometric center coordinates to obtain the spot position deviation index of the solar spot contour area, and the spot reference center coordinates include the reference center horizontal coordinate value and the reference center vertical coordinate value.

[0046] The specific formula for calculating the central abscissa value and central ordinate value of the geometric center coordinates of the light spot is as follows: Among them, X′ is the central abscissa value of the geometric center coordinates of the light spot, x i is the horizontal coordinate value of the i-th spot pixel point in the sun spot contour area image, XsZ i is the pixel value of the i-th spot pixel in the solar spot contour area image, y′ is the central ordinate value of the spot geometric center coordinate, y i is the ordinate value of the i-th spot pixel in the solar spot contour area image, i = 1, 2, 3, ..., i 0 ,i 0It is the number of spot pixels in the sun spot contour area image.

[0047] The specific formula for calculating the spot position deviation index of the sun spot contour area is as follows: Among them, GpL is the spot position deviation index of the solar spot contour area, x′ is the central horizontal coordinate value of the spot geometric center coordinates, x″ is the reference center horizontal coordinate value of the spot reference center coordinates, y′ is the central vertical coordinate value of the spot geometric center coordinates, y″ is the reference center vertical coordinate value of the spot reference center coordinates, and DjX is the diagonal length of the solar spot contour area.

[0048] It should be explained that the specific calculation process of the diagonal length of the sun spot contour area is:

[0049] The leftmost part of the sun spot contour area with the smallest horizontal coordinate value is recorded as the minimum horizontal coordinate value;

[0050] The rightmost side of the sun spot contour area: the largest horizontal coordinate value is recorded as the maximum horizontal coordinate value;

[0051] The top edge of the sun spot contour area: the smallest ordinate value is recorded as the minimum ordinate value;

[0052] The bottom edge of the sun spot contour area: the largest ordinate value is recorded as the maximum ordinate value;

[0053] Perform difference analysis on the minimum abscissa value, maximum abscissa value, minimum ordinate value, and maximum ordinate value of the sun spot contour area to obtain the width and height values ​​of the sun spot contour area;

[0054] The width and height of the sun spot contour area are calculated comprehensively, that is, the diagonal length of the sun spot contour area = (width 2 +Height value 2 ) 1 / 2 .

[0055] In this embodiment, the geometric center position of the light spot is the key parameter for the light spot deviation analysis. By calculating the horizontal and vertical coordinates of the geometric center of the light spot and comparing them with the center of the reference light spot, this method can accurately evaluate the position information of the light spot. The geometric center is the weighted average position of all light spot pixels, taking into account the actual brightness distribution of the light spot, so it can more accurately reflect the position change of the light spot. Different from the simple geometric center calculation, this calculation method based on pixel brightness weighting can better capture the actual change of the light spot and avoid errors caused by irregular light spots or changes in illumination. The calculation of the light spot position deviation index is based on the comparison with the reference light spot center. The reference center coordinates represent the center position of the light spot under ideal conditions. By calculating the deviation between the actual light spot geometric center and the reference center, the degree of light spot deviation can be directly reflected. Using the reference center coordinates as a standard can effectively reduce the interference of external factors (such as ambient light changes, equipment errors, etc.) on the deviation calculation, thereby improving the accuracy of light spot deviation analysis. When calculating the light spot position deviation index, this method introduces spatial size information by calculating the diagonal length of the light spot contour area. This approach not only considers the position difference of the light spot, but also the spatial size of the light spot area, avoiding the influence of the light spot deviation on the light spot size. Even if a small displacement occurs in a large spot, it may not significantly affect the spot quality due to its large size; while even a small displacement occurs in a small spot, it may have a greater impact on the tracking effect. Introducing the diagonal length calculation can ensure that the calculation of the deviation index is more comprehensive and adapt to spots of different sizes. When the weighted average method is used to calculate the geometric center of the spot, the influence of the brightness distribution of the spot on the center position is fully considered. The brightness of the spot is usually uneven. The weighted average ensures that the calculation of the geometric center is not only based on the geometric position of the spot, but also reflects the actual brightness distribution of the spot, thereby improving the accuracy of the calculation. This method avoids The oversensitivity in areas with weaker brightness more accurately describes the actual position deviation of the light spot. By combining the light spot position deviation index with the diagonal length, the calculation process is not limited to the position difference, but also takes into account the change in the light spot shape. The diagonal length, as a spatial metric, intuitively reflects the size and shape of the light spot, and can adapt to spots of different sizes and shapes, enhancing the flexibility and robustness of the algorithm. In practical applications, the shape and size of the light spot may be affected by various factors such as equipment and lighting, and the calculation based on the diagonal length enables this method to adapt to these changes more flexibly, thereby reducing errors and improving the stability of detection and analysis.

[0056] Specifically, the specific steps for obtaining the spot shape distortion index of the solar spot contour area are as follows: count the number of spot pixels in the solar spot contour area image, and mark them as the solar spot contour area area value; and count the number of boundary spot pixels in the solar spot contour area image (the boundary is obtained by the result of edge detection), and mark them as the solar spot contour area perimeter value; conduct a comprehensive analysis of the solar spot contour area area value and the solar spot contour area perimeter value to obtain the spot shape distortion index of the solar spot contour area.

[0057] The specific formula for calculating the spot shape distortion index of the sun spot contour area is as follows: Among them, GsZ is the spot shape distortion index of the sun spot contour area, π is the pi, MjZ is the area value of the sun spot contour area, and ZcZ is the circumference value of the sun spot contour area.

[0058] In this embodiment, the shape of the light spot is a crucial parameter in the solar tracking system, especially when the light spot deviates, deforms or distorts, it may cause tracking errors. By counting the area and circumference of the solar spot contour area, the change in the light spot shape can be quantitatively evaluated, thereby reflecting its degree of distortion. The ratio of area to circumference is highly representative and can effectively describe the shape of the light spot. When the light spot is circular or nearly circular, the ratio of area to circumference is close to the ideal circular value; if the light spot is deformed (such as an elliptical or irregular shape), the ratio will change. Through this calculation, the method can detect and respond to the distortion of the light spot shape in a timely manner to ensure that the system makes adjustments when deformation occurs. The introduction of pi (π) as a calculation constant can standardize the light spot shape distortion index to ensure that the index has physical meaning and consistency. The use of pi helps to compare the light spot shape distortion index with the standard geometric shape (circle), so that the calculation results are more in line with practical applications. In particular, in practical applications, the solar spot The ideal shape should be nearly circular. Therefore, through the standardization of pi, this method can more accurately reflect the degree of deviation of the shape. No matter how complex the spot shape is, the distortion index can be evaluated under a unified standard. Area and circumference are two basic geometric parameters of the spot shape, which fully reflect the spatial shape of the spot. The area value represents the total coverage area of ​​the spot, and the circumference describes the complexity of the spot boundary. By comprehensively analyzing these two parameters, this method can more accurately determine whether the spot is distorted and avoid the errors that may be caused by a single parameter. The combined calculation of area and circumference not only reflects the change in the size of the spot, but also can accurately capture the subtle changes in the spot boundary. When the spot shape is deformed, the extension or contraction of the boundary has a greater impact on the spot distortion, and the circumference can effectively capture these changes. Therefore, a comprehensive analysis of the ratio of area to circumference can provide a more comprehensive and accurate evaluation of the spot shape distortion, ensuring that the system can track and adjust efficiently and accurately under different spot shapes.

[0059] Specifically, the specific steps for obtaining the spot brightness uniformity index of the solar spot contour area are as follows: for each spot pixel in the solar spot contour area image, respectively identify the number of adjacent spot pixel points in the set neighborhood; comprehensively analyze the pixel value of each spot pixel in the solar spot contour area image in combination with the pixel value of each adjacent spot pixel point in the set neighborhood to obtain the spot brightness neighborhood mean and spot brightness neighborhood standard deviation value of each spot pixel in the solar spot contour area image; comprehensively analyze the spot brightness neighborhood mean and spot brightness neighborhood standard deviation value of each spot pixel in the solar spot contour area image to obtain the spot brightness uniformity index of the solar spot contour area.

[0060] The specific formulas for calculating the spot brightness neighborhood mean, spot brightness neighborhood standard deviation, and spot brightness uniformity index of the solar spot outline area for each spot pixel in the solar spot outline area image are as follows: Among them, LjZ i is the neighborhood mean of the brightness of the i-th spot pixel in the sun spot contour area image, XsZ i is the pixel value of the i-th spot pixel in the sun spot contour area image, XsZ it is the pixel value of the tth adjacent spot pixel in the set neighborhood of the i-th spot pixel in the solar spot contour area image, LbC i is the standard deviation of the spot brightness neighborhood of the i-th spot pixel point in the sun spot contour area image, LjY is the spot brightness uniformity index of the sun spot contour area, i = 1, 2, 3, ..., i 0 ,i 0 is the number of spot pixels in the image of the sun spot contour area, t = 1, 2, 3, ..., t 0 , t 0 To set the number of adjacent spot pixels in the neighborhood.

[0061] In this embodiment, the brightness uniformity of the light spot is a key indicator of the light spot quality, especially in applications such as sunlight tracking and energy focusing, where the brightness uniformity directly affects the performance of the system. By calculating the mean and standard deviation of the brightness of each pixel and its neighborhood, the brightness fluctuation in the light spot area can be effectively measured, thereby providing a detailed brightness distribution analysis. If the brightness of the light spot area is relatively uniform, the method can maintain the best energy utilization and high tracking accuracy; if the brightness distribution is uneven, the method will detect and adjust in time to optimize the light spot quality and tracking performance. By comprehensively analyzing the brightness information of each pixel and its surrounding neighborhood, the method can accurately detect local brightness deviations and avoid undetected small-scale brightness changes. The neighborhood mean and standard deviation can describe the light spot brightness in detail. The method not only considers the brightness of a single pixel, but also combines the neighborhood information to improve the accuracy of the spot brightness uniformity assessment. Even small brightness changes can be captured in time by this method. By calculating the brightness neighborhood mean and standard deviation, this method can identify and process abnormal values ​​with excessive brightness fluctuations in the spot. These abnormal values ​​may be caused by sensor noise, atmospheric interference and other factors. The standard deviation is an effective tool to measure brightness changes. It can reflect the stability and uniformity of the spot brightness, help the system eliminate errors caused by the environment, equipment or noise, and ensure the stability of the spot brightness uniformity index. For the sunlight tracking system, brightness uniformity optimization can reduce the deviation caused by errors and ensure the high accuracy and stability of the system.

[0062] Specifically, the specific steps of obtaining the spot contrast uniformity index of the solar spot contour area are as follows: comparatively analyzing the pixel values ​​of each spot pixel point in the solar spot contour image data, respectively, to obtain the maximum spot pixel value and the minimum spot pixel value in the solar spot contour image; comprehensively analyzing the maximum spot pixel value and the minimum spot pixel value in the solar spot contour image, to obtain the comprehensive contrast index of the solar spot contour area; dividing the solar spot contour image data into a plurality of solar spot contour divided area image data, and each solar spot contour divided area image data includes a plurality of spot pixel points; for each solar spot circle The pixel values ​​of each spot pixel point in the contour division area image data are compared and analyzed respectively to obtain the maximum spot pixel value and the minimum spot pixel value of the division area in each sun spot contour division area image; the maximum spot pixel value and the minimum spot pixel value of the division area in each sun spot contour division area image are comprehensively analyzed to obtain the division area contrast index of each sun spot contour division area; the comprehensive contrast index of the sun spot contour area and the division area contrast index of each sun spot contour division area are comprehensively analyzed to obtain the spot contrast uniformity index of the sun spot contour area.

[0063] The specific formulas for calculating the comprehensive contrast index of the sun spot contour area, the contrast index of each divided area of ​​the sun spot contour, and the spot contrast uniformity index of the sun spot contour area are as follows: Among them, ZdB is the comprehensive contrast index of the sun spot contour area, XsZ′ Max is the maximum spot pixel value in the sun spot profile image, XsZ′ Min is the minimum spot pixel value in the sun spot profile image, QdB u is the contrast index of the divided area of ​​the u-th sun spot contour divided area, is the maximum spot pixel value of the divided area in the u-th sun spot contour divided area image, is the minimum spot pixel value of the divided area in the image of the u-th sun spot contour divided area, GdB is the spot contrast uniformity index of the sun spot contour area, u=1, 2, 3, …, u 0 ,u 0 The number of image data for dividing the sun spot contour into regions.

[0064] In this embodiment, the contrast uniformity of the light spot directly affects the accuracy and efficiency of the sun tracking system. Especially when tracking the details of the light spot, uneven contrast may cause the positioning error or increase of the light spot. By analyzing the maximum and minimum pixel values ​​of the light spot area and its divided areas, the contrast distribution of the light spot can be accurately determined, thereby evaluating its uniformity. This method can identify whether there are overly bright or dark parts in the light spot, and avoid the uneven contrast affecting the tracking accuracy. Contrast analysis enables the system to adjust the tracking process in real time, optimize the lens focal length or sensor gain, and avoid local overexposure or shadow problems of the light spot. By calculating the contrast uniformity index, this method can dynamically optimize the tracking algorithm to ensure that the contrast of the light spot in the imaging area remains consistent, avoiding Too large or too small a contrast may cause errors or blurring. Too large a contrast may cause overexposure, while too small a contrast may cause loss of spot details and affect accuracy. This method optimizes the spot quality by accurately analyzing the contrast index of each area to ensure that details are retained without being too strong. This method can effectively identify and optimize areas with abnormal contrast in the spot, ensure a reasonable contrast distribution, and avoid the impact of uneven spot contrast on subsequent tracking and positioning. The contrast uniformity index provides a quantitative basis for spot quality analysis. Combined with the set threshold, this method can monitor the contrast changes of the spot in real time and make quick adjustments. By quantifying the contrast difference, this method can accurately identify spot quality issues, reduce human errors, and ensure high-precision spot quality evaluation and tracking performance.

[0065] Specifically, when the comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, the sunlight receiving device is adjusted and analyzed until the comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range, and the steps are as follows: when the comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, the abnormal index in the comprehensive deviation index of the solar spot contour area is identified, and corresponding adjustment measures are taken; and the adjusted comprehensive deviation index of the solar spot contour area is analyzed, and a judgment analysis is performed with the preset deviation threshold range; if the adjusted comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range, the adjustment is ended; if the adjusted comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, the adjustment measures step, the step of analyzing the adjusted comprehensive deviation index of the solar spot contour area, and the judgment analysis step are repeated until the comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range.

[0066] Among them, the specific implementation examples of abnormal index in the comprehensive deviation index of the sun spot contour area and taking corresponding adjustment measures are as follows:

[0067] If the abnormal index in the comprehensive deviation index of the solar spot profile area is the spot position deviation index, the spot can be brought closer to the target position by adjusting the azimuth angle, pitch angle or other relevant angles of the device.

[0068] If the abnormal index in the comprehensive deviation index of the solar spot profile area is the spot shape distortion index, the shape distortion can be reduced by adjusting the focus of the device or adjusting the optical device.

[0069] If the abnormal index in the comprehensive deviation index of the sun spot contour area is the spot brightness uniformity index, it can be corrected by adjusting the lens, light source and other equipment, or making appropriate optical adjustments.

[0070] If the abnormal index in the comprehensive deviation index of the sun spot outline area is the spot contrast uniformity index, it can be corrected by recalibrating the intensity of the light source or adjusting the lens focal length.

[0071] According to the determined adjustment direction and amplitude, various parameters of the sunlight receiving device are actually operated and adjusted, for example:

[0072] Adjust the device's electric tracking system to make angle adjustments.

[0073] Adjust the optical components of the device, such as the condenser, lenses, or diaphragms.

[0074] Parameters such as light source intensity and exposure time can be adjusted through software.

[0075] In this embodiment, when the comprehensive deviation index of the solar spot profile exceeds a preset threshold, the method can automatically detect and take targeted adjustment measures according to the specific abnormal type of the light spot (such as position offset, shape distortion, etc.). By real-time monitoring of the light spot deviation, the method can quickly and automatically adjust the equipment to ensure that the sunlight tracking is always in the best state, avoiding the tracking accuracy affected by environmental changes or equipment errors. If the light spot position deviates, the light spot can be accurately aligned by adjusting the azimuth or pitch angle of the device; if the light spot shape is distorted, the distortion is reduced by adjusting the optical device. Such a method ensures that the light spot quality is optimized without the need for global repeated calibration. The method can automatically identify different types of deviations and take corresponding adjustment measures according to the specific type of deviation. For example, if the light spot brightness is uneven, the brightness can be balanced by adjusting the lens; if the light spot shape is distorted, the optical device can be adjusted to reduce the distortion. If the spot shape is distorted, the distortion is reduced by optimizing the focus. Through these fine adjustments, the quality of the light spot can be improved, ensuring that the various indicators of the light spot (such as position, shape, brightness, and contrast) are always in the best state. This dynamic adjustment method reduces human intervention, improves the autonomy and efficiency of the system, and ensures that the solar tracking system can respond quickly and maintain high precision under different lighting conditions. Whenever the comprehensive deviation index of the light spot exceeds the preset threshold, the system will automatically execute the adjustment steps until the light spot returns to normal. This not only saves time and resources, but also reduces human operation errors and improves the system's automation level and self-adjustment ability. Through precise control of the light spot, this method can improve the capture accuracy of sunlight and ensure that the tracker can more accurately capture the position and movement trajectory of the sun, thereby improving the reliability and accuracy of the entire solar tracking system.

[0076] In summary, this application has at least the following effects:

[0077] By conducting a comprehensive analysis of the solar spot based on the spot position deviation index, spot shape distortion index, spot brightness uniformity index and spot contrast uniformity index, the deviation of the spot can be accurately evaluated. This multi-dimensional analysis method not only takes into account the position error of the spot, but also includes shape distortion, brightness and contrast uniformity, thereby ensuring that the tracking system can capture subtle deviations in real time and adjust the tracking direction and amplitude in time. Traditional solar tracking methods are often only based on position offset or simple brightness changes, while this comprehensive analysis method can provide a more accurate deviation index, which can ensure high-precision solar tracking under dynamic lighting conditions.

[0078] Through the careful preprocessing of the solar spot imaging surface data, the data is first divided into several areas and the pixel variance value of each area is calculated. Then, different filtering methods are used according to the different variance values ​​to effectively suppress noise. Unlike the traditional fixed filtering method, this adaptive filtering based on data variance can automatically select the appropriate filtering method according to the changes in image quality, further improving the data quality and providing a more reliable data source for subsequent spot contour recognition and deviation analysis.

[0079] By calculating the comprehensive deviation index of the solar spot contour area and comparing it with the preset deviation threshold, it is possible to determine whether equipment adjustment is needed. When the comprehensive deviation index exceeds the preset range, the system will identify the abnormal index and take corresponding adjustment measures until the deviation index returns to the normal range. This dynamic adjustment mechanism can be optimized and adjusted in real time according to different environmental conditions (such as lighting changes, equipment aging, etc.), avoiding misjudgment or delayed reaction caused by static threshold judgment, and ensuring that the solar tracking equipment can always maintain the best working state.

[0080] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0081] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A sun tracking method based on spot profile detection, characterized in that: The following steps are involved: Acquire the sunlight spot imaging surface data of the sunlight receiving device in real time and perform preprocessing, wherein the sunlight spot imaging surface data includes the pixel value and position coordinates of each pixel point in the aperture imaging surface; Performing identification, detection and analysis on the preprocessed solar spot imaging surface data to obtain solar spot contour area image data, wherein the solar spot area image data includes the pixel value and position coordinates of each solar spot pixel point in the solar spot contour area image; Comprehensively analyze the image data of the solar spot contour area to obtain the spot position deviation index, spot shape distortion index, spot brightness uniformity index, and spot contrast uniformity index of the solar spot contour area; The spot position deviation index, spot shape distortion index, spot brightness uniformity index and spot contrast uniformity index of the sun spot contour area are comprehensively analyzed to obtain the spot comprehensive deviation index of the sun spot contour area. The comprehensive deviation index of the sun spot contour area is judged and analyzed with the preset deviation threshold range; When the comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, the sunlight receiving device is adjusted and analyzed until the comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range.

2. The sun tracking method based on spot profile detection according to claim 1, characterized in that: The specific steps for preprocessing the solar spot imaging surface data of the sunlight receiving device are as follows: Dividing the sunlight spot imaging surface data of the sunlight receiving device into a plurality of sunlight imaging surface area data, and each sunlight imaging surface area data includes a plurality of pixel points; Comprehensively analyze the data of each sunlight imaging surface area to obtain the pixel variance value of each sunlight imaging surface area; The pixel variance value of each sunlight imaging surface area is judged and analyzed with the preset variance threshold interval; If the pixel variance value is within the preset variance threshold range, the pixel retention processing will be adopted in the corresponding sunlight imaging surface area, that is, the pixel value will be retained; If the pixel variance value is outside the preset variance threshold interval and is lower than the preset variance threshold interval lower limit, Gaussian filtering will be applied to the corresponding sunlight imaging surface area; If the pixel variance value is outside the preset variance threshold interval and is higher than the preset upper limit of the variance threshold interval, median filtering will be performed on the corresponding sunlight imaging surface area.

3. The sun tracking method based on spot profile detection according to claim 1, characterized in that: The specific steps of identifying, detecting and analyzing the pre-processed solar spot imaging surface data to obtain the solar spot contour area image data are as follows: Comprehensively analyze the data of each sunlight imaging surface area respectively, obtain the pixel mean value of each sunlight imaging surface area, and mark it as the pixel division threshold of each sunlight imaging surface area; Binarization processing is performed on each sunlight imaging surface area data based on the pixel division threshold to obtain a binary image of each sunlight imaging surface area; The binary image of each sunlight imaging surface area is processed with edge detection and contour extraction to obtain the image data of the sunlight spot contour area.

4. The sun tracking method based on spot profile detection according to claim 1, characterized in that: The specific formula for calculating the comprehensive deviation index of the sun spot contour area is as follows: Among them, ZpL is the comprehensive deviation index of the sun spot contour area, GpL is the spot position deviation index of the sun spot contour area, α1 is the deviation coefficient stored in the database, GsZ is the spot shape distortion index of the sun spot contour area, α2 is the distortion coefficient stored in the database, GjY is the spot brightness uniformity index of the sun spot contour area, α3 is the brightness uniformity coefficient stored in the database, GdB is the spot contrast uniformity index of the sun spot contour area, α4 is the contrast uniformity coefficient stored in the database, α1+α2+α3+α4=1, and e is a natural constant.

5. The sun tracking method based on spot profile detection according to claim 1, characterized in that: The specific steps to obtain the spot position deviation index of the sun spot contour area are as follows: Read the horizontal coordinate value, vertical coordinate value, and pixel value of each spot pixel point in the solar spot contour area image, and perform comprehensive analysis respectively to obtain the geometric center coordinates of the spot, including the center horizontal coordinate value and the center vertical coordinate value; Obtain the reference center coordinates of the solar spot contour area, and perform comprehensive analysis with the geometric center coordinates of the solar spot to obtain the spot position deviation index of the solar spot contour area, wherein the reference center coordinates of the solar spot include a reference center abscissa value and a reference center ordinate value; The specific formula for calculating the central abscissa value and central ordinate value of the geometric center coordinates of the light spot is as follows: Among them, x′ is the central abscissa value of the geometric center coordinate of the light spot, x i is the horizontal coordinate value of the i-th spot pixel point in the sun spot contour area image, XsZ i is the pixel value of the i-th spot pixel in the solar spot contour area image, y′ is the central ordinate value of the spot geometric center coordinate, y i is the ordinate value of the i-th spot pixel in the solar spot contour area image, i=1, 2, 3, ..., i0, i0 is the number of spot pixels in the solar spot contour area image.

6. The sun tracking method based on spot profile detection according to claim 5, characterized in that: The specific formula for calculating the spot position deviation index of the sun spot contour area is as follows: Among them, GpL is the spot position deviation index of the solar spot contour area, x′ is the central horizontal coordinate value of the spot geometric center coordinates, x″ is the reference center horizontal coordinate value of the spot reference center coordinates, y′ is the central vertical coordinate value of the spot geometric center coordinates, y″ is the reference center vertical coordinate value of the spot reference center coordinates, and DjX is the diagonal length of the solar spot contour area.

7. The sun tracking method based on spot profile detection according to claim 1, characterized in that: The specific steps for obtaining the spot shape distortion index of the sun spot contour area are as follows: Count the number of spot pixels in the sun spot contour area image and mark them as the sun spot contour area area value; And count the number of boundary spot pixels in the sun spot contour area image, and mark them as the sun spot contour area perimeter value; Comprehensively analyze the area value and perimeter value of the sun spot contour area to obtain the spot shape distortion index of the sun spot contour area; The specific formula for calculating the spot shape distortion index of the sun spot contour area is as follows: Among them, GsZ is the spot shape distortion index of the sun spot contour area, π is the pi, MjZ is the area value of the sun spot contour area, and ZcZ is the circumference value of the sun spot contour area.

8. The sun tracking method based on spot profile detection according to claim 1, characterized in that: The specific steps to obtain the spot brightness uniformity index of the sun spot contour area are as follows: For each spot pixel in the solar spot contour area image, the number of adjacent spot pixels in a set neighborhood is identified respectively; The pixel value of each spot pixel in the solar spot contour area image is combined with the pixel value of each adjacent spot pixel in the set neighborhood for comprehensive analysis, so as to obtain the spot brightness neighborhood mean value and the spot brightness neighborhood standard deviation value of each spot pixel in the solar spot contour area image; The spot brightness uniformity index of the solar spot contour area is obtained by comprehensively analyzing the spot brightness neighborhood mean and spot brightness neighborhood standard deviation of each spot pixel point in the solar spot contour area image; The specific formulas for calculating the spot brightness neighborhood mean, spot brightness neighborhood standard deviation, and spot brightness uniformity index of the solar spot outline area for each spot pixel in the solar spot outline area image are as follows: Among them, LjZ i is the neighborhood mean of the brightness of the i-th spot pixel in the sun spot contour area image, XsZ i is the pixel value of the i-th spot pixel in the sun spot contour area image, XsZ it is the pixel value of the tth adjacent spot pixel in the set neighborhood of the i-th spot pixel in the solar spot contour area image, LbC i is the standard deviation of the spot brightness neighborhood of the i-th spot pixel in the solar spot contour area image, LjY is the spot brightness uniformity index of the solar spot contour area, i = 1, 2, 3, ..., i0, i0 is the number of spot pixels in the solar spot contour area image, t = 1, 2, 3, ..., t0, t0 is the number of adjacent spot pixels in the set neighborhood.

9. The sun tracking method based on spot profile detection according to claim 1, characterized in that: The specific steps to obtain the spot contrast uniformity index of the sun spot contour area are as follows: Compare and analyze the pixel values ​​of each spot pixel point in the solar spot outline image data to obtain the maximum spot pixel value and the minimum spot pixel value in the solar spot outline image; Comprehensively analyze the maximum spot pixel value and the minimum spot pixel value in the sun spot outline image to obtain the comprehensive contrast index of the sun spot outline area; The solar spot contour image data is divided into a plurality of solar spot contour divided area image data, and each solar spot contour divided area image data includes a plurality of spot pixel points; Compare and analyze the pixel values ​​of each spot pixel point in each solar spot contour divided area image data respectively, and obtain the maximum spot pixel value and the minimum spot pixel value of the divided area in each solar spot contour divided area image; Comprehensively analyze the maximum spot pixel value and the minimum spot pixel value of each sun spot contour divided area in each sun spot contour divided area image to obtain the divided area contrast index of each sun spot contour divided area; The comprehensive contrast index of the sun spot contour area and the contrast index of each divided area of ​​the sun spot contour are comprehensively analyzed to obtain the spot contrast uniformity index of the sun spot contour area: The specific formulas for calculating the comprehensive contrast index of the sun spot contour area, the contrast index of each divided area of ​​the sun spot contour, and the spot contrast uniformity index of the sun spot contour area are as follows: Among them, ZdB is the comprehensive contrast index of the sun spot contour area, XsZ′ Max is the maximum spot pixel value in the sun spot profile image, XsZ′ Min is the minimum spot pixel value in the sun spot profile image, QdB u is the contrast index of the divided area of ​​the u-th sun spot contour divided area, is the maximum spot pixel value of the divided area in the u-th sun spot contour divided area image, is the minimum spot pixel value of the divided area in the u-th sun spot outline divided area image, GdB is the spot contrast uniformity index of the sun spot outline area, u=1.2, 3…, u0, u0 is the number of sun spot outline divided area image data.

10. The sun tracking method based on spot profile detection according to claim 1, characterized in that: When the comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, the steps of adjusting and analyzing the sunlight receiving device until the comprehensive deviation index of the solar spot contour area is within the preset deviation threshold range are as follows: When the comprehensive deviation index of the solar spot contour area is outside the preset deviation threshold range, identifying the abnormal index in the comprehensive deviation index of the solar spot contour area and taking corresponding adjustment measures; And analyze the comprehensive deviation index of the adjusted sun spot contour area, and make judgment and analysis with the preset deviation threshold range; If the adjusted comprehensive deviation index of the sun spot contour area is within the preset deviation threshold range, the adjustment is completed; If the comprehensive deviation index of the adjusted sun spot contour area is outside the preset deviation threshold range, the steps of taking adjustment measures, analyzing the comprehensive deviation index of the adjusted sun spot contour area, and judging and analyzing are repeated until the comprehensive deviation index of the sun spot contour area is within the preset deviation threshold range.

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