Photovoltaic aluminum frame surface defect detection system

Abstract

The invention relates to the technical field of surface defect detection, in particular to a photovoltaic aluminum frame surface defect detection system which comprises a surface defect detection platform, a surface information unit, an image processing unit, a progressive division unit, a defect positioning unit, a defect classification unit and a management display unit. According to the method, the appearance feature image of the photovoltaic aluminum frame to be detected is preliminarily analyzed, so that whether the surface of the photovoltaic aluminum frame to be detected has defect risks or not is known from the perspective of image difference, light source detection defect positioning analysis is carried out in a progressive mode, meanwhile, detection is carried out in a light source detection mode, and the detection accuracy is improved. According to the method, the defect position can be further determined, defect multi-level verification analysis is carried out in an information feedback mode so as to improve the accuracy and effectiveness of the detection result, and the to-be-detected photovoltaic aluminum frame with the defect is divided and managed in the information feedback mode so as to improve the defect processing effect of the subsequent to-be-detected photovoltaic aluminum frame.

Description

Technical Field

[0001] The present invention relates to the technical field of surface defect detection, and in particular to a photovoltaic aluminum frame surface defect detection system. Background Art

[0002] With the rapid development of science and technology, visual image technology has been widely used. As an important part of visual image technology, defect detection system has been comprehensively developed. At present, defect detection system is usually applied to metal surface, glass surface, paper surface, electronic component surface and other items with strict requirements on appearance and clear indicators; The existing method of surface defect detection using machine vision mainly uses a 2D camera or a 3D camera to photograph the surface of the workpiece, and then uses a specific algorithm to determine whether there are defects on the surface of the workpiece based on the acquired image features. However, in the existing technology, it is impossible to accurately analyze the position of surface defects of photovoltaic aluminum frames, resulting in large deviations in the analysis results, and it is impossible to further locate and verify the position of surface defects of photovoltaic aluminum frames, which is not conducive to the subsequent defect management of photovoltaic aluminum frames, and it is impossible to reasonably classify and manage photovoltaic aluminum frames according to the degree of defects, thereby reducing the efficiency of defect management.

[0003] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0004] The purpose of the present invention is to provide a photovoltaic aluminum frame surface defect detection system to solve the above-mentioned technical defects. The present invention preliminarily analyzes the appearance feature image of the photovoltaic aluminum frame to be detected, so as to understand whether there is a defect risk on the surface of the photovoltaic aluminum frame to be detected from the perspective of image difference, so as to provide data support for subsequent analysis, and performs light source detection defect positioning analysis in a progressive manner, and at the same time performs detection by light source detection to further determine the defect location, and performs multi-level defect verification analysis by information feedback to improve the accuracy and effectiveness of the detection results, and divides and manages the defective photovoltaic aluminum frames to be detected by information feedback, that is, performs defect degree division analysis, so as to reasonably and targetedly manage the photovoltaic aluminum frames to be detected according to different defect degrees, so as to improve the subsequent defect processing effect of the photovoltaic aluminum frames to be detected.

[0005] The object of the present invention can be achieved by the following technical solutions: A photovoltaic aluminum frame surface defect detection system, including a surface defect detection platform, a surface information unit, an image processing unit, a progressive division unit, a defect location unit, a defect classification unit and a management display unit; The surface information unit is used to collect the appearance feature image of the photovoltaic aluminum frame to be detected, and send the appearance feature image to the image processing unit; After receiving the appearance feature image, the image processing unit immediately performs image difference screening analysis on the appearance feature image, performs comparison analysis on the obtained suspicious deviation index, and obtains a feedback signal and a marking signal; The progressive division unit is used to respond to the marking signal and immediately perform light source detection defect location analysis, compare and analyze the obtained plane evaluation angle, and obtain a normal signal and a defect signal; The defect location unit is used to respond to the defect signal and immediately perform multi-level defect verification analysis, compare and analyze the obtained defect reflection index, and obtain a location signal; The defect classification unit is used to respond to the positioning signal and immediately perform defect degree classification analysis, compare and analyze the obtained defect depth assessment coefficient Q, and obtain the defect type index QZ.

[0006] Preferably, the image difference screening and analysis process of the image processing unit is as follows: The surface to be detected of the photovoltaic aluminum frame to be detected is obtained, and the surface to be detected of the photovoltaic aluminum frame to be detected is set as the analysis surface, and the analysis surface is divided into h sub-region blocks, where h is a natural number greater than zero. The appearance feature image of each sub-region block is obtained through an image acquisition device, and the appearance feature image is compared with the standard feature image for difference, and then the difference value between the appearance feature image and the standard feature image is obtained, and the difference value between the appearance feature image and the standard feature image is set as a suspicious deviation index, and the suspicious deviation index is discriminated and processed to obtain a feedback signal and a marking signal.

[0007] Preferably, the light source detection defect location analysis process of the progressive division unit is as follows: The sub-region block corresponding to the marking signal is set as a suspicious sub-region, and i detection points are set on the suspicious sub-region, where i is a natural number greater than zero. The spatial coordinates of each detection point are obtained, and the detection light source is adjusted according to the spatial coordinates to reach the preset detection position, and then the detection points are illuminated and detected in turn by the light source, and the detection light source is controlled to illuminate the detection point at a first set angle, so as to obtain the maximum reflection angle and the minimum reflection angle formed by the reflected light and the plane where the detection point on the photovoltaic aluminum frame to be detected is located, and the difference between the maximum reflection angle and the minimum reflection angle formed by the reflected light and the plane where the detection point on the photovoltaic aluminum frame to be detected is located is set as the plane evaluation angle, and the plane evaluation angle is compared and analyzed with the preset plane evaluation angle threshold value recorded and stored internally to obtain normal signals and defective signals.

[0008] Preferably, the defect multi-level verification and analysis process of the defect location unit is as follows: The detection point corresponding to the defect signal is obtained and set as the suspected detection point. At the same time, the preset detection position corresponding to the suspected detection point is obtained and set as the position to be adjusted. The angle formed by the line between the suspected detection point and the position to be adjusted and the analysis surface is obtained, and set as the detected angle. Then the degree of the detected angle is adjusted g times, where g is a natural number greater than zero. The maximum reflection angle and the minimum reflection angle formed by each reflected light after the detection light source is adjusted and the plane where the detection point on the photovoltaic aluminum frame to be detected is located are obtained, and the difference between the maximum reflection angle and the minimum reflection angle formed by each reflected light after the detection light source is adjusted and the plane where the detection point on the photovoltaic aluminum frame to be detected is located is set as the reflection deviation degree, and the reflection deviation degree is compared and analyzed with the preset reflection deviation degree threshold value recorded and stored internally, and the ratio between the number of adjustments corresponding to the reflection deviation degree being greater than the preset reflection deviation degree threshold and the number of adjustments corresponding to the reflection deviation degree being less than or equal to the preset reflection deviation degree threshold is set as the defect reflection index.

[0009] Preferably, the defect reflection index is compared and analyzed with a preset defect reflection index threshold value recorded and stored internally: If the ratio between the defect reflection index and the preset defect reflection index threshold is less than 1, no signal is generated; if the ratio between the defect reflection index and the preset defect reflection index threshold is greater than or equal to 1, a positioning signal is generated.

[0010] Preferably, the defect degree classification and analysis process of the defect classification unit is as follows: The defect reflection index corresponding to the positioning signal is obtained, and the part of the defect reflection index greater than the preset defect reflection index threshold is set as the defect depth value. At the same time, the suspicious deviation index is called from the image processing unit, and the defect depth value and the suspicious deviation index are labeled QS and KP respectively. The defect depth value QS and the suspicious deviation index KP are substituted into the formula to obtain the defect depth assessment coefficient Q.

[0011] Preferably, the defect depth assessment coefficient Q is compared and analyzed with a preset defect depth assessment coefficient range stored internally: If the defect depth assessment coefficient Q is greater than the maximum value in the preset defect depth assessment coefficient range, a Class I defect is determined; if the defect depth assessment coefficient Q belongs to the preset defect depth assessment coefficient range, a Class II defect is determined; if the defect depth assessment coefficient Q is less than the minimum value in the preset defect depth assessment coefficient range, a Class III defect is determined, and Class I defects, Class II defects and Class III defects are set as defect type index QZ, QZ=1, 2, 3.

[0012] The beneficial effects of the present invention are as follows: The present invention analyzes the appearance feature image of the photovoltaic aluminum frame to be detected preliminarily, so as to understand whether there is a defect risk on the surface of the photovoltaic aluminum frame to be detected from the perspective of image difference, so as to provide data support for subsequent analysis, and performs light source detection defect location analysis in a progressive manner, and at the same time performs detection by light source detection, so as to further determine the defect location; The present invention performs multi-level defect verification and analysis by means of information feedback, so as to perform in-depth defect detection by changing the position of the detection light source, so as to improve the accuracy and effectiveness of the detection result, and at the same time help to accurately and intuitively understand the defective parts of the analysis surface, and help to improve the efficiency of surface defect detection of photovoltaic aluminum frames. By means of information feedback, photovoltaic aluminum frames to be detected with defects are divided and managed, that is, defect degree division analysis is performed, so that the photovoltaic aluminum frames to be detected can be reasonably and targetedly managed according to different defect degrees, so as to improve the subsequent defect processing effect of the photovoltaic aluminum frames to be detected. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention will be further described below in conjunction with the accompanying drawings; Figure 1 It is a flowchart of the system of the present invention; Figure 2 It is a local analysis reference diagram of the first embodiment of the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Embodiment 1:

[0015] See also Figure 1 to Figure 2 As shown, the present invention is a photovoltaic aluminum frame surface defect detection system, including a surface defect detection platform, a surface information unit, an image processing unit, a progressive division unit, a defect positioning unit, a defect classification unit and a management display unit, the surface defect detection platform is connected to the surface information unit in a one-way communication, the surface information unit is connected to the image processing unit in a one-way communication, the image processing unit is connected to the progressive division unit and the management display unit in a one-way communication, the progressive division unit is connected to the defect positioning unit and the management display unit in a one-way communication, the defect positioning unit is connected to the defect classification unit and the management display unit in a one-way communication, and the defect classification unit is connected to the management display unit in a one-way communication; When the surface defect detection platform generates an operation and management instruction, the operation and management instruction is sent to the surface information unit. When the surface information unit receives the operation and management instruction, it immediately collects the appearance feature image of the photovoltaic aluminum frame to be detected, and sends the appearance feature image to the image processing unit. After receiving the appearance feature image, the image processing unit immediately performs image difference screening and analysis on the appearance feature image, so as to perform a preliminary analysis from the perspective of image difference to understand whether there is a defect risk on the surface of the photovoltaic aluminum frame to be detected. The specific image difference screening and analysis process is as follows: The surface to be detected of the photovoltaic aluminum frame to be detected is obtained, and the surface to be detected of the photovoltaic aluminum frame to be detected is set as the analysis surface, and the analysis surface is divided into h sub-region blocks, where h is a natural number greater than zero. The appearance feature image of each sub-region block is obtained through an image acquisition device, and the appearance feature image is compared with the standard feature image for difference, thereby obtaining the difference value between the appearance feature image and the standard feature image, and the difference value between the appearance feature image and the standard feature image is set as the suspicious deviation index, and the suspicious deviation index is discriminated: If the suspicious deviation index is less than or equal to the preset suspicious deviation index threshold, a feedback signal is generated and sent to the management display unit. After receiving the feedback signal, the management display unit immediately displays the preset warning text corresponding to the feedback signal to understand the preliminary analysis situation of the analysis surface; If the suspicious deviation index is greater than a preset suspicious deviation index threshold, a marking signal is generated; When a marking signal is generated, the progressive division unit is used to respond to the marking signal and immediately perform light source detection defect location analysis to further determine the defect location. The specific light source detection defect location analysis process is as follows: The line connecting the midpoints of the two long sides of the detection workbench is taken as the Y axis, the line connecting the midpoints of the two short sides of the detection workbench is taken as the X axis, the intersection point between the line connecting the midpoints of the two long sides of the detection workbench and the line connecting the midpoints of the two short sides is set as point O, and the ray starting from point O and perpendicular to point O is set as the Z axis, thereby constructing a spatial coordinate system; In the embodiment of the present invention, the detection workbench is rectangular; The sub-region block corresponding to the marking signal is set as a suspicious sub-region, i detection points are set on the suspicious sub-region, i is a natural number greater than zero, the spatial coordinates of each detection point are obtained, and the detection light source is adjusted according to the spatial coordinates to reach the preset detection position, and then the detection points are illuminated and detected in turn, and the detection light source is controlled to illuminate the detection point at a first set angle, and then the maximum reflection angle and the minimum reflection angle formed by the reflected light and the plane where the detection point on the photovoltaic aluminum frame to be detected is located are obtained, and the difference between the maximum reflection angle and the minimum reflection angle formed by the reflected light and the plane where the detection point on the photovoltaic aluminum frame to be detected is located is set as the plane evaluation angle, and the plane evaluation angle is compared and analyzed with the preset plane evaluation angle threshold value recorded and stored internally: If the ratio between the plane evaluation angle and the preset plane evaluation angle threshold is less than 1, a normal signal is generated and sent to the management display unit. After receiving the normal signal, the management display unit immediately displays the preset warning text corresponding to the normal signal, so as to accurately understand whether there are defects on the analyzed surface; If the ratio between the plane evaluation angle and the preset plane evaluation angle threshold is greater than or equal to 1, a defect signal is generated; In the embodiment of the present invention, the detection light source adopts a linear array light source, and the image acquisition device acquires an SK linear array camera; In the embodiment of the present invention, the spatial coordinates of each monitoring point are different, and the preset detection positions of the detection light source and the image acquisition device are different, that is, each monitoring point corresponds to each preset detection position; In the embodiment of the present invention, the larger the value of the plane evaluation angle is, the greater the risk of diffuse reflection is, and the greater the risk of defects on the analyzed surface is. The plane evaluation angle is an influencing parameter that reflects the risk of diffuse reflection state. Embodiment 2:

[0016] When a defect signal is generated, the defect location unit is used to respond to the defect signal and immediately perform multi-level defect verification and analysis, so as to perform in-depth detection by changing the position of the detection light source to improve the accuracy and effectiveness of the detection results. The specific multi-level defect verification and analysis process is as follows: The detection point corresponding to the defect signal is obtained, and it is set as the suspected detection point. At the same time, the preset detection position corresponding to the suspected detection point is obtained, and it is set as the position to be adjusted. The angle formed by the line between the suspected detection point and the position to be adjusted and the analysis surface is obtained, and it is set as the detected angle, and then the degree of the detected angle is adjusted g times, where g is a natural number greater than zero. The maximum reflection angle and the minimum reflection angle formed by each reflected light after the detection light source is adjusted and the plane where the detection point on the photovoltaic aluminum frame to be detected is located are obtained, and the difference between the maximum reflection angle and the minimum reflection angle formed by each reflected light after the detection light source is adjusted and the plane where the detection point on the photovoltaic aluminum frame to be detected is located is set as the reflection deviation degree, and the reflection deviation degree is compared and analyzed with the preset reflection deviation degree threshold value recorded and stored internally, and the ratio between the number of adjustments corresponding to the reflection deviation degree greater than the preset reflection deviation degree threshold and the number of adjustments corresponding to the reflection deviation degree less than or equal to the preset reflection deviation degree threshold is set as the defect reflection index, and the defect reflection index is compared and analyzed with the preset defect reflection index threshold value recorded and stored internally: If the ratio between the defect reflection index and the preset defect reflection index threshold is less than 1, no signal is generated; If the ratio between the defect reflection index and the preset defect reflection index threshold is greater than or equal to 1, a positioning signal is generated and sent to the management display unit. After receiving the positioning signal, the management display unit immediately displays the spatial coordinates of the suspicious detection point corresponding to the positioning signal, so as to accurately and intuitively understand the defective parts of the analysis surface, thereby helping to improve the accuracy and reliability of photovoltaic aluminum frame surface defect detection, and at the same time help to improve the efficiency of photovoltaic aluminum frame surface defect detection; In the embodiment of the present invention, the degree of the detected angle g times is adjusted, and the adjusted angle is adjusted in sequence according to the set angle parameter, so as to realize that the detection light source detects the suspicious detection point from different angles. For example, if the detected angle is 30°, according to the first set angle parameter +15°, the corresponding detection light source position is adjusted to illuminate the detection at 45°, and the detection is performed again; if the detected angle is 30°, according to the first set angle parameter -15°, the corresponding detection light source position is adjusted to illuminate the detection at 15°; When a positioning signal is generated, the defect classification unit is used to respond to the positioning signal and immediately perform defect degree classification analysis, so as to perform reasonable and targeted management on the photovoltaic aluminum frame to be inspected according to different defect degrees, so as to improve the subsequent defect treatment effect of the photovoltaic aluminum frame to be inspected. The specific defect degree classification analysis process is as follows: Obtain the defect reflection index corresponding to the positioning signal, set the part of the defect reflection index greater than the preset defect reflection index threshold as the defect depth value, and at the same time retrieve the suspicious deviation index from the image processing unit, label the defect depth value and the suspicious deviation index as QS and KP respectively, and substitute the defect depth value QS and the suspicious deviation index KP into the formula The defect depth assessment coefficient is obtained, where a1 and a2 are preset proportional factor coefficients of the defect depth value and the suspicious deviation index respectively. The proportional factor coefficient is used to correct the deviation of various parameters in the formula calculation process, so as to make the calculation result more accurate. a3 is the preset error correction factor coefficient. a1, a2 and a3 are all greater than zero. Q is the defect depth assessment coefficient. The defect depth assessment coefficient Q is compared and analyzed with the preset defect depth assessment coefficient range stored internally: If the defect depth assessment coefficient Q is greater than the maximum value in the preset defect depth assessment coefficient range, a type of defect is determined; If the defect depth assessment coefficient Q falls within the preset defect depth assessment coefficient range, a Class II defect is determined; If the defect depth assessment coefficient Q is less than the minimum value in the preset defect depth assessment coefficient range, three types of defects are determined, wherein the defect degrees corresponding to the first type of defects, the second type of defects and the third type of defects are successively reduced, and the first type of defects, the second type of defects and the third type of defects are set as defect type indexes QZ, QZ=1, 2, 3, that is, the defect type index QZ=1 indicates a first type of defect, the defect type index QZ=2 indicates a second type of defect, and the defect type index QZ=3 indicates a third type of defect, and the defect type index QZ is sent to the management display unit. After receiving the defect type index QZ, the management display unit immediately displays the preset warning text corresponding to the defect type index QZ, so as to classify and manage the photovoltaic aluminum frame to be detected according to the feedback information, so as to reasonably perform subsequent repair management on the different defect degrees of the photovoltaic aluminum frame to be detected, so as to improve the defect management efficiency of the photovoltaic aluminum frame to be detected; To summarize, the present invention preliminarily analyzes the appearance feature image of the photovoltaic aluminum frame to be inspected, so as to understand whether there is a defect risk on the surface of the photovoltaic aluminum frame to be inspected from the perspective of image difference, so as to provide data support for subsequent analysis, and performs light source detection defect positioning analysis in a progressive manner, and at the same time, performs detection by light source detection to further determine the defect position, and performs multi-level defect verification analysis by information feedback, so as to perform in-depth defect detection by changing the position of the detection light source, so as to improve the accuracy and effectiveness of the detection results, and at the same time help to accurately and intuitively understand the defective parts of the analysis surface, and help to improve the efficiency of photovoltaic aluminum frame surface defect detection, and divide and manage the defective photovoltaic aluminum frames to be inspected by information feedback, that is, perform defect degree division analysis, so as to reasonably and targetedly manage the photovoltaic aluminum frames to be inspected according to different defect degrees, so as to improve the subsequent defect processing effect of the photovoltaic aluminum frames to be inspected.

[0017] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0018] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A photovoltaic aluminum frame surface defect detection system, characterized in that: It includes a surface defect detection platform, a surface information unit, an image processing unit, a progressive division unit, a defect location unit, a defect classification unit and a management display unit; The surface information unit is used to collect the appearance feature image of the photovoltaic aluminum frame to be detected, and send the appearance feature image to the image processing unit; After receiving the appearance feature image, the image processing unit immediately performs image difference screening analysis on the appearance feature image, performs comparison analysis on the obtained suspicious deviation index, and obtains a feedback signal and a marking signal; The progressive division unit is used to respond to the marking signal and immediately perform light source detection defect location analysis, compare and analyze the obtained plane evaluation angle, and obtain a normal signal and a defect signal; The defect location unit is used to respond to the defect signal and immediately perform multi-level defect verification analysis, compare and analyze the obtained defect reflection index, and obtain a location signal; The defect classification unit is used to respond to the positioning signal and immediately perform defect degree classification analysis, compare and analyze the obtained defect depth assessment coefficient Q, and obtain the defect type index QZ.

2. A photovoltaic aluminum frame surface defect detection system according to claim 1, characterized in that: The image difference screening and analysis process of the image processing unit is as follows: The surface to be detected of the photovoltaic aluminum frame to be detected is obtained, and the surface to be detected of the photovoltaic aluminum frame to be detected is set as the analysis surface, and the analysis surface is divided into h sub-region blocks, where h is a natural number greater than zero. The appearance feature image of each sub-region block is obtained through an image acquisition device, and the appearance feature image is compared with the standard feature image for difference, and then the difference value between the appearance feature image and the standard feature image is obtained, and the difference value between the appearance feature image and the standard feature image is set as a suspicious deviation index, and the suspicious deviation index is discriminated and processed to obtain a feedback signal and a marking signal.

3. A photovoltaic aluminum frame surface defect detection system according to claim 1, characterized in that: The light source detection defect location analysis process of the progressive division unit is as follows: The sub-region block corresponding to the marking signal is set as a suspicious sub-region, and i detection points are set on the suspicious sub-region, where i is a natural number greater than zero. The spatial coordinates of each detection point are obtained, and the detection light source is adjusted according to the spatial coordinates to reach the preset detection position, and then the detection points are illuminated and detected in turn by the light source, and the detection light source is controlled to illuminate the detection point at a first set angle, so as to obtain the maximum reflection angle and the minimum reflection angle formed by the reflected light and the plane where the detection point on the photovoltaic aluminum frame to be detected is located, and the difference between the maximum reflection angle and the minimum reflection angle formed by the reflected light and the plane where the detection point on the photovoltaic aluminum frame to be detected is located is set as the plane evaluation angle, and the plane evaluation angle is compared and analyzed with the preset plane evaluation angle threshold value recorded and stored internally to obtain normal signals and defective signals.

4. A photovoltaic aluminum frame surface defect detection system according to claim 1, characterized in that: The defect multi-level verification and analysis process of the defect location unit is as follows: The detection point corresponding to the defect signal is obtained and set as the suspected detection point. At the same time, the preset detection position corresponding to the suspected detection point is obtained and set as the position to be adjusted. The angle formed by the line between the suspected detection point and the position to be adjusted and the analysis surface is obtained, and set as the detected angle. Then the degree of the detected angle is adjusted g times, where g is a natural number greater than zero. The maximum reflection angle and the minimum reflection angle formed by each reflected light after the detection light source is adjusted and the plane where the detection point on the photovoltaic aluminum frame to be detected is located are obtained, and the difference between the maximum reflection angle and the minimum reflection angle formed by each reflected light after the detection light source is adjusted and the plane where the detection point on the photovoltaic aluminum frame to be detected is located is set as the reflection deviation degree, and the reflection deviation degree is compared and analyzed with the preset reflection deviation degree threshold value recorded and stored internally, and the ratio between the number of adjustments corresponding to the reflection deviation degree being greater than the preset reflection deviation degree threshold and the number of adjustments corresponding to the reflection deviation degree being less than or equal to the preset reflection deviation degree threshold is set as the defect reflection index.

5. A photovoltaic aluminum frame surface defect detection system according to claim 4, characterized in that: Compare and analyze the defect reflection index with the preset defect reflection index threshold value recorded and stored internally: If the ratio between the defect reflection index and the preset defect reflection index threshold is less than 1, no signal is generated; if the ratio between the defect reflection index and the preset defect reflection index threshold is greater than or equal to 1, a positioning signal is generated.

6. A photovoltaic aluminum frame surface defect detection system according to claim 1, characterized in that: The defect degree classification and analysis process of the defect classification unit is as follows: The defect reflection index corresponding to the positioning signal is obtained, and the part of the defect reflection index greater than the preset defect reflection index threshold is set as the defect depth value. At the same time, the suspicious deviation index is called from the image processing unit, and the defect depth value and the suspicious deviation index are labeled QS and KP respectively. The defect depth value QS and the suspicious deviation index KP are substituted into the formula to obtain the defect depth assessment coefficient Q.

7. A photovoltaic aluminum frame surface defect detection system according to claim 5, characterized in that: The defect depth assessment coefficient Q is compared and analyzed with the preset defect depth assessment coefficient range stored internally: If the defect depth assessment coefficient Q is greater than the maximum value in the preset defect depth assessment coefficient range, a type of defect is determined; If the defect depth assessment coefficient Q falls within the preset defect depth assessment coefficient range, a Class II defect is determined; If the defect depth assessment coefficient Q is less than the minimum value in the preset defect depth assessment coefficient range, three types of defects are determined, and the first type of defects, the second type of defects and the third type of defects are set as the defect type index QZ, QZ=1, 2, 3.

Images