A surface detection method for energy-saving and environmentally friendly aluminum curtain walls based on machine vision

Abstract

The present invention relates to the field of industrial detection technology, and in particular to a surface detection method for energy-saving and environmentally friendly aluminum curtain walls based on machine vision. The method can eliminate shadows and reduce misjudgments in surface detection by illuminating the aluminum curtain wall. At the same time, the method obtains image information of the aluminum curtain wall in real time and performs image preprocessing on the obtained image information, which can effectively reflect the defect boundary in real time, thereby accurately determining the defect area of ​​the aluminum curtain wall. At the same time, by dividing the detected aluminum curtain wall into a number of partitions with the same area, and determining the reason why the curtain wall does not meet the standards based on the results of periodic detection of the area ratio of each partition and generating a corresponding processing method, the method can effectively avoid the influence of preprocessing or irradiation light on the surface detection of the aluminum curtain wall during the image acquisition process, thereby effectively reducing misjudgments when detecting the aluminum curtain wall, thereby further improving the accuracy of aluminum curtain wall detection, and further improving the efficiency of curtain wall detection.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial detection, and in particular to a surface detection method for an energy-saving and environmentally friendly aluminum plate curtain wall based on machine vision. Background Art

[0002] Energy-saving and environmentally friendly aluminum curtain walls are a modern building exterior material. Combining the durability of aluminum with its energy-saving and environmentally friendly properties, they have become an important choice in modern architectural design. However, research on the detection of surface corrosion is currently limited.

[0003] Chinese patent publication number CN118332292B discloses a surface inspection method for energy-saving and environmentally friendly aluminum curtain walls based on machine vision, including: obtaining a set of steel material types; obtaining a set of steel corrosion materials; forming steel corrosion categories; obtaining an alternative set; sorting and numbering alternative inspection solutions in the alternative set; forming a corrosion database and data analysis classification for the alternative inspection solutions; identifying the material type and corrosion type of the steel to be inspected; obtaining the lowest-numbered alternative inspection solution in the alternative set corresponding to the characteristic steel corrosion category as the characteristic alternative inspection solution; analyzing the data to be analyzed using the corrosion database and data analysis classification corresponding to the characteristic alternative inspection solution; and re-sorting and numbering the alternative inspection solutions in the updated alternative set. By constructing an alternative set, matching the optimal inspection solution, and updating the existing data, steel corrosion detection can be continuously optimized.

[0004] It can be seen that the above scheme has the following problems: the scheme cannot analyze the reasons why the surface inspection results do not meet the standards due to other factors other than the material itself, and there is no periodic inspection of the curtain wall to make the reasons for non-compliance with the standards detected more accurate, thereby failing to effectively reduce the occurrence of misjudgments when inspecting aluminum curtain walls, and thus failing to further improve the accuracy of aluminum curtain wall inspection, and failing to further improve the efficiency of curtain wall inspection. Summary of the Invention

[0005] To this end, the present invention provides a surface detection method for energy-saving and environmentally friendly aluminum plate curtain walls based on machine vision, which is used to overcome the problem in the prior art that it is unable to analyze the reasons why the surface detection results do not meet the standards for other reasons other than the curtain wall itself, thereby failing to reduce the misjudgment of the surface not meeting the standards, and further failing to ensure the accuracy of the surface detection of the aluminum plate curtain wall.

[0006] To achieve the above objectives, the present invention provides a surface detection method for energy-saving and environmentally friendly aluminum curtain walls based on machine vision, comprising:

[0007] Polish the aluminum curtain wall to eliminate shadows on its surface;

[0008] Acquiring image information of the surface of the aluminum curtain wall in real time;

[0009] Preprocessing the image information;

[0010] Based on the preprocessed image information, the image information is detected using the YOLOv5 model to obtain defect features in the image information;

[0011] Dividing the preprocessed image information into a plurality of partitions of equal area, and calculating the area ratio in each partition, wherein the area ratio is the ratio of the area of ​​the defect feature in a single partition to the area of ​​the corresponding partition;

[0012] Based on the obtained area ratios, it is determined whether the aluminum curtain wall meets the standards. When it is determined that the aluminum curtain wall does not meet the standards, a corresponding treatment method is generated based on the determined reason for not meeting the standards, including issuing an anti-corrosion treatment notice and redetermining corresponding detection parameters.

[0013] Furthermore, the process of determining whether the aluminum plate curtain wall meets the standard based on the obtained area ratios includes: calculating the average value of each area ratio, and determining whether the aluminum plate curtain wall meets the standard based on the comparison result of the obtained average value and the pre-stored preset area ratio, wherein: if the average value is less than or equal to the first preset average value, the aluminum plate curtain wall is determined to meet the standard; if the average value is greater than the first preset average value and less than the second preset average value, whether the aluminum plate curtain wall meets the standard is determined based on the variance of each area ratio; if the average value is greater than or equal to the second preset average value, the aluminum plate curtain wall is determined to not meet the standard, and the reason why the aluminum plate curtain wall does not meet the standard is determined based on the difference between the average value and the second preset average value.

[0014] Furthermore, the process of determining whether the aluminum plate curtain wall meets the standard based on the variance of each of the area ratios includes: comparing the obtained variance with a preset variance; if the variance is less than or equal to the preset variance, determining that the acquisition process of the image information does not meet the standard, and re-determining the detection parameters in the image acquisition process based on the obtained variance value; if the variance is greater than the preset variance, determining that the curtain wall does not meet the standard, and determining the reason for non-compliance based on the difference between the average value and the second preset average value.

[0015] Furthermore, the process of re-determining the detection parameters in the image acquisition process based on the variance value includes: obtaining the difference between the variance and the preset variance; increasing the illumination light intensity based on the obtained difference, and the difference is proportional to the increase in the illumination light intensity.

[0016] Furthermore, the process of determining the reason why the aluminum plate curtain wall does not meet the standard based on the difference between the average value and the second preset average value includes: determining whether the aluminum plate curtain wall is corroded based on the comparison result of the difference between the average value and the second preset average value and the pre-stored preset difference, wherein: if the difference is less than or equal to the first preset difference, it is determined that the aluminum plate curtain wall is corroded; if the difference is greater than the first preset difference and less than the second preset difference, it is determined whether the aluminum plate curtain wall is corroded based on the average value of the clarity of the boundaries of each defect feature; if the difference is greater than or equal to the second preset difference, it is determined whether the aluminum plate curtain wall is corroded based on the secondary ratio; wherein: the secondary ratio is the ratio of the average value of the area ratio in the current test result to the average value of the area ratio in the previous test result.

[0017] Furthermore, the process of determining whether the aluminum curtain wall is corroded based on the average clarity value of the boundaries of each defect feature includes: comparing the average clarity value with a preset average clarity value; if the average clarity value is less than or equal to the preset average clarity value, determining that the preprocessing process for the image information does not meet the standard, and re-determining preprocessing parameters based on the difference between the average clarity value and the preset average clarity value; wherein: the detection parameters include the preprocessing parameters. If the average clarity value is greater than the preset average clarity value, determining that the aluminum curtain wall is corroded and issuing an anti-corrosion treatment notice.

[0018] Furthermore, the process of redetermining the preprocessing parameters based on the difference between the average clarity value and the preset average clarity value includes: increasing the noise reduction ratio based on the difference between the clarity value and the preset clarity value, and the difference is proportional to the noise reduction ratio; wherein: the preprocessing parameters include (noise reduction ratio, grayscale transformation parameters).

[0019] Furthermore, the process of determining whether the aluminum curtain wall is corroded based on the secondary ratio includes:

[0020] The secondary ratio is compared with a preset secondary ratio; if the secondary ratio is less than or equal to the preset secondary ratio, it is determined that the aluminum curtain wall is corroded, and an anti-corrosion treatment notice is issued; if the secondary ratio is greater than the preset secondary ratio, it is determined that there is a problem with the illumination angle, and the illumination angle is re-determined based on the difference between the secondary ratio and the preset secondary ratio; wherein: the illumination angle is the angle between the line connecting the illumination point and the aluminum curtain wall and the line connecting the image acquisition point and the aluminum curtain wall; the detection parameters include the illumination angle.

[0021] Furthermore, the process of redetermining the illumination angle based on the difference between the secondary ratio and the preset secondary ratio includes: reducing the illumination angle based on the difference, and the difference is inversely proportional to the reduction range of the illumination angle.

[0022] Furthermore, the process of re-determining the illumination light intensity based on the illumination angle includes: reducing the illumination light intensity based on the illumination angle, and the angle is inversely proportional to the reduction amplitude of the illumination light intensity; wherein: the detection parameter includes the illumination light intensity.

[0023] Compared with the prior art, the beneficial effect of the present invention is that, by illuminating the aluminum plate curtain wall, the present invention can eliminate shadows and reduce misjudgment of its surface detection. At the same time, the image information of the aluminum plate curtain wall is acquired in real time and the acquired image information is preprocessed, which can effectively reflect the defect boundary in real time, thereby accurately determining the defect area of ​​the aluminum plate curtain wall. At the same time, by dividing the detected aluminum plate curtain wall into several partitions of the same area, and determining the reason why the curtain wall does not meet the standards through the results of periodic detection based on the area ratio of each partition and generating a corresponding processing method, the influence of preprocessing or irradiation light on the surface detection of the aluminum plate curtain wall during the image acquisition process can be effectively avoided, thereby effectively reducing the misjudgment when detecting the aluminum plate curtain wall, thereby further improving the accuracy of aluminum plate curtain wall detection, and further improving the efficiency of curtain wall detection.

[0024] Furthermore, the present invention determines whether the surface of the aluminum plate curtain wall meets the standards through the average value of each area ratio, and preliminarily determines the reason for not meeting the standards. This can more quickly determine whether the surface of the aluminum plate curtain wall meets the standards, thereby further improving the efficiency of determining whether the surface of the aluminum plate curtain wall is standard.

[0025] Furthermore, the present invention generates a corresponding processing method by comparing the variance of each area ratio with a preset variance. Based on the fluctuation of the area ratio at multiple moments, it can more accurately determine the reason why the surface of the aluminum curtain wall does not meet the standards and make adjustments, thereby further improving the accuracy of surface detection of the aluminum curtain wall.

[0026] Furthermore, the present invention adjusts the brightness of the illumination light by the difference between the variance of each of the area ratios and the preset variance, thereby further avoiding the problem of inaccurate surface detection of the aluminum curtain wall due to the brightness of the illumination light, and further improving the detection accuracy of the aluminum curtain wall surface.

[0027] Furthermore, the present invention determines whether the aluminum curtain wall is corroded by the difference between the actual area ratio and the second preset average value, and preliminarily analyzes the cause of the corrosion. It can more quickly analyze whether the aluminum curtain wall is corroded, thereby further improving the detection efficiency of the aluminum curtain wall surface.

[0028] Furthermore, the present invention analyzes the comparison results of the average clarity of the boundary of the corrosion position at the same moment with the preset clarity, and can more accurately determine whether the corrosion is detected due to improper setting of the preprocessing parameters of the image information, thereby further improving the detection accuracy of the aluminum plate curtain wall surface.

[0029] Furthermore, the present invention adjusts the noise reduction ratio based on the difference between the clarity and the preset clarity, thereby being able to more accurately adjust the noise reduction ratio, thereby more accurately performing image preprocessing, and further improving the detection accuracy of the aluminum curtain wall surface.

[0030] Furthermore, the present invention analyzes the comparison results based on the ratio of the area ratio in the detection result at the current moment to the area ratio in the detection result at the previous moment and the preset ratio, so as to more accurately determine whether the aluminum curtain wall is corroded during detection due to the problem of light irradiation angle, thereby further improving the detection accuracy of the aluminum curtain wall surface.

[0031] Furthermore, the present invention adjusts the angle based on the ratio of the area ratio in the detection result at the current moment to the area ratio in the detection result at the previous moment and a preset ratio, which can more accurately adjust the angle, thereby further avoiding the occurrence of corrosion detection due to inappropriate angle size, thereby further improving the detection accuracy of the aluminum plate curtain wall surface.

[0032] Furthermore, the present invention adjusts the intensity of the irradiated light based on the angle, which can avoid the influence of reflection during direct irradiation and save resources, thereby further improving the detection accuracy of the aluminum curtain wall surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a module schematic diagram of a surface detection system for energy-saving and environmentally friendly aluminum curtain walls based on machine vision according to an embodiment of the present invention;

[0034] Figure 2 This is a flowchart of the steps of a surface detection method for energy-saving and environmentally friendly aluminum curtain wall based on machine vision according to an embodiment of the present invention;

[0035] Figure 3 A flowchart of the steps for determining the result of comparing the average value of a plurality of area ratios at the same time with a preset area ratio according to an embodiment of the present invention;

[0036] Figure 4 This is a flow chart of the steps of determining based on the variance of the area ratio at the same time and the preset variance according to an embodiment of the present invention;

[0037] Figure 5 This is a flowchart of the steps of determining the difference between the actual area ratio and the second preset average value and the preset difference according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0039] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0040] See also Figure 1 , which is a module schematic diagram of a surface detection system for energy-saving and environmentally friendly aluminum curtain wall based on machine vision according to an embodiment of the present invention;

[0041] A lighting unit for lighting the aluminum curtain wall to eliminate shadows on its surface;

[0042] An image acquisition unit, connected to the lighting unit, for acquiring image information of the curtain wall surface;

[0043] an image processing unit connected to the image acquisition unit and configured to pre-process image information;

[0044] a feature extraction unit connected to the image processing unit, configured to obtain defect features of the pre-processed image information and perform partitioning processing on the pre-processed image information;

[0045] an analysis unit connected to the feature extraction unit, configured to determine whether the curtain wall meets the standards based on the acquired defect features, and to determine the reasons for non-compliance with the standards based on the determination results, and to generate corresponding instructions according to the reasons;

[0046] The processing unit is connected to the analyzing unit and is used to issue an anti-corrosion treatment notification based on the received instruction, or to redetermine the corresponding detection parameters.

[0047] Specifically, in this embodiment, the lighting unit and the image acquisition unit are both fixed on the guide rail. The position of the lighting unit on the guide rail is adjusted to achieve the illumination angle between the lighting unit and the image acquisition unit. The background transmits the image information obtained by the image acquisition unit to the image processing unit, performs noise reduction and other preprocessing operations on it, and inputs the preprocessed image information into the feature extraction unit, uses the YOLOv5 model to extract features, obtains the defect features of the image information, and divides it into multiple partitions of the same area. Subsequently, the multiple partitions will be periodically inspected to analyze the reasons why the curtain wall does not meet the standards, and generates corresponding instructions or redefines the inspection parameters based on the reasons. The inspection parameters include preprocessing parameters (noise reduction ratio, grayscale transformation parameters), the illumination angle of the lighting unit, and the illumination light intensity.

[0048] See also Figure 2 As shown, it is a flow chart of the steps of the surface detection method of the energy-saving and environmentally friendly aluminum plate curtain wall based on machine vision in an embodiment of the present invention.

[0049] The steps in the actual operation process of the system of the embodiment of the present invention include:

[0050] S1, the lighting unit illuminates the aluminum curtain wall;

[0051] S2, the image acquisition unit acquires image information of the surface of the aluminum curtain wall in real time;

[0052] S3, the image processing unit performs image preprocessing on the image information;

[0053] S4, the feature extraction unit detects the image information using the YOLOv5 model based on the image information after image preprocessing, obtains the corrosion position on the surface of the aluminum curtain wall, and detects the clarity of the boundary of the corrosion position;

[0054] S5, the analyzing unit divides the aluminum curtain wall at each moment into a plurality of partitions of equal area, and calculates the area ratio of the area of ​​the corroded portion in each partition to the area of ​​the corresponding partition;

[0055] S6, the analyzing unit further determines whether the aluminum curtain wall meets the standards based on the several area ratios at the same time, and analyzes the reasons why the aluminum curtain wall surface does not meet the standards according to the determination results.

[0056] Specifically, the aluminum curtain wall is first illuminated, and the main operation is to select a suitable light source type (such as natural light, artificial light, point light source, parallel light source, etc.), and determine the position, angle and intensity of the light source to control shadows, highlights and overall brightness. Secondly, an industrial camera is used to capture images of the illuminated aluminum curtain wall, and then the captured image information is preprocessed, which includes grayscale processing and noise reduction operations. Then, the preprocessed image information is input into the trained YOLOV5 model for detection. The output detection result is the corrosion position on the surface of the aluminum curtain wall, and the boundary of the corrosion position is detected using a clarity tester. Then, the aluminum curtain wall is divided into several partitions of the same area, and the ratio of the area of ​​the corroded part in each partition to the area of ​​the corresponding partition is calculated respectively. Finally, based on these ratios, it is judged whether the surface of the aluminum curtain wall does not meet the standards, and a preliminary analysis is made of the reasons why the aluminum curtain wall does not meet the standards to avoid incorrect detection results caused by other factors.

[0057] Specifically, the core concept of YOLOv5 is to formulate the entire object detection task as a regression problem. It segments the image into multiple regions (called grid cells) and predicts bounding boxes and class probabilities for each grid cell. The YOLOv5 architecture consists of the following components: The Backbone extracts features from the image, typically using the CSPDarknet53 network; the Neck integrates and transfers the extracted features; in YOLOv5, the Panoptic Feature Pyramid Network (PANet) is used; and the Head generates bounding boxes and class probabilities, using YOLO's original prediction method.

[0058] See also Figure 3 As shown, it is a flowchart of the steps of judging based on the comparison result of the average value of several area ratios at the same time with the preset area ratio in an embodiment of the present invention. The process of judging whether the aluminum plate curtain wall meets the standard based on the obtained area ratios in an embodiment of the present invention includes: calculating the average value of each area ratio, and judging whether the aluminum plate curtain wall meets the standard based on the comparison result of the obtained average value with the pre-stored preset area ratio, wherein: if the average value is less than or equal to the first preset average value, the aluminum plate curtain wall is judged to meet the standard; if the average value is greater than the first preset average value and less than the second preset average value, judging whether the aluminum plate curtain wall meets the standard based on the variance of each area ratio; if the average value is greater than or equal to the second preset average value, judging that the aluminum plate curtain wall does not meet the standard, and determining the reason why the aluminum plate curtain wall does not meet the standard based on the difference between the average value and the second preset average value.

[0059] Specifically, in this embodiment, the average value L0 of several area ratios at the same time can be divided into a first preset average value L1 and a second preset average value L2, and the average value standard L3 is set to 0.5, L1=L3, and L2=1.5×L3. It should be noted that in other embodiments, the values ​​of L1, L2, and L3 can also be determined according to the relative requirements of the aluminum plate curtain wall, and the values ​​of the average values ​​are rounded up; the comparison process based on the average value L with L1 and L2 is as follows:

[0060] If the average value L is less than or equal to the first preset average value L1, it can be determined that the surface of the current aluminum curtain wall meets the standard;

[0061] If the average value L is greater than the first preset average value L1 and less than the second preset average value L2, it is impossible to determine whether the test result is caused by other factors. Therefore, it is necessary to perform a secondary determination on the variance P of the area ratio of the aluminum curtain wall surface at the same time.

[0062] If the average value L is greater than or equal to the second preset average value L2, it is determined that the current aluminum plate curtain wall surface does not meet the standard, and the reason why the aluminum plate curtain wall does not meet the standard is analyzed based on the difference between the average value of the actual area ratio and the second preset average value.

[0063] See also Figure 4 , which is a flowchart of the steps for determining whether the aluminum curtain wall meets the standard based on the variance of the area ratio at the same time and the preset variance according to an embodiment of the present invention. The process of determining whether the aluminum curtain wall meets the standard based on the variance of the average value of each area ratio according to an embodiment of the present invention includes: comparing the obtained variance with the preset variance; if the variance is less than or equal to the preset variance, determining that the image information acquisition process does not meet the standard, and re-determining the detection parameters in the image acquisition process based on the obtained variance value; if the variance is greater than the preset variance, determining that the curtain wall does not meet the standard, and determining the reason for non-compliance based on the difference between the average value and the second preset average value.

[0064] Specifically, when the average value L is greater than the first preset average value L1 and less than the second preset average value L2, the variance of the average values ​​of the area ratios is calculated, and the reason why the curtain wall does not meet the standard is determined based on the comparison result of the obtained variance with the preset variance. In this embodiment, the preset variance P0 is set to 1, and the comparison process of the variance of the area ratios at the same time with the preset variance is as follows:

[0065] If the variance P is less than or equal to the preset variance P0, it means that the numerical discreteness of the area ratio of each partition is low. At this time, it is determined that there is a problem with the illumination light intensity during the image information acquisition process, and the illumination brightness during the image information acquisition process needs to be re-determined.

[0066] If the variance P is greater than the preset variance P0, it indicates that there is no problem in the corrosion position identification part, and it is determined that the surface of the aluminum curtain wall meets the standard. It is necessary to further determine the reason why the surface of the aluminum curtain wall does not meet the standard.

[0067] Specifically, the process of re-determining the detection parameters in the image acquisition process based on the variance value in an embodiment of the present invention includes: obtaining the difference between the variance and the preset variance; increasing the illumination light intensity based on the obtained difference, and the difference is proportional to the increase in the illumination light intensity.

[0068] Specifically, in this embodiment, the preset difference is Q0=0.5, and the comparison process based on the difference between the variance and the preset variance is as follows:

[0069] If the difference Q is less than the preset difference Q0, the illumination light intensity of the processing unit is adjusted to 1.5 times the original illumination light intensity;

[0070] If the difference Q is greater than or equal to the preset difference Q0, the illumination light intensity of the processing unit is adjusted to 3.5 times the original illumination light intensity.

[0071] See also Figure 5 As shown, it is a flowchart of the steps of the present invention based on the difference between the average value of the actual area ratio and the second preset average value and the preset difference. The process of determining the reason why the aluminum plate curtain wall does not meet the standard based on the difference between the average value and the second preset average value in the embodiment of the present invention includes: determining whether the aluminum plate curtain wall is corroded based on the comparison result of the difference between the average value and the second preset average value and the pre-stored preset difference, wherein: if the difference is less than or equal to the first preset difference, it is determined that the aluminum plate curtain wall is corroded; if the difference is greater than the first preset difference and less than the second preset difference, it is determined whether the aluminum plate curtain wall is corroded based on the average value of the clarity of the boundaries of each defect feature; if the difference is greater than or equal to the second preset difference, it is determined whether the aluminum plate curtain wall is corroded based on the secondary ratio; wherein: the secondary ratio is the ratio of the average value of the area ratio in the current detection result to the average value of the area ratio in the previous detection result.

[0072] Specifically, in this embodiment, the difference M0 can be divided into a first preset difference M1 and a second preset difference M2, and the average value standard M3 is set to 0.5, M1=M3, and M2=1.5×M3. It should be noted that in other embodiments, the values ​​of M1, M2, and M3 can also be determined according to the relative component quality requirements, and the vertical values ​​of the matching items are rounded up. The comparison process based on the difference M with M1 and M2 is as follows:

[0073] If the difference M0 is less than or equal to the first preset difference M1, it indicates that the surface of the aluminum curtain wall is corroded, and an anti-corrosion treatment notice is issued;

[0074] If the difference M0 is greater than the first preset difference M1 and less than the second preset difference M2, it indicates that there may be a problem in the image preprocessing process, and the cause of the corrosion on the aluminum curtain wall surface is analyzed based on the clarity of the boundary of the corrosion position;

[0075] If the difference M0 is greater than or equal to the second preset difference M2, the reason why the aluminum curtain wall is corroded is analyzed based on the detection results at the historical moment and the current moment.

[0076] Specifically, the process of determining whether the aluminum curtain wall is corroded based on the average value of the clarity of the boundaries of each defect feature in the embodiment of the present invention includes:

[0077] Comparing the clarity average with a preset clarity average;

[0078] If the average clarity value is less than or equal to the preset average clarity value, it is determined that the preprocessing process for the image information does not meet the standard, and the preprocessing parameters are re-determined based on the difference between the average clarity value and the preset average clarity value; wherein: the detection parameters include the preprocessing parameters.

[0079] If the average clarity value is greater than the preset average clarity value, it is determined that the aluminum curtain wall is corroded and an anti-corrosion treatment notice is issued.

[0080] Specifically, in this embodiment, the average value of the preset clarity N0=3.4, and the comparison process of the average value of the clarity of the boundary of the corrosion position at the same time and the preset clarity is as follows:

[0081] If the average value N of the clarity is less than or equal to the average value N0 of the preset clarity, it indicates that there is a problem with image acquisition, and the acquired image cannot be effectively processed, resulting in the use of blurred image information for feature recognition in actual situations, so the preprocessing parameters for the image information are adjusted;

[0082] If the average value N of the clarity is greater than the average value N0 of the preset clarity, it means that there is no problem in the image processing process, and corrosion occurs on the aluminum curtain wall, and an anti-corrosion treatment notice is issued.

[0083] Specifically, the process of re-determining the preprocessing parameters based on the difference between the average clarity value and the preset average clarity value in an embodiment of the present invention includes: increasing the noise reduction ratio based on the difference between the clarity and the preset clarity, and the difference is proportional to the noise reduction ratio; wherein: the preprocessing parameters include (noise reduction ratio, grayscale transformation parameters).

[0084] Specifically, in this embodiment, the preset difference H0=1, and the comparison process based on the difference between the definition and the preset definition is as follows:

[0085] If the actual difference H is less than or equal to the preset difference H0, the noise reduction ratio is adjusted to 1.2 times the original noise reduction ratio;

[0086] If the actual difference H is greater than the preset difference H0, the noise reduction ratio is adjusted to 3 times the original noise reduction ratio.

[0087] Specifically, the process of determining whether the aluminum curtain wall is corroded based on the secondary ratio in an embodiment of the present invention includes: comparing the secondary ratio with a preset secondary ratio; if the secondary ratio is less than or equal to the preset secondary ratio, determining that the aluminum curtain wall is corroded, and issuing an anti-corrosion treatment notice; if the secondary ratio is greater than the preset secondary ratio, determining that there is a problem with the illumination angle, and redetermining the illumination angle based on the difference between the secondary ratio and the preset secondary ratio; wherein: the illumination angle is the angle between the line connecting the illumination point and the aluminum curtain wall and the line connecting the image acquisition point and the aluminum curtain wall; the detection parameters include the illumination angle.

[0088] Specifically, in this embodiment, the preset ratio G0=1, and the comparison process of the ratio of the average value of the area ratio in the detection result at the current moment to the average value of the area ratio in the detection result at the previous moment with the preset ratio is as follows:

[0089] If the ratio G is less than or equal to the preset ratio G0, it means that the corrosion area on the surface of the aluminum curtain wall is large and an anti-corrosion treatment notice needs to be issued;

[0090] If the ratio G is greater than the preset ratio G0, it means that there is a deviation in the illumination angle, resulting in excessive shadows, so that the system misjudges the shadows as corrosion, and therefore it is necessary to adjust the illumination angle during the image acquisition process.

[0091] Specifically, the process of redetermining the illumination angle based on the difference between the secondary ratio and the preset secondary ratio in the embodiment of the present invention includes: reducing the illumination angle based on the difference, and the difference is inversely proportional to the reduction degree of the illumination angle.

[0092] Specifically, in this embodiment, the preset difference K0=1, and the processing process based on the difference between the ratio and the preset ratio is as follows:

[0093] If the difference K is greater than the preset difference KO, the angle is adjusted to 0.7 times the original angle;

[0094] If the difference K is less than or equal to the preset difference K0, the angle is adjusted to 0.5 times the original angle.

[0095] Specifically, the process of re-determining the illumination light intensity based on the illumination angle in an embodiment of the present invention includes: reducing the illumination light intensity based on the illumination angle, and the angle is inversely proportional to the degree of reduction of the illumination light intensity; wherein: the detection parameter includes the illumination light intensity.

[0096] Specifically, in this embodiment, the preset angle R0=90°, and the comparison process based on the angle and the preset angle is as follows:

[0097] If the angle R is less than or equal to the preset angle R0, the intensity of the irradiation light is reduced to 0.7 times the original intensity of the irradiation light;

[0098] If the angle R is greater than the preset angle R0, the intensity of the irradiation light is reduced to 0.4 times the original intensity of the irradiation light.

[0099] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0100] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A surface detection method for energy-saving and environmentally friendly aluminum curtain wall based on machine vision, characterized in that: include: Polish the aluminum curtain wall to eliminate shadows on its surface; Acquiring image information of the surface of the aluminum curtain wall in real time; Preprocessing the image information; Based on the preprocessed image information, the image information is detected using the YOLOv5 model to obtain defect features in the image information; Dividing the preprocessed image information into a plurality of partitions of equal area, and calculating the area ratio in each partition, wherein the area ratio is the ratio of the area of ​​the defect feature in a single partition to the area of ​​the corresponding partition; determining whether the aluminum curtain wall meets the standards based on the obtained area ratios, and if it is determined that the aluminum curtain wall does not meet the standards, generating a corresponding treatment method based on the determined reason for not meeting the standards, including issuing an anti-corrosion treatment notice and re-determining corresponding inspection parameters; The process of determining whether the aluminum curtain wall meets the standards based on the obtained area ratios includes: Calculate the average value of each area ratio, and determine whether the aluminum curtain wall meets the standard based on the comparison result of the obtained average value and the pre-stored preset area ratio, wherein: If the average value is less than or equal to a first preset average value, it is determined that the aluminum curtain wall meets the standard; If the average value is greater than the first preset average value and less than the second preset average value, determining whether the aluminum curtain wall meets the standard based on the variance of each area ratio; If the average value is greater than or equal to the second preset average value, it is determined that the aluminum curtain wall does not meet the standard, and the reason why the aluminum curtain wall does not meet the standard is determined based on the difference between the average value and the second preset average value; The process of determining whether the aluminum curtain wall meets the standard based on the variance of each area ratio includes: Compare the obtained variance with the preset variance; If the variance is less than or equal to the preset variance, determining that the acquisition process of the image information does not meet the standard, and re-determining the detection parameters in the image acquisition process based on the obtained variance value; If the variance is greater than the preset variance, it is determined that the curtain wall does not meet the standard, and the reason for not meeting the standard is determined based on the difference between the average value and the second preset average value; The process of re-determining the detection parameters in the image acquisition process based on the variance value includes: Obtaining a difference between the variance and the preset variance; Increasing the intensity of the illumination light based on the obtained difference, wherein the difference is directly proportional to the increase in the intensity of the illumination light; The process of determining the reason why the aluminum panel curtain wall fails to meet the standard based on the difference between the average value and the second predetermined average value includes: Based on the comparison result of the difference between the average value and the second preset average value and the pre-stored preset difference value, it is determined whether the aluminum curtain wall is corroded, wherein: If the difference is less than or equal to a first preset difference, it is determined that the aluminum curtain wall is corroded; If the difference is greater than the first preset difference and less than the second preset difference, determining whether the aluminum curtain wall is corroded based on the average value of the clarity of the boundaries of each defect feature; If the difference is greater than or equal to the second preset difference, it is determined whether the aluminum curtain wall is corroded based on the secondary ratio; wherein: the secondary ratio is the ratio of the average area ratio in the current test result to the average area ratio in the previous test result.

2. The surface detection method of energy-saving and environmentally friendly aluminum curtain wall based on machine vision according to claim 1 is characterized in that: The process of determining whether the aluminum curtain wall is corroded based on the average value of the clarity of the boundaries of each defect feature includes: Comparing the clarity average with a preset clarity average; If the average clarity value is less than or equal to the preset average clarity value, determining that the preprocessing process for the image information does not meet the standard, and re-determining preprocessing parameters based on the difference between the average clarity value and the preset average clarity value; If the average clarity value is greater than the preset average clarity value, it is determined that the aluminum curtain wall is corroded and an anti-corrosion treatment notice is issued.

3. The surface detection method of energy-saving and environmentally friendly aluminum curtain wall based on machine vision according to claim 2 is characterized in that: The process of re-determining the preprocessing parameters based on the difference between the average clarity value and the preset average clarity value includes: The noise reduction magnification is increased based on the difference between the definition and the preset definition, and the difference is proportional to the increase of the noise reduction magnification.

4. The surface detection method of energy-saving and environmentally friendly aluminum curtain wall based on machine vision according to claim 1 is characterized in that: The process of determining whether the aluminum curtain wall is corroded based on the secondary ratio includes: comparing the secondary ratio with a preset secondary ratio; If the secondary ratio is less than or equal to the preset secondary ratio, it is determined that the aluminum curtain wall is corroded, and an anti-corrosion treatment notice is issued; If the secondary ratio is greater than the preset secondary ratio, it is determined that there is a problem with the illumination angle, and the illumination angle is re-determined based on the difference between the secondary ratio and the preset secondary ratio; wherein: the illumination angle is the angle between the line connecting the illumination point and the aluminum curtain wall, and the line connecting the image acquisition point and the aluminum curtain wall.

5. The surface detection method of energy-saving and environmentally friendly aluminum curtain wall based on machine vision according to claim 4 is characterized in that: The process of redetermining the irradiation angle based on the difference between the secondary ratio and the preset secondary ratio includes: The illumination angle is reduced based on the difference, and the difference is inversely proportional to the reduction of the illumination angle.

6. The surface detection method of energy-saving and environmentally friendly aluminum curtain wall based on machine vision according to claim 5 is characterized in that: The process of re-determining the illumination light intensity based on the illumination angle includes: The illumination light intensity is reduced based on the illumination angle, and the angle is inversely proportional to the reduction amplitude of the illumination light intensity.

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