Quantitative evaluation method for concrete appearance bubbles

Abstract

The invention discloses a quantitative evaluation method for concrete appearance bubbles. The quantitative evaluation method comprises the following steps: S1, image acquisition: performing image acquisition on a concrete test piece by adopting a digital camera; and S2, processing the surface state of the test piece by adopting image Image-Pro-Plus software. The method has the advantages that key parameters such as the bubble area, the bubble diameter, the roundness and the surface pore area ratio can be meticulously analyzed and quantified by accurately collecting the concrete surface image and combining the meticulously designed image processing flow. Compared with a traditional manual detection mode, the detection speed and accuracy are remarkably improved, deviation caused by subjective factors is reduced, and automation and standardization of the detection process are achieved. The method has good adaptability, parameters can be flexibly adjusted according to different scenes and material characteristics, and it is ensured that stable and reliable detection results can be obtained under various conditions.

Description

Technical Field

[0001] The invention relates to the technical field of concrete appearance detection, and in particular to a quantitative evaluation method for concrete appearance bubbles. Background Art

[0002] With the continuous progress of society and the rapid development of science and technology, concrete, as a widely used basic building material, plays a vital role in the construction field. As one of the key factors affecting the appearance quality of concrete, the existence and distribution of concrete bubbles are not only related to the aesthetics of the building, but also directly related to the structural safety and durability. In the process of appearance quality acceptance, the existence of bubbles has become an inspection indicator that cannot be ignored. Especially for larger bubbles or densely distributed bubble groups, they are often regarded as defective indicators, which can easily lead to unqualified acceptance, thus affecting the progress of the project and quality evaluation.

[0003] In view of this, it is particularly important to accurately control and reasonably evaluate the apparent pores. In recent years, relevant domestic industry standards and specifications have been introduced one after another, aiming to provide unified technical guidance and evaluation basis for the detection of concrete bubbles. However, most current research and practice still remain at the stage of traditional ruler measurement or close-range visual inspection. Although these methods are intuitive and simple, they are difficult to get rid of the influence of subjective judgment and lack sufficient accuracy and reliability. Faced with this situation, it is urgent to propose a scientific and effective method to detect the appearance of concrete bubbles. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a quantitative evaluation method for concrete appearance bubbles.

[0005] In order to solve the above technical problems, the technical solution of the present invention is:

[0006] A quantitative evaluation method for concrete appearance bubbles comprises the following steps:

[0007] S1. Image acquisition:

[0008] A digital camera was used to collect images of concrete specimens;

[0009] S2. Use Image-Pro-Plus software to process the surface state of the specimen. The steps are as follows:

[0010] (1) Image import: Import the photo of the concrete specimen surface into the software;

[0011] (2) Image capture: Use the AOI function to accurately extract the specimen and try to avoid image loss;

[0012] (3) Grayscale processing: The concrete pores in the photo appear black, and the image is processed using a binary grayscale processing method with a grayscale threshold of 8;

[0013] (2) Size correction: Click the measurement calibration space function of the software, then drag the ruler to the left and right edges of the specimen image to obtain the number of pixels between the two rulers. The measurement data is converted to the actual measurement length of 150 mm.

[0014] (3) Image adjustment:

[0015] a. Adjust the brightness and contrast to improve the contrast of bubbles in the specimen image;

[0016] b. Use the CLEAN BORDER function (border cleaning) of the software to process the specimen image;

[0017] (4) Export data: Click the "Measurement Data" function of the software to view and output the results, including bubble area, bubble diameter, roundness, and surface pore area ratio. Click the "Statistics" function of the software to summarize all the data.

[0018] Preferably, in step S1, the concrete specimen is cast using a standard concrete compressive strength test mold, and the size of the specimen surface is 150 mm×150 mm.

[0019] Preferably, in step S1, the pixel of the digital camera is 20 million, and the distance between the lens and the surface of the test piece is 0.4 m.

[0020] Preferably, in step S1, before the digital camera captures the image of the concrete specimen, a piece of white paper is placed under the specimen.

[0021] Preferably, in step S1, when the digital camera collects images of the concrete specimen, the lens is perpendicular to the specimen surface and located in the center of the specimen surface, and the edge of the digital camera screen should be parallel to the side length of the specimen.

[0022] The above technical solution has the following advantages:

[0023] The present invention cleverly integrates image acquisition technology and image software analysis technology to construct a set of efficient and accurate concrete bubble detection methods. A variety of image processing technologies, including binary grayscale processing and size correction, are used to accurately identify bubble characteristics. Through the precise acquisition of concrete surface images, combined with a carefully designed image processing process, key parameters such as bubble area, bubble diameter, roundness, and surface pore area ratio can be carefully analyzed and quantified. Compared with traditional manual detection methods, the present invention significantly improves detection speed and accuracy, reduces deviations caused by subjective factors, and realizes automation and standardization of the detection process. The present invention has good adaptability and can flexibly adjust parameters according to different scenarios and material characteristics to ensure that stable and reliable detection results can be obtained under various conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The image captured by the digital camera of the present invention;

[0025] Figure 2 is the image after image capture processing;

[0026] Figure 3 is the image after the grayscale processing step;

[0027] Figure 4 This is the image after the exported data is processed; DETAILED DESCRIPTION

[0028] The specific embodiments of the present invention are further described below in conjunction with the accompanying drawings. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0029] S1. Image acquisition:

[0030] A 20-megapixel digital camera was used to capture images of concrete specimens; the image acquisition requirements are as follows:

[0031] The specimen was cast in a standard concrete compressive strength test mold. The size of the specimen surface was 150 mm × 150 mm. Since the area to be collected was relatively small, the distance between the lens and the specimen surface was 0.4 m.

[0032] Before the digital camera collects images of the concrete specimen, a blank A3 paper is placed under the specimen to eliminate the white balance. To avoid interference, the specimen surface must be dry before taking photos, otherwise reflections and other factors will affect the bubble extraction using software in the later stage.

[0033] When collecting images, ensure that there is sufficient light around, the lens is perpendicular to the surface of the specimen, and is located in the center of the specimen surface; at the same time, the digital camera should be parallel to the side length of the specimen, otherwise data will be lost when the software is used to extract the area of ​​the specimen in the photo later;

[0034] S2. Use Image-Pro-Plus software to process the surface state of the specimen. The steps are as follows:

[0035] (1) Image import: Import the photo of the concrete specimen surface into the software, such as Figure 1 As shown;

[0036] (2) Image capture: Use the AOI function (automatic optical inspection function) to accurately extract the specimen and try to avoid image loss, such as Figure 2 As shown; AOI function is used to eliminate white balance;

[0037] (3) Grayscale processing: The concrete pores in the photo appear black, and the image is processed using a binarization grayscale processing method with a grayscale threshold of 8. The purpose of binarization is to make the pores and pore walls in the image appear in two extreme colors (black or white) to improve the recognition of the measurement and thus improve the calculation accuracy.

[0038] (2) Correction of size: Click the software measurement calibration space, and drag the ruler to the left and right edges of the specimen image to obtain the number of pixels between the two rulers. The measurement data is converted to the actual measurement length of 150 mm. By using Image-Pro-Plus software to correct the size of the concrete specimen image, the actual size of the concrete is input and equivalently replaced by the image size in the software, and then the size of the on-site concrete structure and the pore size on its surface are marked. At this time, the final data is converted into mm units accordingly;

[0039] (3) Image adjustment:

[0040] a. Adjust the brightness and contrast. Although the image has been grayscaled and appears in black, white and gray, the corresponding area in the image tends to appear darker due to the color difference of the concrete surface, which affects data extraction. Therefore, the brightness and contrast can be adjusted to attenuate and improve the contrast of the bubbles.

[0041] b. Use the CLEAN BORDER function of the software to process the specimen image to remove edge shadows around the specimen in the image caused by light problems;

[0042] (4) Export data: Click "Measurement Data" to view and output the results, including bubble area, bubble diameter, roundness, surface pore area ratio and other data. Click "Statistics" to summarize all the data.

[0043] The present invention ingeniously combines two key technical fields, image acquisition and image software analysis, to create an efficient and accurate solution specifically for concrete bubble detection. With the help of image acquisition equipment, high-resolution images of the concrete surface can be captured, laying a solid foundation for subsequent analysis. At the software analysis level, the present invention uses a series of complex image processing algorithms including binary grayscale processing and size correction to ensure accurate identification and quantification of bubble features.

[0044] Through this series of carefully designed image processing processes, not only can the area, diameter and roundness of the bubbles be accurately measured, but also the surface pore area ratio can be calculated, that is, the ratio of the total pore area to the total surface area of ​​the concrete. This indicator is of great significance for evaluating the performance and quality of concrete. Compared with the traditional detection method that relies on manual experience, this invention significantly improves the efficiency and accuracy of detection, effectively eliminates the errors that may be caused by subjective judgment, and realizes the automation and standardization of the entire detection process.

[0045] What is more worth mentioning is that the present invention can flexibly adjust the image processing parameters according to different application scenarios and material characteristics, ensuring stable and reliable results in any environment. This breakthrough innovation not only greatly improves the level of detection technology in the concrete industry, but also provides a powerful tool for engineering quality control and defect analysis, which effectively promotes technological progress and quality upgrades in the construction industry.

[0046] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. For those skilled in the art, various changes, modifications, substitutions and variations of these embodiments are made without departing from the principles and spirit of the present invention, and still fall within the scope of protection of the present invention.

Claims

1. A quantitative evaluation method for concrete appearance bubbles, characterized in that The following steps are involved: S1. Image acquisition: A digital camera was used to collect images of concrete specimens; S2. Use Image-Pro-Plus software to process the surface state of the specimen. The steps are as follows: (1) Image import: Import the photo of the concrete specimen surface into the software; (2) Image capture: Use the AOI function to accurately extract the specimen and try to avoid image loss; (3) Grayscale processing: The concrete pores in the photo appear black, and the image is processed using a binary grayscale processing method with a grayscale threshold of 8; (2) Size correction: Click the measurement calibration space function of the software, then drag the ruler to the left and right edges of the specimen image to obtain the number of pixels between the two rulers. The measurement data is converted to the actual measurement length of 150 mm. (3) Image adjustment: a. Adjust the brightness and contrast to improve the contrast of bubbles in the specimen image; b. Use the CLEAN BORDER function of the software to process the specimen image; (4) Export data: Click the "Measurement Data" function of the software to view and output the results, which include bubble area, bubble diameter, roundness, surface pore area ratio and other data. Click the "Statistics" function of the software to summarize all the data.

2. The quantitative evaluation method of concrete appearance bubbles according to claim 1 is characterized by: In step S1, the concrete specimen is cast using a standard concrete compressive strength test mold, and the size of the specimen surface is 150 mm × 150mm.

3. The quantitative evaluation method of concrete appearance bubbles according to claim 1 is characterized by: In step S1, the pixel of the digital camera is 20 million, and the distance between the lens and the surface of the test piece is 0.4 m.

4. The quantitative evaluation method of concrete appearance bubbles according to claim 1 is characterized by: In step S1, before the digital camera collects images of the concrete specimen, a piece of white paper is placed under the specimen.

5. The quantitative evaluation method of concrete appearance bubbles according to claim 1 is characterized by: In step S1, when the digital camera collects images of the concrete specimen, the lens is perpendicular to the specimen surface and located in the center of the specimen surface, and the edge of the digital camera screen should be parallel to the side length of the specimen.

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