A method for quickly identifying and determining fiber distribution of a fiber concrete section based on MATLAB

Abstract

The present application relates to a kind of based on MATLAB fast identification and determine the method of fiber concrete section fiber distribution, belong to material intelligent detection technical field.The method includes: cutting fiber concrete block, get smooth fiber concrete section;With camera shooting, obtain fiber distribution original image;Based on the figuremodify.m code file written in MATLAB, input fiber distribution original image, carry out gray scale, binarization and noise removal processing, obtain clear fiber distribution chart;According to the mapping relationship of pixel-physical size, output quantization report, obtain the centroid coordinate graph and average spacing of fiber.The present application can utilize image recognition processing and calculation technology to realize fast automatic quantization analysis, overcome the problems such as low efficiency, complex steps and high cost in detecting fiber distribution, significantly improve the efficiency and accuracy of material detection.

Description

Technical Field

[0001] This invention relates to the field of intelligent material detection technology, specifically to a method for rapidly identifying and determining the fiber distribution in a cross-section of fiber-reinforced concrete based on MATLAB. Background Technology

[0002] Adding an appropriate amount of fiber to concrete can effectively inhibit the generation and development of microcracks and improve its strength. However, excessive addition, excessively large fiber spacing, or localized aggregation can increase internal defects in the concrete and weaken its resistance to deformation. Therefore, quickly and accurately identifying and quantifying the distribution of fibers in the concrete cross-section is a key step in optimizing material mix proportions and testing material properties.

[0003] Traditional fiber distribution detection methods mainly rely on manual operation, involving sampling through a microscope and then observing and calculating the images using image processing tools or automated tools developed in C language. This process requires manual adjustment of parameters and algorithms, resulting in poor applicability. In recent years, attempts have been made to introduce image recognition technology into the detection of fiber distribution in concrete cross-sections. However, due to background interference and variations in brightness, false fiber outlines are easily generated, leading to missed or misjudged fibers.

[0004] MATLAB is an integrated platform for engineering calculations and image processing. It has the characteristics of quickly implementing fiber contour enhancement, noise filtering and feature extraction algorithms, automatically adapting to different lighting conditions, quantifying distribution uniformity indicators and visualizing them. It can effectively solve the problems existing in previous fiber distribution detection methods.

[0005] Current research still has significant limitations in determining the distribution of fibers in concrete cross-sections. No publicly available technology has yet deeply integrated MATLAB's matrix computation advantages with the quantitative analysis needs of concrete fiber distribution. Summary of the Invention

[0006] This invention addresses the shortcomings of existing technologies by providing a method for rapidly identifying and determining the fiber distribution in a cross-section of fiber-reinforced concrete based on MATLAB. The invention utilizes MATLAB to perform grayscale conversion, binarization, and noise reduction on the image, then obtains the centroid coordinates of each identified fiber, and calculates the fiber distribution in the cross-section. Furthermore, this invention is applicable to the distribution of admixtures on the surface of any material.

[0007] This invention is achieved through the following technical solution:

[0008] Cut concrete specimens containing fibers, grind the cut surfaces to obtain smooth concrete surfaces;

[0009] Furthermore, the concrete cross-section is photographed to obtain the original image, with the image file extension .jpg;

[0010] Furthermore, based on MATLAB, the image was processed for grayscale conversion, binarization, and noise reduction to identify a clear fiber distribution map;

[0011] Furthermore, the centroid coordinates of each fiber and the average fiber spacing were calculated based on MATLAB.

[0012] The output includes fiber distribution images, fiber coordinates, and average spacing after grayscale conversion, binarization, and noise reduction processing, respectively.

[0013] Advantages and beneficial effects of the present invention:

[0014] This invention uses MATLAB to perform grayscale conversion, binarization, and noise reduction on the original fiber images of concrete cross-sections, resulting in a very clear fiber distribution map and enhancing the reliability of the results.

[0015] This invention is based on MATLAB and automates the process from image input to result output without the need for any other equipment, greatly improving the detection rate and contributing to engineering practice.

[0016] This invention is based on MATLAB and supports the detection of the distribution of different types of fibers and even admixtures on the surface of any material. Furthermore, the distribution of fibers within concrete can be obtained by analyzing the distribution across multiple cross-sections. Attached Figure Description

[0017] Figure 1 This is a schematic diagram illustrating the operation process for obtaining fiber distribution maps using MATLAB.

[0018] Figure 2 Original image of fiber distribution in a certain type of fiber-reinforced concrete;

[0019] Figure 3 This is a grayscale image of the fiber obtained by grayscale conversion using MATLAB.

[0020] Figure 4 This is a binary image of the fiber obtained using MATLAB binarization.

[0021] Figure 5 This is a fiber noise reduction image obtained after noise reduction processing based on MATLAB.

[0022] Figure 6 This is a graph of the fiber centroid coordinates calculated using MATLAB. Detailed Implementation

[0023] To make the objectives and technical solutions of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0024] Step 1: Cutting and Polishing. Cut the fiber-reinforced concrete, grind and polish the cut surface to obtain a smooth concrete surface;

[0025] Step 2: Take a picture. Use a high-definition camera to take a picture to obtain the original image of the fiber distribution. The image file extension is .jpg.

[0026] Step 3: Same folder. Place the original fiber distribution image and the code file figuremodify.m in the same folder;

[0027] Step 4: Start the program. Open the figuremodify.m file in the folder in MATLAB;

[0028] Step 5: Enter the filename. Enter the filename of the original fiber distribution image into the figuremodify.m file and run the program;

[0029] Step 6: Output Results. The program will output a grayscale image, a binarized image, a denoised image, and a fiber centroid coordinate map based on the original fiber distribution map. The program will generate a txt file named "centroids" containing the coordinates of all fiber centroids.

[0030] Example

[0031] like Figure 1 As shown, a method for quickly identifying and determining the fiber distribution in a concrete cross-section based on MATLAB is described. The image 001.jpg, obtained by photography, undergoes grayscale conversion, binarization, and noise reduction using the figuremodify.m file written in MATLAB. This yields the centroid coordinates of the fibers, determining their distribution in the concrete cross-section. The reliability of this method is verified through manual measurement. The specific steps include:

[0032] Step 1: Cutting and Polishing. Cut the fiber-reinforced concrete and polish the cut surface with sandpaper or similar materials to obtain a smooth concrete surface;

[0033] Step 2: Take a photo. Use a 24.2-megapixel camera to take a picture to obtain the original fiber distribution map. The file name is 001.jpg. Figure 2 As shown;

[0034] Step 3: Same folder. Place the original fiber distribution map 001.jpg and the code file figuremodify.m in the text folder;

[0035] Step 4: Start the program. Open the figuremodify.m file in the text folder in MATLAB;

[0036] Step 5: Enter the filename. Input the filename 001.jpg of the original fiber distribution map into the image input program figuremodify.m, and run MATLAB;

[0037] Step 6: Output Results. MATLAB will output a grayscale image, a binarized image, a denoised image, and a fiber centroid coordinate image based on the original fiber distribution map, as shown below. Figure 3-6 As shown in Table 1, MMATLAB will generate a txt file named "centroids" in the text folder, containing the coordinates of all fiber centroids.

[0038] Table 1. Coordinates of the centroid of the fiber in fiber-reinforced concrete

[0039]

[0040]

[0041] The calculation results show that the average fiber spacing of the fiber-reinforced concrete is similar to that of relevant literature, indicating that the method is highly reliable.

[0042] The above description of the embodiments is provided to enable those skilled in the art to understand and use the invention. It will be apparent to those skilled in the art that various modifications can be made to these embodiments, and the general principles described herein can be applied to other embodiments without inventive effort. Therefore, the present invention is not limited to the above embodiments, and any improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the invention should be within the protection scope of the present invention.

Claims

1. A method for rapidly identifying and determining the fiber distribution in a cross-section of fiber-reinforced concrete based on MATLAB, characterized in that, Includes the following steps: Step 1. Obtain the original fiber distribution map. Cut the fiber-reinforced concrete, grind the cut surface, and take a picture to obtain the original fiber distribution map; Step 2. Write the figuremodify.m file. Based on MATLAB and combined with C language knowledge, write code that can quickly identify and determine the fiber distribution in the cross-section; Step 3. Run the program. In MATLAB, run the figuremodify.m file for the original fiber distribution map; Step 4. Output Results. The program will automatically generate grayscale images, binarized images, denoised images, and centroid coordinate data files of the cross-sectional fiber distribution, and generate centroid coordinate images and average fiber spacing.

2. The method for rapidly identifying and determining the fiber distribution in a cross-section of fiber-reinforced concrete based on MATLAB, as claimed in claim 1, is characterized in that... In step 2 of this invention, the color image is converted into a grayscale image, and the image contrast is enhanced by CLAHE and adaptive histogram equalization, with contrast limits of 0.02 and 0.01, respectively.

3. The method for rapidly identifying and determining the fiber distribution in a cross-section of fiber-reinforced concrete based on MATLAB, as claimed in claim 1, is characterized in that... In step 2 of this invention, an initial binary image is generated using the Otsu global thresholding method. Then, an auxiliary binary image is generated by correcting uneven illumination of the image through top-hat transformation. Finally, the initial binary image and the auxiliary binary image are merged by logical operation to obtain a binary image.

4. The method for rapidly identifying and determining the fiber distribution in a cross-section of fiber-reinforced concrete based on MATLAB, as claimed in claim 1, is characterized in that... In step 2 of this invention, Sobel edge detection is used to extract fiber contours, and logical operations are performed with the binarized image to enhance the edges. Erosion and dilation operations are then performed on the merged image to adjust the shape of the fiber region.

5. The method for rapidly identifying and determining the fiber distribution in a cross-section of fiber-reinforced concrete based on MATLAB, as claimed in claim 1, is characterized in that... In step 2 of this invention, the centroid coordinates of the fibers are extracted through regional attribute analysis. Then, based on the pixel-physical size mapping relationship, the centroid coordinates are converted into actual size data to calculate the average fiber spacing and statistically analyze the centroid coordinate data of the fibers.

6. The method for rapidly identifying and determining the fiber distribution in a cross-section of fiber-reinforced concrete based on MATLAB, as claimed in claim 1, is characterized in that... In step 3 of this invention, only the filename of the original fiber distribution map needs to be entered. The program will automatically identify, process, and calculate the distribution and average spacing of the fibers in the cross-section. The entire process is simple to operate, highly accurate, and greatly improves detection efficiency.

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