D Srikanthrao
Mechanical engineering
June 2024
This study investigates defect detection and classification in composite materials using Scanning Electron Microscopy (SEM) imaging. An experimental study design is applied to enhance SEM picture quality through preprocessing techniques such as Gaussian filtering and histogram equalization. The research focuses on identifying and quantifying defects, including cracks, voids, fiber misalignment, and delamination, by employing edge detection algorithms (Canny and Sobel) and thresholding methods (global and adaptive). Quantitative analysis is performed to determine defect density, size distribution, and classification accuracy. The study aims to provide a comprehensive evaluation of defect detection and classification processes, contributing to improved material quality assessment in composite materials.
600- 610
© Airo Journals 2021
