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What is Ultrasonic Welding Defects Analysis about?

This document presents an analysis of ultrasonic welding defects using image processing and deep learning techniques, specifically Convolutional Neural Networks (CNNs). The study aims to evaluate the impact of various welding parameters on the mechanical characteristics of aluminum joints and to classify weld quality into three categories: good, under, and over weld. Experimental results indicate a classification accuracy of 90% for the CNN model in identifying weld defects based on image data.

Author

Tamal Paul

Language

EN