Classification of shot peening coverage based on deep learning technologies

Shot peening is a cold working process widely used in the aerospace industry, currently, the shot peening process involves mainly an inspector performing visual inspection using a 10x magnifier and comparing the mental visual with an image reference. The state-of-art-technology for coverage inspecti...

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Bibliographic Details
Main Author: Koh, Ren Wei
Other Authors: Ng Beng Koon
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/157853
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Institution: Nanyang Technological University
Language: English
Description
Summary:Shot peening is a cold working process widely used in the aerospace industry, currently, the shot peening process involves mainly an inspector performing visual inspection using a 10x magnifier and comparing the mental visual with an image reference. The state-of-art-technology for coverage inspection involves deep learning. However, there have been no implementing of an automated coverage inspection system using Deep Learning technology. Hence, this paper aims to explore and evaluate different convolutional neural network architecture to evaluate the functionality and performance of a vision inspection system.