A convolutional neural network based framework for health monitoring of a welded joint steel frame structure

Naresh, Maloth, Sikdar, Shirsendu and Pal, Joy 2022. A convolutional neural network based framework for health monitoring of a welded joint steel frame structure. Presented at: IMPORTED, MAY BE LINKED, Advances in Structural Mechanics and Applications. ASMA 2021. , vol.26 pp. 251-262. 10.1007/978-3-031-05509-6_21

Full text not available from this repository.

Abstract

This study presents a Convolutional Neural Network (CNN) based Deep-learning framework for the health monitoring of a welded joint steel plane frame structure. The deep learning algorithm model is trained to extract local features from the vibration-based time-frequency scalogram images and using those features to distinguish the undamaged and two different damage cases of the steel plane frame structure. The performance and robustness of the framework are tested for an unseen image set corresponding to the training classes. The proposed deep learning framework can successfully classify the undamaged and damaged classes with high testing accuracy that signifies its efficiency as an automation tool for the health monitoring of steel plane frame structures subjected to damage near joints.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
ISBN:	978-3-031-05509-6
ISSN:	2522-560X
Last Modified:	06 Jan 2024 02:22
URI:	https://orca.cardiff.ac.uk/id/eprint/160537

Actions (repository staff only)

Edit Item