Synthetic Data-Driven Approach for Missing Nut and Bolt Classification in Flange Joints

Frankly Toro, Hassane Trigui, Yazeed Alnumay, Siddharth Mishra, Sahejad Patel

2024

Abstract

Inspection of bolted flange joints is a routine procedure typically done manually in process-based industries. However, this is a time-consuming task since there are many flanges in a typical operational facility. We present a computer vision-based tool that can be integrated into other systems to enable automated inspection of these flanges. We propose a multi-view image classification architecture for detecting a missing bolt or nut in a flange joint image. To guide the training process, a synthetic dataset with 60,000 image pairs was created to simulate realistic environmental conditions of flange joints. To demonstrate the effectiveness of our approach, an additional real-world dataset of 1,080 flange joint image pairs was manually collected. The proposed approach achieved remarkable performance in classifying missing bolt instances with an accuracy of 95.28% and 95.14% for missing nut instances.

Paper Citation

in Harvard Style

Toro F., Trigui H., Alnumay Y., Mishra S. and Patel S. (2024). Synthetic Data-Driven Approach for Missing Nut and Bolt Classification in Flange Joints. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 301-308. DOI: 10.5220/0012271500003660

in Bibtex Style

@conference{visapp24,
author={Frankly Toro and Hassane Trigui and Yazeed Alnumay and Siddharth Mishra and Sahejad Patel},
title={Synthetic Data-Driven Approach for Missing Nut and Bolt Classification in Flange Joints},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2024},
pages={301-308},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012271500003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - Synthetic Data-Driven Approach for Missing Nut and Bolt Classification in Flange Joints
SN - 978-989-758-679-8
AU - Toro F.
AU - Trigui H.
AU - Alnumay Y.
AU - Mishra S.
AU - Patel S.
PY - 2024
SP - 301
EP - 308
DO - 10.5220/0012271500003660
PB - SciTePress