Multi-Robot System for Automated Fluorescent Penetrant Indication Inspection with Deep Neural Nets
Authors:
- John KarigiannisJKJohn Karigiannis
- Shaopeng LiuSLShaopeng Liu
- Stephane HarelSHStephane Harel
- Xiao BianXBXiao Bian
- Peihong ZhuPZPeihong Zhu
- Feng XueFXFeng Xue
- Steeves BouchardSBSteeves Bouchard
- David CantinDCDavid Cantin
- Maxime Beaudoin-PouliotMBMaxime Beaudoin-Pouliot
- Bernard P. BewlayBBBernard P. Bewlay
- Marie-Christine CaronMCMarie-Christine Caron
Open Access
- 1 January 2021
- journal article
- research article
- Published by Elsevier in Procedia Manufacturing
- Vol. 53, 735-740
Abstract
No abstract availableKeywords
This publication has 4 references indexed in Scilit:
- Automated defect detection for Fluorescent Penetrant Inspection using Random ForestNDT & E International, 2019
- Design of advanced automatic inspection system for turbine blade FPI analysisAIP Conference Proceedings, 2013
- Fully automated dye-penetrant inspection of automotive partsComputer Standards & Interfaces, 1999
- Automated inspection system for detecting metal surface cracks from fluorescent penetrant images1995