AI-facilitated coating corrosion assessment system for productivity enhancement

Application of protective coatings is the primary method used to protect marine and offshore structures from coating breakdown and corrosion (CBC). Assessment of CBC is the major aspect in coating failure management. Subjective assessment methods cause unnecessary maintenance cost and higher risk of...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE Conference on Industrial Electronics and Applications (Online) pp. 606 - 610
Main Authors:	Liu, Lili, Tan, Estee, Zhen, Yongda, Yin, Xi Jiang, Cai, Zhi Qiang
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.05.2018
Subjects:	AI-facilitated CBC assessment system (A-CAS) coating breakdown and corrosion (CBC) inspection Coatings Corrosion deep transfer learning Electric breakdown Feature extraction Image edge detection Image segmentation Inspection instance-aware semantic segmentation
ISSN:	2158-2297
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Application of protective coatings is the primary method used to protect marine and offshore structures from coating breakdown and corrosion (CBC). Assessment of CBC is the major aspect in coating failure management. Subjective assessment methods cause unnecessary maintenance cost and higher risk of failure. To improve efficiency and productivity, an integrated coating breakdown and corrosion (CBC) assessment system is developed. This AI-facilitated CBC inspection system implements a deep transfer learning technique to automate CBC assessment, it includes a faster region-base convolutional neural network (faster R-CNN) architecture and a vgg19 model for deep transfer learning, an instance-aware semantic segmentation method is developed for CBC measurement and grading. This method provides efficient inspection techniques for marine and offshore industries.
ISSN:	2158-2297
DOI:	10.1109/ICIEA.2018.8397787