2018
DOI: 10.4018/ijmdem.2018100103
|View full text |Cite
|
Sign up to set email alerts
|

A Fully Automated Porosity Measure for Thermal Barrier Coating Images

Abstract: Thermal barrier coating (TBC), a widely used advanced manufacturing technique in various industries, provides thermal insulation and surface protection to a substrate by spraying melted coating materials on to the surface of the substrate. This article is an extended version of a previously published work. To quantify microstructures in the TBC, the authors introduce a fully automated image analysis-based TBC porosity measure (TBCPM) framework which includes 1) top coat layer (TCL) detection module, and 2) mic… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2020
2020
2022
2022

Publication Types

Select...
3
2

Relationship

1
4

Authors

Journals

citations
Cited by 5 publications
(1 citation statement)
references
References 15 publications
0
1
0
Order By: Relevance
“…Some research also proved that CNNs are able to achieve satisfied accuracy results when deployed for microstructure quantification within thermal spray coatings. Chen et al [39] collected the ground truth of the porosity mask on two full-size images and then randomly selected pixels in the top coat layer (TCL) to form sub-images centred at the pixel and with different sizes to train convolutional neural networks (CNNs) with various architecture. Their proposed approach was evaluated on a dataset of 150 images of size 100 by 100 randomly selected from a set of 30 high-resolution thermal barrier coating images.…”
Section: Convolutional Neural Network (Cnns)mentioning
confidence: 99%
“…Some research also proved that CNNs are able to achieve satisfied accuracy results when deployed for microstructure quantification within thermal spray coatings. Chen et al [39] collected the ground truth of the porosity mask on two full-size images and then randomly selected pixels in the top coat layer (TCL) to form sub-images centred at the pixel and with different sizes to train convolutional neural networks (CNNs) with various architecture. Their proposed approach was evaluated on a dataset of 150 images of size 100 by 100 randomly selected from a set of 30 high-resolution thermal barrier coating images.…”
Section: Convolutional Neural Network (Cnns)mentioning
confidence: 99%