Feature Detection of GFRP Subsurface Defects Using Fast Randomized Sparse Principal Component Thermography

Shen, Peng; Luo, Zhitao; Wang, Sheng; Mao, Feilong; Su, Zihao; Zhang, Hui

doi:10.1007/s10765-022-03076-z

Cited by 8 publications

(1 citation statement)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since these assessments can be time-consuming and destructive, they are usually performed offline on a very small sample cut from the produced film (Gosselin et al, 2009;Łukasik & Stachowiak, 2020). Alternatively, since defects can have a significant impact on the quality of polymeric products, attribute-based defect detection is used to evaluate the quality of polymers (Altarazi, 2018;Shen et al, 2022). Practically, defect detection is a proven method for reducing the negative impact of product defects (Ravimal et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Vision-based Online Defect Detection of Polymeric Film via Structural Quality Metrics

Rawashedeh,

Hazaveh,

Altarazi

2023

Management and Production Engineering Review

View full text Add to dashboard Cite

Nondestructive and contactless online approaches for detecting defects in polymer films are of significant interest in manufacturing. This paper develops vision-based quality metrics for detecting the defects of width consistency, film edge straightness, and specks in a polymeric film production process. The three metrics are calculated from an online low-cost grayscale camera positioned over the moving film before the final collection roller and can be implemented in real-time to monitor the film manufacturing for process and quality control. The objective metrics are calibrated to correlate with an expert ranking of test samples, and results show that they can be used to detect defects and measure the quality of polymer films with satisfactory accuracy.

show abstract