2014
DOI: 10.1117/12.2052938
|View full text |Cite
|
Sign up to set email alerts
|

Thermal inspection of composite honeycomb structures

Abstract: Composite honeycomb structures continue to be widely used in aerospace applications due to their low weight and high strength advantages. Developing nondestructive evaluation (NDE) inspection methods are essential for their safe performance. Pulsed thermography is a commonly used technique for composite honeycomb structure inspections due to its large area and rapid inspection capability. Pulsed thermography is shown to be sensitive for detection of face sheet impact damage and face sheet to core disbond. Data… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2015
2015
2017
2017

Publication Types

Select...
2
1

Relationship

1
2

Authors

Journals

citations
Cited by 3 publications
(4 citation statements)
references
References 9 publications
0
4
0
Order By: Relevance
“…Comparative analysis of computed tomography, X-ray and ultrasonic techniques for the inspection of composite honeycomb structures was reported by Zalameda and Parker [108].…”
Section: Specific Applicationsmentioning
confidence: 95%
“…Comparative analysis of computed tomography, X-ray and ultrasonic techniques for the inspection of composite honeycomb structures was reported by Zalameda and Parker [108].…”
Section: Specific Applicationsmentioning
confidence: 95%
“…A processing time window of 1.5 to 4.83 seconds was used (200 frames). A time delay of 1.5 seconds allowed enough time for the heat to flow through the composite face sheet and into the core and 4.83 seconds was sufficient time to provide good contrast of the underlying geometry [4]. Some thicker laminate regions around the door and window frames would require longer time windows, however for this study only sandwich structure was of interest.…”
Section: Local Eigenvector Calculationmentioning
confidence: 99%
“…As shown in figure 3, these eigenvectors are more influenced by noise and thus result in images that have less spatial detail of interest. The first or second eigenvector PCA image provides good contrast for defect detection [4]. This is shown in figure 4 where the processed images from 3 data sets, starboard side Row I columns: 4, 5, and 6 are assembled to correspond to the visible image.…”
Section: Local Eigenvector Calculationmentioning
confidence: 99%
See 1 more Smart Citation