An in-situ real-time hidden damage inspection on C-17 Globemaster III composite aileron using LSP technique under thermal excitation

斑点图案 光学 计算机科学 人工智能 物理
作者
Rey-Yie Fong,Fuh‐Gwo Yuan
标识
DOI:10.1117/12.2585247
摘要

A non-contact, full-field vision-based non-destructive inspection (V-NDI) system was developed with multiple damages detection capabilities in composite structures under thermal excitation. In contrast to point-based nondestructive inspection (P-NDI) systems employing laser Doppler vibrometer (LDV) with discrete wavefield captured by pointwise scanning, the V-NDI system captures higher spatial resolution wavefield by a CMOS camera for every time instance without repeating the experiment tens of thousand times to reassemble the wavefield like P-NDI. An Advanced Damage Processing Network (ADPNet) was proposed with laser speckle photometry (LSP) employed in a V-NDI system for hidden damages inspection. The LSP/ADPNet system relies on observing the variation of speckle clouds in time sequence without a baseline and is very insensitive to ambient noise with statistics-based image processing where traditional holography/ESPI suffers greatly. Other advances of LSP/ADPNet system are its robust tolerance of laser coherence, larger illumination area, flexible choice of correlation functions, and more advanced post-processing techniques such as Bayesian updating/inference or unsupervised image segmentation that can be readily applied. Thermal excitation can have very large power throughput in hundreds of watts compared to traditional PZT actuator, merely in a few watt ranges. Laser speckle itself is the result of self-interference scatter field reflected from a rough surface, and each speckle can be treated as a sensing point from a randomly distributed speckle cloud. By observing the variation of speckle cloud on the structure surface, displacement related quantities in higher dimensions (e.g. hypercomplex envelope, phase between real-valued signal and its quadrature, phase congruency, etc.) can be deduced by the Riesz bp transform and correlated in time sequence to highlight the location of hidden damages in a very effective way. Another novelty of this paper is to make a super compact real-time LSP system on LabVIEW FPGA by applying ADPNet comprised of the Riesz bp transform, non-linear filter bank and unsupervised image segmentation to quantify/characterize barely visible impact damages (BVID) on a C-17 Globemaster III composite aileron. To conclude, the images processed by LSP/ADPNet of a V-NDI system show a very good agreement with ultrasonic C-scan and pulse laser/LDV wavefield reconstruction results. It is also demonstrated to be more accurate and robust than Digital Image Correlation (DIC) for minute deformation (sub-nano to nano meter) measurement and large area (meter by meter) inspection under industrial environment.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Twonej应助HYLynn采纳,获得20
1秒前
情怀应助沙拉酱采纳,获得10
1秒前
科研通AI6.1应助baiyu采纳,获得10
1秒前
2秒前
4秒前
雪白的雪完成签到,获得积分10
5秒前
5秒前
亦安发布了新的文献求助10
5秒前
JamesPei应助xh采纳,获得10
7秒前
8秒前
黄晨雅发布了新的文献求助10
8秒前
Cyrilla完成签到,获得积分10
8秒前
8秒前
ls发布了新的文献求助10
8秒前
666999发布了新的文献求助10
8秒前
胡图图发布了新的文献求助10
9秒前
11秒前
无极微光应助Weedy采纳,获得20
11秒前
yang发布了新的文献求助10
11秒前
喝酒的二胖完成签到,获得积分10
12秒前
完美世界应助糕木糕采纳,获得10
12秒前
情怀应助称心的板栗采纳,获得10
13秒前
邓邓发布了新的文献求助10
13秒前
13秒前
直率铁身完成签到,获得积分10
13秒前
14秒前
田様应助南小鸟采纳,获得10
15秒前
啾啾发布了新的文献求助10
16秒前
16秒前
uu完成签到,获得积分10
16秒前
时尚白凡完成签到 ,获得积分10
16秒前
16秒前
18秒前
杜晓倩发布了新的文献求助10
18秒前
yingying发布了新的文献求助10
19秒前
领导范儿应助ls采纳,获得10
20秒前
HHW完成签到,获得积分10
22秒前
22秒前
思源应助Tim采纳,获得10
22秒前
沉默火完成签到,获得积分10
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
Leading Academic-Practice Partnerships in Nursing and Healthcare: A Paradigm for Change 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
Research Methods for Business: A Skill Building Approach, 9th Edition 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6423739
求助须知:如何正确求助?哪些是违规求助? 8242087
关于积分的说明 17521455
捐赠科研通 5478088
什么是DOI,文献DOI怎么找? 2893459
邀请新用户注册赠送积分活动 1869759
关于科研通互助平台的介绍 1707480