Toggle Main Menu Toggle Search

Open Access padlockePrints

Impact Damage Detection and Identification Using Eddy Current Pulsed Thermography Through Integration of PCA and ICA

Lookup NU author(s): Dr Liang Cheng, Dr Bin Gao, Professor Gui Yun TianORCiD, Dr Wai Lok Woo


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Eddy current pulsed thermography (ECPT) is implemented for detection and separation of impact damage and resulting damages in carbon fiber reinforced plastic (CFRP) samples. Complexity and nonhomogeneity of fiber texture as well as multiple defects limit detection identification and characterization from transient images of the ECPT. In this paper, an integration of principal component analysis (PCA) and independent component analysis (ICA) on transient thermal videos has been proposed. This method enables spatial and temporal patterns to be extracted according to the transient response behavior without any training knowledge. In the first step, using the PCA, the data is transformed to orthogonal principal component subspace and the dimension is reduced. Multichannel morphological component analysis, as an ICA method, is then implemented to deal with the sparse and independence property for detecting and separating the influences of different layers, defects, and their combination information in the CFRP. Because different transient behaviors exist, multiple types of defects can be identified and separated by calculating the cross-correlation of the estimated mixing vectors between impact the ECPT sequences and nondefect ECPT sequences.

Publication metadata

Author(s): Cheng L, Gao B, Tian GY, Woo WL, Berthiau G

Publication type: Article

Publication status: Published

Journal: IEEE Sensors Journal

Year: 2014

Volume: 14

Issue: 5

Pages: 1655-1663

Print publication date: 01/05/2014

Online publication date: 17/01/2014

Acceptance date: 05/01/2014

ISSN (print): 1530-437X

ISSN (electronic): 1558-1748

Publisher: IEEE


DOI: 10.1109/JSEN.2014.2301168


Altmetrics provided by Altmetric


Funder referenceFunder name
Cognitive-Networks-Enabled Transnational Proactive Healthcare
Health Monitoring of Offshore Wind Farms
National Research Center of Sensors Engineering
Shenyang Academy of Instrumentation Company Ltd.
University of Electronic Science and Technology of China
2013HH0059Sichuan Science and Technology Department
51377015National Natural Science Foundation of China
EP/F06151X/1Engineering and Physical Sciences Research Council (EPSRC), U. K.
FP7-PEOPLE-2010-IRSES-269202FP7 Health Monitoring of Offshore Wind Farms (HEMOW)