Enhancement of open-cracks detection using a principal
component analysis / wavelet technique in photothermal
non destructive testing
S. Hermosilla-Lara1,2,3, Pierre-Yves Joubert2, D. Placko2, F. Lepoutre3, M. Piriou1
1 Technical Center of Framatome, ZIP Sud 71380 Saint-Marcel, France,
2 Laboratoire Electronique Signaux et Robotique (LESiR), Ecole Normale Supérieure de
Cachan, 61 av. du Président Wilson, 94235 Cachan, France,
3 Dept of Structure and Damage Mechanics, ONERA, 29 avenue de la Division Leclerc
BP72, 92322 Châtillon cedex, France
Correspondence to François Lepoutre : tel. :33 1 40 27 29 93 or 33 1 46 73 48 61, Fax : 33
1 46 73 48 91, e-ma
Since the beginning of the 90’s, an important effort in R&D has been done by
Onera to develop a photothermal camera (flying-spot camera) [1]. Indeed, in the
context of the nondestructive inspection of metallic structures in nuclear industry, this
type of active thermography appears to be a good alternative to conventional
techniques such as penetrant inspection for open-crack detection, because it is a
contactless and automatizable technique. A photothermal camera prototype was
realized by ONERA and Framatome. The prototype is a simple and portable device
and was presented in previous works such as [2][3].
In the present paper, the authors focus on the enhancement of open-crack
detection performances in the case of severe surface conditions of the inspected
structure, by the means of appropriate signal processing. After a short description of
the basic principle of the implemented photothermal camera, the tested structure and
the obtained photothermal images are presented. The images are then processed in
order to enhance the open-crack detection and to provide an automatic detection
diagnosis in the form of a binary map [4]. The processing basically consists in the
separation and the identification of the main physical interactions between the
camera and the inspected structure by the means of appropriate principal component
analysis [5]. The detection is then achieved using a continuous wavelet transform.
Finally, receiver operating characteristic curves [6] are used in order to optimize and
characterize the detection performances.
[1] Gruss C. and Balageas D., Theoretical and experimental applications of the flying spot camera,
Proc. of QIRT’92, Ed. D. Balageas, G. Busse and G. Carlomagno, Publ. Editions Européennes
Thermique et Industrie, Paris, 1992, pp. 19-24
[2] L. Legrandjacques , J.C. Krapez , F. Lepoutre et D. Balageas, Nothing but the Cracks: A New Kind
of Photothermal Camera, 7th European Conference on Non-Destructive Testing, 26-29 May 1998,
ISBN: 87-986898-0-00.
[3] J.C. Krapez, L. Legrandjacques; F. Lepoutre, and D.L. Balageas, Optimization of the photothermal
camera for crack detection, QIRT’98, ED. D.Balageas, G. Busse, and G. Carlomagno, Publ. Akademie
Centrum Graficzno-Marketingowe Lodart S.A., Lodz,1999, pp. 305-310.
[4] P.Y. Joubert, Y. Le Bihan, D. Placko, F. Lepoutre : A Wavelet/Bayes Approach for Small Notch
Detection In Eddy Current Testing of Steam Generator Tubes, Review of Progress in Quantitative Non
destructive Evaluation vol.19 , AIP conference proceedings 509, Montréal, Canada, 25-30 juillet 1999,
pp 823-830.
[5] G. Saporta, Probabilités, analyse de données et statistique, Technip, 1990
[6] J.P. Ergan, Signal detection theory an ROC analysis, Series in cognition and perception, NewYork: Academic Press, 1975.
Key-words:
flying-spot camera, photothermal camera, crack detection, principal component analysis, wavelet
transform