University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Non-invasive damage detection in beams using marker extraction and wavelets

Song, Yi-Zhe, Bowen, C.R., Kim, H.A., Nassehi, A., Padget, J., Gathercole, N. and Dent, A. (2014) Non-invasive damage detection in beams using marker extraction and wavelets Mechanical Systems and Signal Processing, 49 (1-2). pp. 13-23.

Full text not available from this repository.


For structural health monitoring applications there is a need for simple and contact-less methods of Non-Destructive Evaluation (NDE). A number of damage detection techniques have been developed, such as frequency shift, generalised fractal dimension and wavelet transforms with the aim to identify, locate and determine the severity of damage in a material or structure. These techniques are often tailored for factors such as (i) type of material, (ii) damage pattern (crack, delamination), and (iii) the nature of any input signals (space and time). This paper describes and evaluates a wavelet-based damage detection framework that locates damage on cantilevered beams via NDE using computer vision technologies. The novelty of the approach is the use of computer vision algorithms for the contact-less acquisition of modal shapes. Using the proposed method, the modal shapes of cantilever beams are reconstructed by extracting markers using sub-pixel Hough Transforms from images captured using conventional slow motion cameras. The extracted modal shapes are then used as an input for wavelet transform damage detection, exploiting both discrete and continuous variants. The experimental results are verified and compared against finite element analysis. The methodology enables a non-invasive damage detection system that avoids the need for expensive equipment or the attachment of sensors to the structure. Two types of damage are investigated in our experiments: (i) defects induced by removing material to reduce the stiffness of a steel beam and (ii) delaminations in a (0/90/0/90/0)s composite laminate. Results show successful detection of notch depths of 5%, 28% and 50% for the steel beam and of 30 mm delaminations in central and outer layers for the composite laminate.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Bowen, C.R.
Kim, H.A.
Nassehi, A.
Padget, J.
Gathercole, N.
Dent, A.
Date : 20 December 2014
Funders : Leverhulme Trust
DOI : 10.1016/j.ymssp.2013.12.011
Grant Title : Formal techniques for sensor network design, management and optimisation
Uncontrolled Keywords : Hough transform; Image processing; Non-Destructive Evaluation (NDE); Visual tracking; Wavelet transform
Depositing User : Clive Harris
Date Deposited : 30 Jul 2019 08:53
Last Modified : 30 Jul 2019 08:53

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800