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PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING
Edited by: Y. Tsompanakis, J. Kruis and B.H.V. Topping
Soft Computing Applied to Defect Detection in Composite Materials
P. Nazarko and L. Ziemianski
Department of Structural Mechanics, Rzeszow University of Technology, Poland
P. Nazarko, L. Ziemianski, "Soft Computing Applied to Defect Detection in Composite Materials", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 46, 2015. doi:10.4203/ccp.109.46
Keywords: novelty detection, damage identification, structural health monitoring, composite material, principal component analysis.
Composite materials are widely used in many important structures, which in turn entails the need to develop sensitive and reliable structural health monitoring systems. This paper investigates the use of guided waves and artificial neural networks as essential components of a two-stage diagnostics system. Successful experiments carried out on isotropic specimens proved that this system was able to perform automatic analysis of the elastic waves and accelerate the process of structural diagnosis. For the first time, this approach was used for non-destructive testing of glass fibre reinforced polymer strip and plate specimens with defects of various origin. The diagnostic system training stage was based on elastic wave signals received by a network of piezoelectric transducers and then processed by the principal components analysis. Examples of preliminary fault detection results show that any signal anomalies are detected perfectly and the prediction of damage level enabled the defects introduced to be distinguished.
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