An Artificial Neural Network Based Approach for Impact Detection on Composite Panel for Aerospace Application

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Abstract: Fleet maintenance and safety aspects represent a strategic aspect in the managing of the modern aircraft fleets. The demand for efficient techniques of system and structure’s monitoring represent so a key aspect in the design of new generation aircraft. This is even more significant for composite structures that can be highly susceptible to delamination of the ply, which is often very difficult to detect externally and can lead to a dramatic reduction of design strength and service life, as a consequence of impact damage. The purpose of the work is the presentation of an innovative application within the Non Destructive Testing field based upon vibration measurements. The aim of the research has been the development of a Non Destructive Test (NDT) which meets most of the mandatory requirements for effective health monitoring systems while, at the same time, reducing as much as possible the complexity of the data analysis algorithm and the experimental acquisition instrumentation.

WSEAS Transactions on Applied and Theoretical Mechanics, ISSN / E-ISSN: 1991-8747 / 2224-3429, Volume 11, 2016, Art. #26

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M. Viscardi, P. Napolitano, "An Artificial Neural Network Based Approach for Impact Detection on Composite Panel for Aerospace Application," WSEAS Transactions on Applied and Theoretical Mechanics, vol. 11, pp. 203-211, 2016, DOI:
M. Viscardi, P. Napolitano. An Artificial Neural Network Based Approach for Impact Detection on Composite Panel for Aerospace Application. WSEAS Transactions on Applied and Theoretical Mechanics. 2016;11:203-211.
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