Nonlinear ultrasonics for early damage detection

Rafael Munoz*, Juan Chiachío Ruano, Guillermo Rus, Manuel Chiachío, Nicolas Bochud, Sergio Cantero, Daniel J. Barnard, Antonio M. Callejas, Juan Melchor, Laura M. Peralta, Leonard J. Bond

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter in a book

4 Citations (Scopus)


Structural Health Monitoring (SHM) is an emerging discipline that aims at improving the management of the life cycle of industrial components. The scope of this chapter is to present the integration of nonlinear ultrasonics with the Bayesian inverse problem as an appropriate tool to estimate the updated health state of a component taking into account the associated uncertainties. This updated information can be further used by prognostics algorithms to estimate the future damage stages. Nonlinear ultrasonics allows an early detection of damage moving forward the achievement of reliable predictions, while the inverse problem emerges as a rigorous method to extract the slight signature of early damage inside the experimental signals using theoretical models. The Bayesian version of the inverse problem allows measuring the underlying uncertainties, improving the prediction process. This chapter presents the fundamentals of nonlinear ultrasonics, their practical application for SHM, and the Bayesian inverse problem as a method to unveil damage and manage uncertainty.

Original languageEnglish
Title of host publicationEmerging Design Solutions in Structural Health Monitoring Systems
PublisherIGI Global
Number of pages36
ISBN (Electronic)9781466684911
ISBN (Print)1466684909, 9781466684904
Publication statusPublished - 7 Oct 2015


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