Nonlinear Ultrasonics for Early Damage Detection Muñoz Beltrán, Rafael Rus Carlborg, Guillermo Bochud, Nicolás Barnard, Daniel J. Melchor Rodríguez, Juan Manuel Chiachío Ruano, Juan Chiachío Ruano, Manuel Cantero Chinchilla, Sergio Callejas Zafra, Antonio Manuel Peralta, Laura Bond, Leonard J. 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. 2024-02-12T08:53:44Z 2024-02-12T08:53:44Z 2019-09 book part Munoz, R., Rus, G., Bochud, N., Barnard, D. J., Melchor, J., Ruano, J. C., Chiachío, M., Cantero, S., Callejas, A. M., Peralta, L. M., & Bond, L. J. (2020). Nonlinear Ultrasonics for Early Damage Detection. In I. Management Association (Ed.), Virtual and Mobile Healthcare: Breakthroughs in Research and Practice (pp. 697-732). IGI Global. https://doi.org/10.4018/978-1-5225-9863-3.ch034 9781522598633 9781522598640 https://hdl.handle.net/10481/88999 10.4018/978-1-5225-9863-3.ch034 eng embargoed access IGI Global