Acoustic emission and signal processing for fault detection and location in composite materials Carlos Quiterio Gómez Muñoz 1 , Raúl Ruiz de la Hermosa González-Carrato 2* , Fausto Pedro García Márquez 1 , 1 Ingenium Research Group, University of Castilla-La Mancha, Spain {carlosquiterio.gomez; FaustoPedro.Garcia}@uclm.es 2 CUNEF-Ingenium, CUNEF, Spain raulruiz@cunef.edu * corresponding author Abstract The renewable energy industry is in a constant improvement in order to compete and cover any evolving opportunity presented. Nowadays one of those remarkable competitive advantages is focused on maintenance management and terms as operating and maintenance costs, availability, reliability, safety, lifetime, etc. The objectives of this paper are focused on the blades of a wind turbine. A structural health monitoring study is presented, that starts with the collection and analysis of data coming from different non- destructive tests. Signals from acoustic emissions are studied by a novel signal processing approach to detect cracks on the surface of the blades. The case study proposes a new localization method using macro-fibre composite sensors and actuators. The monitoring system uses three sensors strategically located on the blade section. Among the main difficulties involved in this first approach, the modal separation of the wave is taken into account for its importance when drawing conclusions concerning the crack. This effect is the result of the blade breakdown, producing different signals at multiple frequencies. Another drawback is associated to the direction of the fibres in the composite material. This is known as slowness profile, a function depending on the propagation speed. On the other hand, the main novelty of the approach presented is that it is able to predict the failure. In addition, it can be considered an accurate analysis as the solution will be always a single point obtained from a graphical method, i.e. the location of the crack can be detected with precision. The results are also checked quantitatively using nonlinear equations. Keywords: Acoustic emission, wind turbine, structural health monitoring, macro-fibre composite.