The objective of this master project is to improve the current SHM techniques for global damage identification of beam-like composite structures. The studied damage diagnosis method is based on structural vibrations from which the modal parameters are obtained. The literature study provides an overview of the most common vibration-based damage identification methods. The modal curvature shape- and modal strain energy-based methods are selected due to their higher sensitivity to local damages. These methods are applied on an aero-elastically tailored composite wing. High-spatial-resolution modal shapes are extracted from the structure with a state-of-the-art fibre optic strain sensing technology based on Rayleigh back-scattering. Damages are simulated in the wing employing localized mass attachments. The achievable level of damage identification with this technique is found and characterized. The different vibration-based methods are compared and their potential is discussed. It is concluded that the used sensing technique is an excellent choice for global damage diagnosis in composite structures.

Wind energy is a growing industry, and in an effort to reduce costs and increase turbine efficiency, rotor blades are becoming increasingly large in size. To facilitate this effort, the SmartBlades2 research project has designed, built, and tested a set of prototype research blades. As part of the SmartBlades2 project, high sensor density modal testing has been conducted on the research blades. The analysis of the modal tests showed good agreement of the global vibration modes with the finite element model predictions. However, the test analysis also identified low frequency vibration modes, referred to as breathing modes, which were not predicted by the finite element models. These vibration modes were found on all of the blades and are characterised by out-of-plane trailing edge panel motion. The objective of this thesis is to identify and predict the aforementioned breathing modes using finite element analysis. To achieve this, three model characteristics are analysed to determine their influence on the breathing mode prediction, namely, model topology, shell element configuration, and material properties. To characterise the affect of model topology, a cut section from the SmartBlades2 prototype blade is modelled with shell elements and continuum element glue joints. To validate the blade section model, a modal test is conducted which identifies breathing modes analogous to the full blade. Various topology features are investigated with the focus on the shell glue joints and spar web joints of the blade section. The analysis shows that while these changes significantly effect the mode shapes and frequencies, none of them predict the experimentally identified breathing modes. To investigate the source of this discrepancy, the modal behaviour of a sample plate structure with the same materials is used to remove the variability of topology. The effects of shell element size and configuration are analysed with mutual comparisons. The analysis shows that higher fidelity element configurations offer no advantage over linear shell elements for prediction of modal behaviour, while the element size shows higher sensitivity. Furthermore, the effects of material properties are examined using the sample plate, subject to modal and flexural tests. It is found that the specified properties are stiffer than measured, and new predictions of the properties are made which better fit the plates experimental results. Finally, the topology, element, and material investigations are then applied to an improved finite element model of the complete blade and correlated with the experimental modal tests. It is found that the improved blade model has closer correlation with the experimental modal tests for global modes, however is unable to predict the identified breathing modes for the blade. It is hypothesised that cause of this may relate to the connection of the spar web with the glue flanges.