Damage detection in T-joint composite structures

The use of composite structures in engineering applications has proliferated over the past few decades. This is mainly due to their distinct advantages of high structural performance, high corrosion resistance, and high strength/weight ratio. They are however prone to fibre breakage, matrix cracking and delaminations which are often invisible. Although there are systems to detect such damage, the characterisation of the damage is often much more difficult to achieve. A study is presented of the strain distribution of a GFRP T-joint structure under tensile pull-out loads and the determination of the presence and the extent of disbonds. Finite element analysis (FEA) has been conducted by placing delaminations of different sizes at various locations along the structure. The FEA results are also validated experimentally. The resulting strain distribution from the FEA is pre-processed by a method developed called the damage relativity assessment technique (DRAT). Artificial neural networks (ANNs) were used to determine the extent of damage. A real-time system has been developed which detects the presence, location and extent of damage from the longitudinal strains obtained from a set of sensors placed on the surface of the structure. The system developed is also independent of the magnitude of load acting on the structure.