Detection of delamination in carbon fibre reinforced composite using vibration analysis and artificial neural network

Abstract

From recent years damage detection in composite structures is given a prior attention to avoid failure and breakdown of the structures. Delamination in composite structures is one of the main reasons for the failure and also affects the properties of the composite structures. Carbon fibre reinforced composite has a wide applications in industries which requires monitoring and detection of delamination for proper functioning. There are various methods such as non-destructive methods, mathematical models etc. to detect the delamination but are quiet costly, time taking and inefficient. In the present investigation, Artificial neural network (ANN) is used to determine delamination defect in carbon fiber reinforced polymer composite. ANN model can solve complex problems. Hence, the ANN model is developed to predict the delamination length and location from the fixed end by analyzing the first three carbon fiber composite structures three natural frequencies. The natural frequencies and mode shapes are obtained using finite element analysis (FEA). It has been found that the ANN can predict delamination length and location in carbon fiber reinforced polymer composite.