Cracks are one of the main causes of structural failure and they develop in the structures due to various reasons such as fatigue, temperature variation, excessive load, cyclic load, environmental effects, impact loading etc. Thus, structural health monitoring is necessary to avoid risks, damages and failures. So, in order to avoid an extensive failure or accident, the early prognosis of crack in structures is necessary. Visual inspection and some non-destructive testing (NDT) methods for detection of crack are difficult as it requires time, expenses and are quite inefficient. So the alternative methods are motivated to be developed. In this study, vibration analysis, finite element analysis (FEA) and an alternative way which is artificial neural network (ANN) is used to predict, detect and identify the damages in structures. It is found that the theoretical, experimental, finite element analysis and artificial neural network have good accuracy in predicting the crack characteristics.

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In automobiles suspension system, laminated springs are widely used for the absorption of shock and vibration. These laminated springs account for approximately 10%–20% of the unsprung weight of the vehicle. It has been found that composite material is used to reduce the weight of the vehicle in order to obtain better efficiency. Therefore, in the current research work, composite material is used for the fabrication of laminated spring. Among the various types of glass fiber available, the C-glass fiber has been widely used due to its better corrosion resistant property. Commercial software package ANSYS is used to optimize the composite-laminated spring. The optimized leaf spring is then fabricated by the hand layup method. It was found that the spring with composite graduated leaf resulted in 40% reduction in weight than the spring with steel graduated leaf. Similarly, the stress concentration and deformation values are reduced by 76.39% and 50% in comparison with those of steel graduated leaf. The composite-laminated spring showed better damping property and also resulted in less transmission of force to the chassis of the vehicle. The noise induced by the composite-laminated spring is also reduced in comparison with steel graduated leaf. Finally, a composite-laminated spring is found to be lighter in weight and with better noise, vibration, and harshness in comparison with steel graduated leaf. Thus, it is found to be best suited for an electric vehicle.