Health Monitoring of Polymer Matrix Composites Using Vibration Technique

Abstract

Glass and carbon fiber-reinforced plastics have become increasingly popular in engineering applications as relatively new materials, and it is expected that this trend will continue. E-glass laminates have become more common in aviation components such as wings, fuselages, and stabilizers as stronger, more durable, and tougher resins such as epoxies have evolved. A sudden breakdown of an engineering component like aircraft usually results in a significant financial loss, as well as posing a risk to human life. Vibration-based detection is one type of global damage identification method. Changes in physical qualities like damping, mass, and stiffness bring noticeable changes in the modal parameters in vibration-based damage detection approaches. This chapter demonstrates how vibration-based analysis can be used to forecast the severity and position of delamination in composites. The position and area of delamination in composite beams are determined using a supervised feed-forward multilayer back-propagation artificial neural network (ANN) in the MATLAB neural network toolbox.