Structural health monitoring of heterogeneous materials using damage index methods and piezoelectric sensors

The high strength to weight ratio and stiffness tailoring characteristics of composite materials has enormous potential in many vehicle sectors and aerospace industries. The reliability of these materials has been hindered by the lack of effective health monitoring systems capable of detecting damage occurrence in fiber-reinforced plastic. Unlike homogenous material, heterogeneous materials such as composite laminates generate interlaminar failure which is indicative of delamination. A concise understanding of the response characteristics of delamination on smart composite structures is necessary for predicting the occurrence of damage. The objective of this research is to develop a methodology for characterizing the existence, location, and extent of damage in laminate composite panels of arbitrary thickness using modal response methods and piezoelectric sensing techniques.;First, a damage index based on modal strain is developed to characterized the dynamic response of laminated composite plates of arbitrary thickness with discrete multiple delaminations. The effectiveness of the newly developed damage index is examined by comparing to previously developed damage indices. The damage index is demonstrated numerically and experimentally on composite panels of various stacking sequences, thickness, and damage sizes. Modal strains are captured from the composite panels using strain gauges with a Labview program.;Piezoelectric sensors are used in structural health monitoring systems. An optimization procedure using a modified Genetic Algorithm (GA) is developed to detect discrete delamination in the vulnerable area of composite plates using distributed piezoelectric sensors. The analysis uses a Monte Carlo method to generate the initial population. The optimization solutions are verified by numerical simulations as well as with experiments conducted using customized piezoelectric sensors.;Limited research is conducted to characterize structural changes using piezoelectric sensors in the presence of damaged sensors. This work proposes a method of detecting delamination and sensor failure using the voltage signal data from dynamic composite panels using Principal Component Analysis (PCA). The proposed method identifies structural changes and distinguishes the change as a sensor failure and a delamination. The strength of the proposed method is quantified using the confusion matrix approach with multiple simulations.