Bootstrap Method for Detecting Damage in Carbon Fiber Reinforced Plastic Using a Macro Fiber Composite Sensor

Abstract

CFRP has been used in aircraft structures for decades. Although CFRP is light, its lamination is its main weakness. We have developed a new method to increase the probability of detecting delamination in carbon fiber reinforced plastic (CFRP) by narrowing the confidence interval of the changes in natural frequency. The changes in the natural frequency in delaminated CFRP are tiny compared with measurement errors. We use the bootstrap method, a statistical technique that increases the estimation accuracy from small samples, for detecting damage in CFRP. The natural frequency was measured using a macro fiber composite sensor to investigate the efficiency of the method. The results show that the confidence intervals of the natural frequency are improved by using the bootstrap method.