Damage detection using robust fuzzy principal component analysis

Abstract

In this work Robust Fuzzy Principal Component Analysis (RFPCA) is used and\ncompared with comparing with classical Principal Component Analysis (PCA) to\ndetect and classify damages. It has been proved that the RFPCA method achieves\nbetter result mainly because it is more compressible than classical PCA and also\ncarries more information, hence not only it can distinguish the healthy structure from\nthe damaged structure much sharper than the traditional counterparts but also in some\ncases traditional PCA is incapable of discerning the pristine from damaged structure.\nThis work involves experimental results using pipe-like structure powered by a\npiezoelectric actuators and sensors.