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EWSHM-6
Damage Detection Using Robust Fuzzy Principal Component Analysis
Damage Detection Using Robust Fuzzy Principal Component Analysis [1564]
Автор(ы): F. Gharibnezhad, L.E. Mujica, J. Rodellar, C.-P. Fritzen
Количество страниц: 8
Год: 2012
Аннотация[273 КБ] 
Код: 10764
Описание
6th European Workshop on Structural Health Monitoring. Dresden. Germany. 2012. Report. In this work Robust Fuzzy Principal Component Analysis (RFPCA) is used and compared with comparing with classical Principal Component Analysis (PCA) to detect and classify damages. It has been proved that the RFPCA method achieves better result mainly because it is more compressible than classical PCA and also carries more information, hence not only it can distinguish the healthy structure from the damaged structure much sharper than the traditional counterparts but also in some cases traditional PCA is incapable of discerning the pristine from damaged structure. This work involves experimental results using pipe-like structure powered by a piezoelectric actuators and sensors.
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