KEYWORDS: Principal component analysis, Visualization, Data modeling, Statistical modeling, Temperature metrology, Structural health monitoring, Sensors, Statistical analysis, Environmental sensing, Aluminum
This paper explores the use of Principal Component Analysis (PCA), an extended form of PCA and, the T2-statistic and Q-statistic; distances that detect and distinguish damages in structures under varying operational
and environmental conditions. The work involves an experiment in which two piezoelectric transducers are
bonded on an aluminium plate. The plate is subjected to several damages and exposed to different levels of
temperature. A series of tests have been performed for each condition. The approach is able to determine
whether the structure has damage or not, and besides, gives qualitative information about its size, isolating
effects of the temperature.
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