3 April 2009 Extended PCA visualisation of system damage features under environmental and operational variations
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Abstract
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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Luis E. Mujica, José Rodellar, Josep Vehí, Keith Worden, Wieslaw Staszewski, "Extended PCA visualisation of system damage features under environmental and operational variations", Proc. SPIE 7286, Modeling, Signal Processing, and Control for Smart Structures 2009, 72860L (3 April 2009); doi: 10.1117/12.815488; https://doi.org/10.1117/12.815488
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KEYWORDS
Principal component analysis

Data modeling

Visualization

Statistical modeling

Temperature metrology

Sensors

Statistical analysis

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