F. Pozo, Y. Vidal, et al.

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EACS 2016 Paper No. 175Growing interest for improving the reliability of safety-critical structures, such as wind turbines, has led to the advancement of structural health monitoring (SHM). Existing techniques for fault detection can be broadly classified into two major categories: model-based methods and signal processing-based methods. This work focuses in the signal-processing-based fault detection by using principal component analysis (PCA) as a way to condense and extract information from the collected signals. In particular, the goal of this work is to select a reduced number of sensors to be used. From a practical point of view, a reduced number of sensors installed in the structure leads to a reduced cost of installation and maintenance. Besides, from a computational point of view,...
Mechanical engineering not elsewhere classified
EACS2016
fault detection
sensor selection
principal component analysis
FAST
wind turbine
Mechanical Engineering

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