Abstract

This work shows a pressure-sensitive platform instrumented with a set of five in-series macro-bend optical fiber sensors. The structure of ${20} \times {20}\;\text{cm}$ is divided into sixteen ${5} \times {5}\;\text{cm}$ sensing cells. Sensing is based on the wavelength-dependent intensity changes in the array transmission visible spectrum, which carries information about the pressure acting on the structure. Data analysis uses principal component analysis to reduce spectral data to 12 principal components that explain 99% of the data variance and $k$-nearest neighbors classification and support vector regression methods. The capability of pressure detection with fewer sensors than the number of monitored cells was demonstrated with an accuracy of 94% for predicting the pressure location and a mean absolute error of 0.31 kPa within 3.74–9.98 kPa range.

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