An EMD-Based Filtering Algorithm for the Fiber-Optic SPR Sensor

Abstract

We present a filtering algorithm based on empirical mode decomposition (EMD) for the data demodulation of the fiber-optic surface plasmon resonance (SPR) sensor. After data preprocessing by the EMD-based filtering algorithm, three methods are compared to obtain the valley wavelength of the SPR. The results show that by using the Gaussian-fitting method, the smallest standard deviation is obtained. Based on the proposed algorithm, the related temperature sensor based on fiber-optic SPR gets the sensitivity of 335.7 pm/°C at 20 °C and 626.9 pm/°C at 99 °C, resulting in temperature resolutions of 0.06 °C at 20 °C and 0.03 °C at 99 °C via the spectrometer resolution of 20 pm.