A novel approach to fibre Bragg grating spectra processing is proposed. The method is based on the use of nonlinear filtration and raising the spectrum value to the second power. A combination of geometric and arithmetic mean filtering is used as nonlinear filtration. The properties of the denoising method are presented on simulation data with different signal-to-noise ratios and on experimental data. The most advantageous combination is raising the intensity of the spectrum to the square power preceded by its significant smoothing. The centroid, fast phase correlation, and cross-correlation methods are used to determine the wavelength shift in the spectrum. To obtain experimental data, measurements of the FBG in reflection mode placed in a temperature chamber with the possibility of temperature control are obtained. The simulations, measurements, and their numerical analysis confirm the usefulness of the proposed methods for demodulating the wavelength shift of FBG spectra.

Fibre Bragg gratings are one of the most popular sensors with a huge number of applications. Their most important advantage is signal modulation consisting in shifting the spectrum in the wavelength domain. Determining the wavelength shift is the most important issue in precise measurements of various quantities. New demodulation methods are constantly being developed. Many of them have good properties, but they do not gain much polarity. This is partly due to their high complexity and partly to a small improvement in the accuracy of determining the wavelength shift in relation to classical methods. Cumulative preprocessing is a very simple method of spectrum processing with the property of reducing the influence of noise on the result. The method can be used directly or with additional algorithms. In this article, we demonstrate the advantages of this method and the possibilities of combining it with other signal processing methods. We show that this method is much simpler than the spectrum denoising methods and additionally simplifies the next stage of the algorithm, i.e., determining the wavelength shift itself.

This paper presents a heurestic zero-dimensional model of a PEM-type fuel cell including dynamic states. The model is based on the static energy characteristics of the cell as the function of the voltage generated from the current drawn from the cell. The model was supplemented with a moduls of inertia under load change and cleaning process. The phenomenon of cell efficiency decrease under the influence of water accumulation on the cathode side and purging of the cell controlled by purging and short-circuiting was also taken into account. The simulation and research results for the Horizon 300W fuel cell are shown. Measurements and simulations were compared to demonstrate the model's high accuracy