Multi-objective design of an FBG sensor network using an improved Strength Pareto Evolutionary Algorithm

To improve the multiplexing capability is a key issue in designing a wavelength division multiplexing (WDM) fiber Bragg grating (FBG) sensor network. In this paper, we present a novel FBG sensor network design based on Pareto-based multi-objective optimization technology. In contrast to conventional WDM network, the proposed network model permits the spectral response to overlap each other. The multi-objective function is established by taking two objectives into account. One objective is to minimize the total source bandwidth occupation of the sensor system to improve the multiplexing capability, and the other is to minimize the overlap degree of spectra to reduce the wavelength measurement error. The improved Strength Pareto Evolutionary Algorithm (SPEA2) is applied to search for the so-called Pareto front. One appropriate solution is selected from the non-dominated solutions to determine the Bragg wavelength assignment. Numerical results show that the proposed approach is effective in saving the bandwidth occupation and maintaining the measurement accuracy simultaneously.