KEYWORDS: Energy harvesting, Resonators, Complex systems, Algorithms, Electromagnetism, Differential equations, Monte Carlo methods, Civil engineering, Genetic algorithms, Power supplies
Vibration is an available source of energy to supply electrical power demand of the freight wagons as it is one the most important challenges in railway engineering. Here we propose an efficient bistable mechanism with linear power take-off and nonlinear stiffness for energy harvesting of freight wagon vibrations. Design parameters of the bitable systems is optimized by genetic algorithm (GA) and simulated annealing (SA) to extract maximum power. It is shown that remarkable enhancement can be achieved in comparison with conventional linear energy harvesters. The reason for this enhancement is harmonic oscillation between stable equilibrium points of the system which is very well matched with the nature of random excitation exerted by the rail irregularities.
Low reliability and high maintenance cost of using power and data cables are two main reasons motivating the application of the self-powered wireless sensors for structural health monitoring (SHM) systems in bridge structures. On the other hand, energy harvesting systems have been introduced as a solution for the current limitations of the batterypowered wireless sensors associated with the finite life-span of batteries and their replacements. The objective in this paper is to propose a new optimized nonlinear energy harvesting concept, namely Bistable Energy Harvesting (BEH) system, for smart SHM of bridge structures. In this study, a dynamic analysis of the energy harvesting system for cablesupported bridges subject to wind-induced vibration is carried out and the feasibility of the energy harvesting device is investigated. This paper presents efficient linear and nonlinear energy harvesting systems for wireless monitoring of long-span cable-supported bridges. It is shown that level of the extracted energy from such energy harvesting system is quite sufficient to supply energy for self-powered sensors of a bridge health monitoring system. This study is to promote the recent line of research on self-powered sensor networks for smart bridge monitoring being performed at the Florida International University.
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