Numerical Improvement for the Mechanical Performance of Bikes Based on an Intelligent PSO-ABC Algorithm and WSN Technology

Abstract

This paper proposed a novel hybrid optimization algorithm, particle swarm optimization-artificial bee colony (PSO-ABC), based on the PSO and ABC algorithms. The ABC algorithm can offset defects in the PSO algorithm that easily fall into a local optimization; combining the algorithms can improve the optimization ability of the PSO algorithm to a certain extent. Therefore, this paper applied the PSO-ABC hybrid algorithm and the finite-element method to systematically optimize the mechanical performance of the disc rotor of a bike and verified the numerical computation model via the wireless sensor network technology. The experimental test was completed with wireless sensor network technologies. To verify the optimized effects of the proposed PSO-ABC hybrid algorithm after parameter selection, the algorithm was compared with the traditional PSO and ABC models. The PSO, ABC, and PSO-ABC models adopted the same population to conduct a multi-objective optimization for vibration accelerations of the disc rotor. Comparing the results from these models proved that the proposed PSO-ABC method is superior for the optimization of vibration characteristics of the disc rotors.