Characteristics analysis and optimization design of bridge crane based on improved particle swarm optimization algorithm

Abstract

Large redundant metal structures have high stability with large cost. An excellent mechanical structure should have the lower weight when satisfying its stability. Aiming at the large redundancy of the main beam metal structure of the double-beam bridge crane, the paper extracts six important parameters to determine its quality, and the corresponding value is set. The orthogonal test table is designed to calculate the strength and stiffness. In order to avoid resonance, the fixed vibration frequency and excitation frequency are calculated. The experimental results are fitted to obtain the six parameters of the quality, strength, stiffness, and natural frequency. Moreover, particle swarm optimization algorithm is used to solve the multi-objective optimization mathematical model with the design quality as the goal and the stiffness, strength, and easy resonance interval as constraints. In view of the long calculation time and poor convergence of particle swarm optimization algorithm, a module that limits the particle forward speed is added and the generation conditions of particles are redefined. The improved particle swarm algorithm shows that the first-order vibration frequency of the main beam increases from 18 Hz to 27.55 Hz. It improves the stability of the overall structure and avoids resonance with the motor frequency. Under the condition of satisfying the stability of the main beam, the quality of the main beam is reduced from 1.23 tons to 0.53 tons, with a reduction of 6%.