The optimisation research of screw conveyor. (16th August 2011)

• Record Type: Journal Article
• Authors: Cai, Jiang-hui; Meng, Wen-jun; Chen, Zhi-mei
• Is Part Of: International journal of innovative computing and applications. Volume 3:Number 3(2011)
• Page Start: 169
• Page End: 176
• Publication Date: 2011-08-16
• Subjects: particle swarm optimisation -- PSO -- parameters optimisation -- innovative computing -- screw conveyor; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Particle swarm optimisation (PSO) is a population-based stochastic optimisation technique. As a result, PSO algorithm is widely used in mechanical engineering design field. Screw conveyors are used extensively in agriculture and processing industries for elevating and/or transporting bulk materials over short to medium distances. They are very effective for conveying dry particulate solids, giving good control over the throughput. Despite their apparent simplicity, the transportation action is very complex and designers have tended to rely heavily on empirical performance data. Intelligent operation parameters optimisation for screw conveyor based on PSO is studied in this paper. This thesis takes a heavy driving drum of screw conveyor as an example, firstly, the optimisation function is built up, then the operation parameter of screw conveyor is precision optimised with PSO algorithm, which offer a foundation to design more reasonable structure for driving drum in order to meet the application demands.