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| Modeling and Simulation of Spiral Stirrer for Asphalt Conveyor Based on Hybrid PSO Algorithm |
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Abstract: To overcome the difficulty of modeling for agitation characteristics of spiral stirrer for asphalt conveyor, a Neural Network (NN) model was established, based on both pitch and radius of helical blade being used as the input vector, with the rate of mixture segregation used as the output vector of NN. To avoid the shortcomings of the Back Propagation (BP) algorithm and the Particle Swarm Optimization (PSO) algorithm, a hybrid PSO algorithm PSOLM was employed as the learning algorithm of NN, which was combined with Levenberg-Marquardt (L-M) algorithm. To avoid the slow search speed reated with the global optimum in the PSO-BP algorithm, a heuristic way was adopted to give a transition from the particle swarm search to L-M search. Simulation experiment was performed with model experiment for asphalt conveyor. The results of simulation and experiment show that the proposed approach not only has faster convergence and higher computational precision than the original PSO, but also can overcome the drawbacks of BP algorithm. It is also a new and effective approach for model building of spiral stirrer agitation characteristics.
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Received: 02 November 2009
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Corresponding Authors:
Zhangping YOU
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2010, Vol. 28 
