Matching Optimization of Ship Engine and Propeller Based on PSO-GA Algorithm

Abstract:

Matching performance of ship engine and propeller has a significant impact on marine propulsion efficiency. In this paper, a hybrid approach combining particle swarm optimization (PSO) and genetic algorithms (GA) is developed for matching optimization of ship engine and propeller. Based on ship theory, the matching performance of ship engine and propeller is analyzed. Considering the diameter, angular speed, picth ratio and disk ratio of propeller, a mathematical model is constructed in which the open-water propeller efficiency is taken as the objective function for matching optimization of ship engine and propeller. Integrating PSO with GA is presented to solve it, in which the mutation operator of GA is introduced to the PSO for the diversity of particles. The effectiveness of the approach is illustrated by a matching optimization example of ship engine and propeller.

• Periodical: Applied Mechanics and Materials (Volumes 121-126)
• Pages: 4503-4507
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.121-126.4503
• Online since: October 2011
• Authors: Li Ren, Wen Xiao Zhang
• Keywords: Genetic Algorithm (GA), Matching Optimization, Particle Swarm Optimization Algorithm (PSO), Ship Engine, Ship Propeller

References

[1] G. Kuiper. New developments and propeller design. Journal of Hydrodynamics. 2010, 22(5): 7-15.

[2] A. G. Chen, J. W. Ye. Research on the genetic neural network for the computation of ship resistance. Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing. (2009).

DOI: 10.1109/cinc.2009.34

[3] J. B. Sun, C. Guo and X. Zhang. Research on modeling and simulation of large marine propulsion plant. Journal of system simulation. 2007, 19 (3): 465-469.

[4] Y. Hu, R. P. Zhou and J. G. Yang. Research on software implementation method of matching propulsion engine to propeller. International Conference on Computational Intelligence and Software Engineering. (2010).

DOI: 10.1109/cise.2010.5676847

[5] F. Qin, Z.G. Zhang, B. Yang, etc. Genetic algorith based optimization design for match of ship engine and propeller. Journal of Wuhan University of Technology. 2003, 27(1): 50-52.

[6] A.H. Liu, S. D. Fan. The research on the matching design of the ship-engine-propeller based on multi-objective particle swarm optimization. 2nd International Workshop on Intelligent Systems and Applications, (2010).

DOI: 10.1109/iwisa.2010.5473726

[7] Y. T. Kao, E. Zahara. Applied Soft Computing, 2008, 8: 849-857.

[8] W. F. Abd-EI-Wahed, A. A. Mousa, M. A. Journal of Computational and Applied Mathematics, 2011, 235: 1446-1453.