Optimization of Rotor Mechanical Properties Parameters Based on Particle Swarm Algorithm

Article Preview

Abstract:

In order to improve the mechanics properties of the rotor components at ultra-high load steady acceleration conditions, the significant factors to the rotor mechanics properties, which include the ellipsoid axis length, minor axis length, rotor speed and gyration radius of holes, are taken as the optimizing objects, the extreme stress, strain extremes, moment of inertia of rotor are optimized as the targets. Then optimization models of the rotor mechanics parameters are established, and the multi-objective optimization method of rotor mechanics properties is proposed based on particle swarm. The results show that the mechanics properties of the rotor were significantly improved using the optimize method.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

493-498

Citation:

Online since:

August 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] ATWELL A R, OKOJIE R S, KORNEGAY K T. Simulation, fabrication and testing of bulk micromachined 6H-SiC high-g piezoresistive accelerometers[J]. Sensors and Actuators A : Physical, 2003, 104(1):11-18.

DOI: 10.1016/s0924-4247(02)00436-3

Google Scholar

[2] HE Zong-ying1, XIE Feng-juan1, GUO Min1, LI Min-sheng. Acceleration Measurement Technology in High Energy Shock Environment Test[J]. Journal of Gun Launch&Control. 2010, 30(3): 329-333.(In Chinese).

Google Scholar

[3] SHI Yun-bo, ZHU Zheng-qiang, LIU Xiao-peng, DU Kang, LIU Jun.Design and impact analysis of a high g accelerometer [J].Explosion and Shock Waves. 2010 (1): 85-88. (In Chinese).

Google Scholar

[4] JIA Puzhao. The design of a steady state acceleration simulation test equipment- centrifuge [J]. Spacecraft Environment Engineering. 2009, 26(1): 88-103. (In Chinese).

Google Scholar

[5] Kennedy J, Eberhart R. Particle swarm optimization[C]. IEEE International Conference on Neural Networks. Perth. 1995: 1942-(1948).

Google Scholar

[6] SHEN ji, HAN Lichuan, SHEN Yibin. Optimization of Airplane Primary Parameters Based on Particle Swarm Algorithm [J]. Acta Aeronautica ET Astronautica Sinica, 2008, 29(6): 1538-1542. (In Chinese).

Google Scholar

[7] GUO Yuanyuan, WANG qian, LIANG Feng. Facility layout design based on particle swarm optimization[J]. Computer Integrated Manufacturing Systems, 2012, 18(11): 1-6. (In Chinese).

Google Scholar

[8] LIU haijiang, HUANG wei. Computer Numerical Control Machining Parameter Optimization Based On Particle Swarm Optimization [J]. Journal of Tongji University, 2009, 36(6): 803-806. (In Chinese).

Google Scholar