用自适应粒子群算法求解自激脉冲喷嘴结构参数模型

›› 2012, Vol. ›› Issue (06): 1415-1420.

用自适应粒子群算法求解自激脉冲喷嘴结构参数模型

周利坤^1,2, 刘宏昭¹

1. 西安理工大学机械与精密仪器工程学院, 西安 710048;
2. 武警工程大学装备运输系, 西安 710086

收稿日期:2011-09-15 出版日期:2012-11-01
通讯作者: 刘宏昭(1954-),男,教授,博士生导师.研究方向:机械系统动力学及控制,机构设计.E-mail:liuhongzhao@xaut.edu.cn E-mail:liuhongzhao@xaut.edu.cn
基金资助:
国家火炬计划基金项目(07C26213711606);陕西省重点学科建设专项基金项目(102-00X903).

Soving the self-excited pulsed nozzle structural parameters of the model by adaptive particle swarm algorithm

ZHOU Li-kun^1,2, LIU Hong-zhao¹

1. Faculty of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China;
2. Equipment and Transportation Department, Engineering University of CAPF, Xi'an 710086, China

Received:2011-09-15 Online:2012-11-01

摘要/Abstract

摘要： 提出了用自适应粒子群优化算法求解自激脉冲喷嘴结构参数模型,以打击力输出最大为优化目标, 对其喷嘴结构参数进行优化。通过试验验证了模型和算法的性能,给出了较为精确的模型和边界约束条件。试验结果表明:所建模型是合理的,自适应粒子群优化算法求解结果与试验结果能够较好地吻合,解决了自激脉冲喷嘴设计和制造边界条件不易定性表达的问题。

关键词: 机械设计, 自激脉冲喷嘴, 结构参数模型, 自适应粒子群算法

Abstract: In order to facilitate the design and manufacture of the self-excited pulsed nozzle(SEPN), a structural parameter model was built by analyzing the structure of the nozzzle. An adaptive particle swarm optimization(APSO) algorithm was proposed to solve the model of the nozzle. Taking the maximum of the jet impact force as the target the structural parameters of SEPN were optimized. The performances of the model and the algorithm were validated by experiments, and the accurate boundary constraints of the model were obtained. The results showed that the built model is reasonable, the results calculated by APSO algorithm were in good agreement with experiment ones, solving the problem that the boundary conditions of the design and manufacture of SEPN were difficult to express qualitatively.

Key words: mechanical design, self-excited pulsed nozzle, structural parameter model, adaptive particle swarm optimization(APSO) algorithm

中图分类号:

TH137.53

周利坤, 刘宏昭. 用自适应粒子群算法求解自激脉冲喷嘴结构参数模型[J]. , 2012, (06): 1415-1420.

ZHOU Li-kun, LIU Hong-zhao. Soving the self-excited pulsed nozzle structural parameters of the model by adaptive particle swarm algorithm[J]. , 2012, (06): 1415-1420.

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