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基于ADAMS与CPSO算法的火炮结构参数优化设计研究 被引量:2

Research on artillery structural parameter optimization based on ADAMS and CPSO algorithm
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摘要 针对火炮动力学模型是多部件、强非线性的系统,直接在ADAMS环境下对火炮结构参数进行优化,可能存在实现难度大、迭代次数过多、优化效果不明显等问题,提出了基于ADAMS与CPSO算法相结合的火炮结构参数优化设计方法.在利用Pro/E与ADAMS建立火炮虚拟样机并进行仿真试验的基础上,采用混沌粒子群算法对火炮结构参数进行优化,从而获得火炮结构参数和炮口扰动优化结果.根据优化值与初始值的对比分析,证明了文中所提优化设计方法合理可行. Considering artillery to be a multi-component dynamic model and strongly nonlinear system, traditional optimization method which was directly used in the ADAMS environment to optimize the structural parameters of artillery would encounter many obstacles such as the excessive number of iterations, the optimization effect is not obvious and so on. Therefore, the optimization for artillery structural parameters based on ADAMS and CPSO algorithm was proposed. The virtual prototype of artillery was set up by Pro/E and ADAMS, simulation experimentation was executed subsequently. On this condition, chaotic particle swarm algorithm was used to optimize the structural parameters, optimization effect was obvious. According to the comparation between optimization results and initial value, the method is practically validated.
出处 《工程设计学报》 CSCD 北大核心 2012年第4期278-282,共5页 Chinese Journal of Engineering Design
基金 国家自然科学基金资助项目(50645019)
关键词 火炮 虚拟样机 炮口扰动 CPSO算法 参数优化 artillery virtual prototype muzzle disturbance CPSO algorithm parameter optimization
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  • 1ANDERSON Meneses, MARCELO Dornellas, ROBERTO Schirru. Particle swarm optimization applied to the nuclear reload problem of a pressurized water reactor[J]. Progress in Nuclear Energy, 2009, 51(2) : 319- 326.
  • 2SHI Y, EBERHART R. Empirical study of particle swarm optimization[C]. International Conference on Evolutionary Computation. Washington, USA, 1999.. 1945-1950.
  • 3崔凯波.基于炮口扰动最小化的火炮结构参数优化方法研究[D].石家庄:军械工程学院火炮工程系,2010:47-49.

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