基于改进DPSO算法的航空发动机失谐叶片排序  

Optimization on Mistuned Blades Sorting Based on Improved Discrete Particle Swarm Optimization Algorithm in Aero-Engine

作　　者：李岩[1] 袁惠群[1,2] 

机构地区：[1]东北大学机械工程与自动化学院,沈阳110004 [2]东北大学理学院,沈阳110004

出　　处：《振动．测试与诊断》2013年第S1期149-153,227,共6页Journal of Vibration,Measurement & Diagnosis

基　　金：国家高技术研究发展计划("八六三"计划)资助项目(2006AA04Z408);国家自然科学基金资助项目(51275081)

摘　　要：通过叶片模态实验获得叶片失谐参数建立了动力学模型。在标准粒子群算法中引入遗传算法的交叉算子和变异算子以及遗传选择,保留了粒子群算法收敛较快的特性,增加种群的多样性,改善了粒子群的全局寻优能力,并得到比其他优化算法精度更高的排序结果。研究表明,选择适当的叶片排布顺序可以有效降低叶盘系统受迫振动幅值、减轻系统振动局部化程度,采用提出的离散粒子群算法(discrete particle swarm optimization,简称DPSO)进行叶片排布可以使叶盘系统振动幅度较小或者在可接受范围内。Aero-engine bladed-disk system of blade mistuning bladed disc seriously affected the vibration characteristics of the system and the whole aviation engine performance and service life of aero-engine rotor blade, so the installation scheme is a difficulty in the engine production and repair engineering. Through the modal experiment of blade mistuning parameters to obtain the dynamic model is established. Blade of aviation engine scheduling problem belongs to NP complete problem, in this paper, the standard particle swarm algorithm into genetic algorithm crossover operator and mutation operator of genetic selection and thought, retained the particle swarm algorithm with faster convergence of the excellent characteristic,increase the diversity of the population, improved particle swarm global optimizing ability, and get more than other optimization algorithm accuracy higher ranking results. Research shows that: the selection of appropriate blade arrangement sequence can effectively reduce the bladed-disk system forced vibration amplitude, vibration reducing system localization degree, by use of the proposed discrete genetic particle swarm algorithm can make the blade arrangement of bladed disk system vibration amplitude is small or within acceptable range.

关 键 词：失谐叶片 叶片排布 减振 离散粒子群算法 

分 类 号：V232.4[航空宇航科学与技术—航空宇航推进理论与工程] TP18[自动化与计算机技术—控制理论与控制工程]