基于改进粒子群算法的航空发动机性能综合评价  

Comprehensive Evaluation of Aeroengine Performance Based on Improved PSO

作　　者：赵凯[1] 李本威[1] 李冬[1] 李海宁[2] 

机构地区：[1]海军航空工程学院飞行器工程系,山东烟台264001 [2]大连理工大学船舶工程学院CAD工程中心,辽宁大连116024

出　　处：《航空发动机》2014年第6期13-17,共5页Aeroengine

基　　金：国家自然科学基金(青年基金)(61102167)资助

摘　　要：针对基于单参数评估发动机性能能力不足的问题,研究了利用多参数综合评估发动机性能的方法;通过对某型发动机台架试车数据分析,确定了使用综合加权法评估发动机性能比算术加权平均法更具合理性;分别利用改进的遗传算法和粒子群优化算法计算多参数的权值,对比结果表明:使用改进的粒子群算法在计算精度和速度上均优于遗传算法。同时还计算了各翻修次数下发动机的性能指标。To solve the lack of ability problem for evaluate engine performance based on single parameter,the method of evaluating engine performance based on multiple parameters was studied.By analyzing the bench test data for an aeroengine,the results show that the synthetic weighted method was more rational than arithmetic weighted mean method for evaluating engine performance.Weights of multiple parameters were calculated by the improved genetic algorithm and particle swarm optimization algorithm.The comparative study shows that the improved particle swarm algorithm is superior to the improved genetic algorithm in the calculation result.Finally,the engine performance index of each overhaul was calculated.

关 键 词：多参数权值 综合评判 遗传算法 粒子群算法 航空发动机 

分 类 号：V235.13[航空宇航科学与技术—航空宇航推进理论与工程]