基于非支配排序遗传算法的涡轮发动机转子系统装配参数优化

doi:10.3969/j.issn.1000-1093.2021.05.022

摘要/Abstract

摘要： 为探究保障转子系统高温动平衡的最佳装配参数方法，掌握高温下动平衡的变化规律，提出转子系统各零件装配角矩阵的优化确定方法。基于高温工况下热-结构动平衡理论模型和零件材料特性随温度的非线性变化规律，建立转子系统动平衡随温度变化的解析方程；根据不同装配参数下系统不平衡量和偏移扭矩的差异，把高温动平衡优化问题转换为多目标多变量的优化问题，给出基于非支配排序遗传算法的解决方案；以某弹用涡轮发动机高压转子系统装配为例，在600 ℃工作环境下对所提方法进行验证，得到该工况下零件最佳装配角矩阵，以及最小化温度对转子系统动平衡的变化量影响，改善了装配质量特性。结果表明，零件装配角对高温工况下转子系统动平衡变化有很大的影响，通过装配参数优化可显著减少高温工况对多零件转子系统动平衡的影响。

关键词: 涡轮发动机, 转子系统, 装配角, 不平衡量, 偏移扭矩, 非支配排序遗传算法

Abstract: An optimization determination method of different matrices of assembly angle was proposed to explore the optimal method for assembly process parameters to guarantee the dynamic balance of rotor system and grasp the changing law of dynamic balance at high temperature. According to the thermal-structure dynamic balance theory model at high temperature and the nonlinear change of material characteristics with temperature, a analytical equation is established for calculating the temperature change of dynamic balance of rotor system with temperature at high temperature. Then, according to the difference between system unbalance and offset torque under the different assembly parameters, the NSGA-Ⅱbased solution is presented by converting the high temperature dynamic balance optimization into multi-objective and multivariable optimization. Taking the assembly of high-pressure rotor system of a missile turbine engine as an example, the proposed method was verified in 600 ℃ working environment, and the optimal assembly angle matrix was obtained, which minimizes the influence of high temperature on the dynamic balance of rotor system and improves the assembly quality. The results show that the assembly angles have great influence on the dynamic balance of rotor system at high temperature, and the influence of high temperature conditions on the dynamic balance of multi-part rotor system can be significantly reduced through the optimization of assembly parameters.

Key words: turboengine, rotorsystem, assemblyangle, unbalance, offsettorque, non-dominatedsortinggeneticalgorithm

中图分类号:

TJ760.5

冯睽睽，张发平，王武宏，张文杰，张田会. 基于非支配排序遗传算法的涡轮发动机转子系统装配参数优化[J]. 兵工学报, 2021, 42(5): 1092-1100.

FENG Kuikui， ZHANG Faping， WANG Wuhong， ZHANG Wenjie， ZHANG Tianhui. Assembly Process Parameters Optimization of Turbine Engine Rotor System Based on Non-dominated Sorting Genetic Algorithm[J]. Acta Armamentarii, 2021, 42(5): 1092-1100.

参考文献

［1］陈立芳, 王维民, 高金吉. 航空发动机自动平衡技术发展综述[J]. 航空动力学报, 2019, 34(7):1530-1541.
CHEN L F, WANG W M, GAO J J. Summary on the development of auto-balancing technology of aero-engine[J]. Journal of Aerospace Power, 2019, 34(7):1530-1541. (in Chinese)
[2］丛培田, 曹松松, 张振厚, 等. 干式涡旋真空泵的动平衡工艺与振动品质研究[J]. 真空科学与技术学报, 2016, 36(6): 613-617.
CONG P T, CAO S S, ZHANG Z H, et al. Dynamic balance and vibration suppression of dry scroll vacuum pump [J]. Chinese Journal of Vacuum Science and Technology, 2016, 36(6): 613-617. (in Chinese)
[3］丁锋, 栗祥, 韩帅. EEMD与NRS在涡桨发动机转子故障诊断中的应用[J]. 航空动力学报, 2018, 33(6):1423-1431.
DING F, LI X, HAN S. Application of EEMD and NRS in turboprop engine rotor fault diagnosis[J]. Journal of Aerospace Power, 2018, 33(6):1423-1431. (in Chinses)
[4］游令非, 张建国, 周霜, 等. 航空发动机限寿件疲劳可靠度计算新方法[J]. 航空学报, 2019, 40(12):109-120.
YOU L F, ZHANG J G, ZHOU S, et al. A new method for calculating fatigue reliability of life limiting parts of aero-engine [J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(12):109-120. (in Chinese)
[5] 程英辉, 崔静波, 项青春, 等.转子动平衡中试加重量和位置与振幅和相位关系的研究[J]. 冶金动力, 2019(9):69-70.
CHENG Y H, CUI J B, XIANG Q C, et al. A study on the relationship between trial weight/position and vibration amplitude/phase in dynamic balance of rotor [J]. Metallurgical Power, 2019(9): 69-70. (in Chinese)
[6] 张军. 硬盘动不平衡测量和校正方法研究[D]. 哈尔滨：哈尔滨工业大学, 2016.
ZHANG J.Research of dynamic unbalance detection and adjustment method in HDDs [D]. Harbin： Harbin Institute of Techno- logy, 2016. (in Chinese)
[7] 何振. 风机动平衡无试重校正方法研究[D]. 哈尔滨：哈尔滨工业大学,2018.
HE Z. Method of dynamic balance without trial weights of draught fan [D]. Harbin： Harbin Institute of Technology, 2018. (in Chinese)
[8] 蒲芃成, 张剀, 于金鹏, 等. 力自由不平衡控制下的高速磁悬浮飞轮系统在线动平衡[J]. 光学精密工程, 2017, 25(7): 1796-1806.
PU F C, ZHANG K, YU J P, et al. On-line balancing of high- speed magnetic suspended fly wheel system under force free control of imbalance [J]. Optics and Precision Engineering, 2017,
25(7): 1796-1806. (in Chinese)
[9] 张仕海. 高速机床主轴内置式双面在线动平衡装置及关键技术研究[D]. 北京：北京工业大学,2012.
ZHANG S H. Research on built-in, double-face online dynamic balance device for high-speed spindle and its key technologies [D]. Beijing：Beijing University of Technology, 2012. (in Chinese)
[10] SONG L K, BAI G C, FEI C W. Dynamic surrogate modeling approach for probabilistic creep-fatigue life evaluation of turbine disks [J]. Aerospace Science and Technology， 2019, 95:105439.
[11] 房友龙, 刘永葆, 贺星. 离心力作用下涡轮转子的径向变形[J]. 舰船电子工程, 2011, 31(2):177-180.
FANG Y L, LIU Y B, HE X. Study of the radial elongations of the turbine rotor with the centrifugal effect [J]. Ship Electronic Engineering, 2011, 31(2):177-180. (in Chinese)
[12] 王水霞, 张璞, 张金娜. 热载荷下叶轮变形仿真分析[J]. 风机技术, 2015, 57(6):54-59.
WANG S X, ZHANG P, ZHANG J N. Simulation analysis on distortion of centrifugal impellers under thermal load [J]. Chinese Journal of Turbomachinery, 2015, 57(6):54-59. (in Chinese)
[13］ DECAIX J, BALARAC G, DREYER M, et al. RANS and LES computations of the tip-leakage vortex for different gap widths [J]. Journal of Turbulence, 2015, 16(4): 309-341.
[14] 骆清国, 赵耀, 桂勇, 等. 基于多种群协同进化免疫多目标优化算法的百叶窗优化研究[J]. 兵工学报, 2019, 40(4): 689-696.
LUO Q G, ZHAO Y, GUI Y, et al. Research on optimization of louvered fin with hybrid multi-objective optimizations based on EDA and AIS [J]. Acta Armamentarii, 2019, 40(4): 689-696. (in Chinese)
[15］吕国俊,曹建军,郑奇斌,等.基于多目标蚁群优化的单类支持向量机相似重复记录检测[J].兵工学报,2020,41(2): 324-331.
L G J, CAO J J, ZHENG Q B, et al. Detection of similar duplicate records based on OCSVM and multi-objective ant colony optimization[J].Acta Armamentarii,2020,41(2): 324-331.(in Chinese)
[16］ WANG S,ALI S,YUE T, et al.Integrating weight assignment strategies with NSGA-II for supporting user preference multiobjective optimization[J].IEEE Transactions on Evolutionary Computation，2018, 22(3):378-393.
[17］ ZHOU W P, YANG J F, LIU M Q. Optimal maximin L2-distance Latin hypercube designs [J]. Journal of Statistical Planning and Inference，2020, 207:113-122.
[18］ Hossein Nourianfar, Hamdi Abdi. Solving the multi-objective economic emission dispatch problems using fast non-dominated sorting TVAC-PSO combined with EMA [J]. Applied Soft Computing Journal，2019, 85:105770.
[19］张浩为, 谢军伟, 张昭建, 等. 基于混合自适应遗传算法的相控阵雷达任务调度[J]. 兵工学报, 2017, 38(9): 1761-1770.
ZHANG H W, XIE J W, ZHANG Z J, et al. Task scheduling of phased array radar based on hybrid adaptive genetic algorithm[J].Acta Armamentarii, 2017, 38(9):1761-1770. (in Chinese)

[1]	刘子昌, 李思雨, 裴模超, 刘洁, 孟硕, 吴巍屹. 基于纹理分析的柴油发动机故障诊断方法[J]. 兵工学报, 2024, 45(2): 684-694.
[2]	汤润之, 班利明, 钱乐, 雷争军, 宋卫星. 资源受限条件下车辆维修工序调度优化[J]. 兵工学报, 2021, 42(9): 2032-2039.
[3]	李伊，张发平，阎艳，张田会，周建华，郭飞燕. 基于工艺因素统计量化的多工序制造质量建模[J]. 兵工学报, 2020, 41(7): 1408-1416.