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- 2018
应用支持向量回归机探索发动机VSV调节规律
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Abstract:
摘要 发动机可调静子叶片（VSV）调节规律极其复杂，通过挖掘快速存取记录装置（QAR）数据对VSV调节规律进行了深入研究。首先，通过PW4077D发动机健康状态的QAR数据，建立基于粒子群优化（PSO）算法的支持向量回归机（SVR）模型，来探索VSV调节规律；然后，利用后续航班数据对PSO-SVR模型进行验证，并将验证结果与传统的PSO-BP神经网络模型进行对比；最后，应用PSO-SVR模型进行发动机故障诊断。研究结果表明：PSO-SVR模型的回归预测精度优于PSO-BP神经网络模型，能够准确反映VSV的调节规律。可将其用于发动机的状态监控和故障诊断，亦可为VSV控制系统设计提供参考。
Abstract：The engine variable stator vane (VSV) regulation law is extremely complex, and through mining quick access recorder (QAR) data, the VSV regulation law is studied. Firstly, the support vector regre-ssion (SVR) model based on particle swarm optimization (PSO) is established through the QAR data of PW4077D engine health condition to explore the regulation law of VSV. Then, the PSO-SVR model is validated by the subsequent flight data, and the verification results are compared with the traditional PSO-BP neural network model. Finally, the PSO-SVR model is applied to engine fault diagnosis. The results show that the regression prediction accuracy of the PSO-SVR model is better than that of the PSO-BP neural network model, and it can accurately reflect the VSV regulation rule. It can be used in the condition monitoring and fault dia-gnosis of engine, and can also provide reference for the design of VSV control system.
| [1] | 唐庆如,孔萌.CFM56-7B发动机VSV结构损伤分析[J].航空维修与工程,2011(4):31-33.TANG Q R,KONG M.Analysis of CFM56-7B VSV structural damage[J].Aviation Maintenance Engineering,2011(4):31-33(in Chinese). |
| [2] | 李世林.VSV系统对CFM56发动机喘振的影响分析[J].科学技术与工程,2011,11(20):4934-4936.LI S L.Research on VSV faults based CFM56 engine surge[J].Science Technology and Engineering,2011,11(20):4934-4936(in Chinese). |
| [3] | 殷锴,钟诗胜,那媛,等.基于BP神经网络的航空发动机故障检测技术研究[J].航空发动机,2017,43(1):53-57.YIN K,ZHONG S S,NA Y,et al.Research on aeroengine fault detection technology based on BP neural network[J].Aeroengine,2017,43(1):53-57(in Chinese). |
| [4] | 崔智全.民航发动机气路参数偏差值挖掘方法及其应用研究[D].哈尔滨:哈尔滨工业大学,2013.CUI Z Q.Civil aeroengine gas path parameter deviation mining method with application[D].Harbin:Harbin Institute of Technology,2013(in Chinese). |
| [5] | Boeing.777 aircraft maintenance manual[Z].Chicago:Boeing,2015. |
| [6] | 彭泽琰,刘刚.航空燃气轮机原理[M].北京:国防工业出版社,2000.PENG Z Y,LIU G.Principles of aviation gas turbines[M].Beijing:National Defense Industry Press,2000(in Chinese). |
| [7] | Pratt & Whitney Company.ECMⅡtraining manual[Z].Hartford:Pratt & Whitney Company,1994. |
| [8] | 周百政,曹惠玲.基于EHM软件思路的QAR数据处理[J].航空维修与工程,2010(4):60-62.ZHOU B Z,CAO H L.QAR data processing based on the method of EHM software[J].Aviation Maintenance & Engineering,2010(4):60-62(in Chinese). |
| [9] | 黄爱华.涡扇发动机可调静子叶片控制规律研究[J].燃气涡轮试验与研究,2017,30(1):48-51.HUANG A H.Control law of variable stator vane for turbofan engine[J].Gas Turbine Experiment and Research,2017,30(1):48-51(in Chinese). |
| [10] | 吴秀宽,林森.某涡扇发动机风扇进口可调导流叶片调节规律分析[C]//第五届中国航空学会青年科技论坛文集(第5集).北京:北京航空航天大学出版社,2012:227-231.WU X K,LIN S.The analyse about the control law of turbofan'IGV[C]//Proceedings of the Fifth China Aviation Society Youth Science and Technology Forum (Fifth Episodes).Beijing:Beihang University Press,2012:227-231(in Chinese). |
| [11] | 曹志鹏,刘波,丁伟.静叶角度调节对组合压气机性能优化机理[J].北京航空航天大学学报,2007,33(8):878-881.CAO Z P,LIU B,DING W.Stator setting angles adjustment on performance improvement of axial-centrifugal compressor[J].Journal of Beijing University of Aeronautics and Astronautics,2007,33(8):878-881(in Chinese). |
| [12] | 张健,任铭林.静叶角度调节对压气机性能影响的试验研究[J].航空动力学报,2000,15(1):27-30.ZHANG J,REN M L.Experimental investigation on effect of stator vane angle adjustment on compressor performance[J].Journal of Aerospace Power,2000,15(1):27-30(in Chinese). |
| [13] | 张宇飞,么子云,唐松林,等.一种基于主成分分析和支持向量机的发动机故障诊断方法[J].中国机械工程,2016,27(24):3307-3311.ZHANG Y F,YAO Z Y,TANG S L,et al.An engine fault diagnosis method based on PCL and SVR[J].China Mechanical Engineering,2016,27(24):3307-3311(in Chinese). |
| [14] | 栾圣罡.基于气路参数样本的航空发动机状态监视方法与系统研究[D].哈尔滨:哈尔滨工业大学,2008.LUAN S G.Aeroengine condition monitoring technique and system based on gas path parameter sample[D].Harbin:Harbin Institute of Technology,2008(in Chinese). |
| [15] | 刘永建.基于改进神经网络的民机发动机故障诊断与性能预测研究[D].南京:南京航空航天大学,2012.LIU Y J.Research on modified neural network for fault diagnosis and performance prediction of aeroengine[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2012(in Chinese). |
| [16] | 王芳.基于支持向量机的沪深300指数回归预测[D].济南:山东大学,2015.WANG F.CSI 300 index regression prediction based on support vector machine[D].Jinan:Shandong University,2015(in Chinese). |
| [17] | 史峰,王辉,郁磊,等.智能算法30个案例分析[M].北京:北京航空航天大学出版社,2011.SHI F,WANG H,YU L,et al.30 cases analysis of intelligent algorithm[M].Beijing:Beihang University Press,2011(in Chinese). |
| [18] | BI F R,LIU Y P.Fault diagnosis of valve clearance in diesel engine based on BP neural network and support vector machine[J].Transactions of Tianjin University,2016,22(6):536-543. |
