融合静电信号和气路参数的发动机性能评估方法
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摘要
为了研究静电监测技术对航空发动机的监测效果,开展了航空涡喷发动机静电监测台架实验,获得了140个完整试车阶段的静电信号数据。针对发动机传统气路性能评估方法的信息源有限的问题,提出了一种融合静电信号和气路参数的发动机性能评估流程和方法,进一步采用了基于逻辑回归模型的评估算法对发动机的综合性能进行量化评估,通过融合试车实验的静电数据和性能参数,对发动机的健康状态评价方法进行研究。结果表明:当健康值为0.9以上可以认为发动机为健康状态,当健康值小于0.3时可以认为发动机已经发生了较为严重的退化,所提出的融合评估方法要优于传统的性能参数评估方法,能够提前预警气路性能严重退化。
In order to study the effect of electrostatic monitoring technology on aero-engine,an electrostatic monitoring bench experiment is carried out on turbojet engine,and the electrostatic signal data of 140 complete testing periods are acquired. In view of the limited information source of traditional gas path performance evaluation method,a method of engine performance evaluation based on electrostatic signal and gas path parameters is proposed. The evaluation algorithm based on logistic regression model is further used to quantify the comprehensive performance of the engine evaluation,through the integration of static test data and performance test parameters,a comprehensive evaluation of the health status of the engine. The results of data analysis show that when the health value is more than 0.9,the engine can be considered healthy,and when the health value is less than 0.3,the engine can be considered to have undergone severe degradation,the proposed fusion evaluation method is superior to the traditional method of evaluating performance parameters,and can early warn the serious deterioration of the gas path performance and provide maintenance windows for maintenance personnel.
In order to study the effect of electrostatic monitoring technology on aero-engine,an electrostatic monitoring bench experiment is carried out on turbojet engine,and the electrostatic signal data of 140 complete testing periods are acquired. In view of the limited information source of traditional gas path performance evaluation method,a method of engine performance evaluation based on electrostatic signal and gas path parameters is proposed. The evaluation algorithm based on logistic regression model is further used to quantify the comprehensive performance of the engine evaluation,through the integration of static test data and performance test parameters,a comprehensive evaluation of the health status of the engine. The results of data analysis show that when the health value is more than 0.9,the engine can be considered healthy,and when the health value is less than 0.3,the engine can be considered to have undergone severe degradation,the proposed fusion evaluation method is superior to the traditional method of evaluating performance parameters,and can early warn the serious deterioration of the gas path performance and provide maintenance windows for maintenance personnel.
引文
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[15]殷逸冰,左洪福,冒慧杰,等.航空发动机进气道静电传感器空间模型解析及感应信号影响因素实验分析[J].仪器仪表学报,2015,36(4):795-803.
[16]殷逸冰,左洪福,付宇,等.某型航空涡扇发动机静电传感器机载化监测实验[J].航空动力学报,2016,31(12):3054-3063.
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[18]陈保家,陈雪峰,李兵,等. Logistic回归模型在机床刀具可靠性评估中的应用[J].机械工程学报,2011,47(18):158-164.
[2] Powrie H E G,Fisher C E. Monitoring of Foreign Objects Ingested into the Intake of a Gas Turbine Aero-Engine[C]. Seattle:International Conference on Condition Monitoring Proceedings,1999.
[3] Navarra K,Lawton R,Mccusker S,et al. An Enterprise Strategy for Implementing Conditioned-Based Maintenance Plus(CBM+)Research in the USAF[C].Washington:IEEE Aerospace Conference Proceedings,1997.
[4] Sangha M S,Yu D L,Gomm J B. On-board Monitoring and Diagnosis for Spark Ignition Engine Air Path via Adaptive Neural Networks[J]. Proceedings of the Institution of Mechanical Engineers,Part D:Journal of Automobile Engineering,2006,220(11):1641-1655.
[5] Cartwright R A,Fisher C. Marine Gas Turbine Condition Monitoring by Gas Path Electrostatic Detection Techniques[C]. Burminghan:ASME 1991 International Gas Turbine and Aeroengine Congress and Exposition,1991.
[6] Vatazhin A B,Starik A M,Kholshchevnikova E K.Electric Charging of Soot Particles in Aircraft Engine Exhaust Plumes[J]. Fluid Dynamics,2004,39(3):384-392.
[7] Vatazhin A B,Golentsov D A,Likhter V A,et al. Aircraft Engine State Nonobstructive Electrostatic Monitoring Theoretical and Laboratory Modelling[J]. Journal of Electrostiacs,1997,40(41):711-716.
[8] Wilcox M,Ransom D,Henry M,et al. Engine Distress Detection in Gas Turbines with Electrostatic Sensors[C]. Glasgow:ASME Turbo Expo 2010:Power for Land,Sea,and Air,2010.
[9]付宇.航空发动机进气道静电传感器理论与实验研究[D].南京:南京航空航天大学,2014.
[10]文振华.基于静电感应的航空发动机气路监测技术研究[D].南京:南京航空航天大学,2009.
[11]文振华,左洪福,李耀华,等.一种新的航空发动机气路监测方法[J].南京航空航天大学学报,2009,41(2):248-252.
[12]文振华,左洪福,王华,等.航空发动机气路静电监测传感器特性[J].传感器与微系统,2008,27(11):28-31.
[13]李耀华,左洪福,文振华,等.航空发动机气路颗粒静电监测技术模拟实验[J].航空学报,2009,30(4):604-608.
[14]文振华,左洪福.基于独立分量分析的航空发动机气路静电信号处理方法[J].机械科学与技术,2011,30(11):1872-1876.
[15]殷逸冰,左洪福,冒慧杰,等.航空发动机进气道静电传感器空间模型解析及感应信号影响因素实验分析[J].仪器仪表学报,2015,36(4):795-803.
[16]殷逸冰,左洪福,付宇,等.某型航空涡扇发动机静电传感器机载化监测实验[J].航空动力学报,2016,31(12):3054-3063.
[17]雷金波.基于逻辑回归和支持向量机的设备状态退化评估与趋势预测研究[D].上海:上海交通大学,2008.
[18]陈保家,陈雪峰,李兵,等. Logistic回归模型在机床刀具可靠性评估中的应用[J].机械工程学报,2011,47(18):158-164.