航空发动机吸入颗粒物静电感应特性的模拟实验及分析
收稿日期: 2014-05-04
修回日期: 2014-05-24
网络出版日期: 2014-06-11
基金资助
国家自然科学基金与中国民航联合资助基金重点项目(60939003);国家自然科学基金(51105344);航空科学基金(2012ZB55003)
Electrostatic induction characteristics of aeroengine inhaled particles: simulated experiment and analysis
Received date: 2014-05-04
Revised date: 2014-05-24
Online published: 2014-06-11
Supported by
National Natural Science Foundation of China and the General Administration of Civil Aviation of China Jointly Funded Key Projects (60939003); National Natural Science Foundation of China (51105344); Aeronautical Science Foundation of China (2012ZB55003)
利用静电传感器和SC-010型环境试验箱等硬件搭建了吸入颗粒物静电监测模拟实验平台,并在此实验平台上展开了针对航空发动机吸入颗粒物静电感应特性的模拟实验研究,成功获取相应静电监测信号。实验设置颗粒材料、管道流速、颗粒粒径和颗粒投入质量4种变量作为变量条件,分别进行4组单一变量的对比实验,采集在不同颗粒材料、不同管道流速、不同颗粒粒径以及不同颗粒质量浓度环境下带电颗粒所产生的静电感应信号,对每组实验信号的活动率水平(AL)、正/负事件率(PER/NER)和绝对平均幅值等特征参数进行相应的数据分析和对比,并得到了一些有用的结论。实验发现,上述4种变量条件分别对静电感应信号的绝对时域平均幅值、AL参数、PER/NER参数有不同程度的影响。
殷逸冰 , 左洪福 , 文振华 , 蔡景 , 付宇 . 航空发动机吸入颗粒物静电感应特性的模拟实验及分析[J]. 航空学报, 2015 , 36(2) : 691 -702 . DOI: 10.7527/S1000-6893.2014.0111
A simulated experiment platform designed for inhaled particles electrostatic monitoring is constructed, electrostatic sensors and SC-010 environmental chamber are used in the construction, simulated experiments on the characteristics of electrostatic induction of aeroengine inhaled particles are carried out by this platform, and the corresponding electrostatic signals are acquired successfully. Particle material, pipe flow velocity, particle size and particle mass concentration are set as experiment variables, and four groups of contrast experiments with different single variables are conducted in sequence. The electrostatic signals are acquired under different variable conditions, which included different particle materials, pipe flow velocities, particle sizes and particle mass concentrations; each kind of electrostatic signals and its activity level (AL), positive/negative event rate(PER/NER) and absolute average amplitude are analyzed and compared in this paper; some valuable conclusions are studied. The experiments found that four kinds of variable conditions mentioned above could have different effects on AL parameter, PER/NER parameter and absolute average amplitude.
Key words: aeroengine; inlet; electrostatics sensor; inhale particles; simulated experiment
[1] Powrie H E G, Mcnicholas K. Gas path condition moni-toring during accelerated mission testing of a demonstrator engine[C]//The 33rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit. Reston: AIAA, 1997: 2904.
[2] Powrie H E G, Fisher C E. Monitoring of foreign objects ingested into the intake of a gas turbine aero-engine[C]//International Conference on Condition Monitoring Proceedings. Swansea: University of Wales, 1999: 175-190.
[3] Navarra K, Lawton R, Hearrell N. An enterprise strategy for implementing conditioned-based maintenance plus (CBM+) research in the USAF[C]//IEEE Aerospace Conference Proceedings. New York: IEEE, 1997: 177-181.
[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] Powrie H E G, Fisher C E. Engine health monitoring: Towards total prognostics[C]//IEEE Aerospace Conference Proceedings. New York: IEEE, 1999: 1112-1123.
[6] Powrie H E G, Fisher C E. Monitoring of foreign objects into the intake of a gas turbine aero-engine[C]//IEEE Aerospace Conference Proceedings. New York: IEEE, 1999: 907-920.
[7] Fisher C E. Gas path debris monitoring—a 21st century PHM tool[C]//IEEE Aerospace Conference Proceedings. New York: IEEE, 2000: 403-410.
[8] Fisher C E. Gas turbine condition monitoring systems-an integrated approach[C]//IEEE Aerospace Conference Proceedings. New York: IEEE, 2000: 633-641.
[9] Fisher C E. Data and information fusion for gas path debris monitoring[C]//IEEE Aerospace Conference Proceedings. New York: IEEE, 2001: 825-839.
[10] Novis A, Powrie H E G. PHM Sensor Implementation in the real world-a status report[C]//IEEE Aerospace Conference Proceedings. New York: IEEE, 2001: 388-393.
[11] Powrie H E G, Novis A. Gas path debris monitoring for F-35 joint strike fighter propulsion system PHM[C]//IEEE Aerospace Conference Proceedings. New York: IEEE, 2006: 314-322.
[12] Wen Z H, Zuo H F, Li Y H, et al. New method for aero engine gas path monitoring[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2009, 21(2): 248-252 (in Chinese). 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, 21(2): 248-252.
[13] Wen Z H, Zuo H F, Li Y H. Gas path debris electrostatic monitoring technology and experiment[J]. Journal of Aerospace Power, 2008, 23(12): 2321-2326 (in Chinese). 文振华, 左洪福, 李耀华. 气路颗粒静电监测技术及实验[J]. 航空动力学报, 2008, 23(12): 2321-2326.
[14] Wen Z H, Zuo H F, Wang H, et al. Characters of sensor for aero-engine gas path electrostatic monitoring[J]. Transducer and Microsystem Technologies, 2008, 27(11): 28-31 (in Chinese). 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.
[15] Wen Z H. Aero-engine gas path monitoring technology based on electrostatic induction[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2009 (in Chinese). 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.
[16] Li Y H, Zuo H F, Wen Z H, et al. Simulated experiment of aircraft engine gas path debris monitoring technology[J]. Acta Aeronautica et Astronautica Sinica, 2009, 30(4): 604-608 (in Chinese). 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.
[17] Li Y H, Zuo H F. Method for rub fault detection based on electrostatic technique: model and simulated experiment[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(6): 1156-1163 (in Chinese). 李耀华, 左洪福. 碰摩故障静电监测方法及模拟实验[J]. 航空学报, 2010, 31(6): 1156-1163.
[18] Fu Y, Zuo H F. Recognition for change-point of aero-engine components based on projective transformation[J]. Information Technology Journal, 2014, 13(2): 347-352.
[19] Fu Y, Zuo H F. Mean change-point model for aero-engine component faults[J]. Journal of Vibroengineeing, 2013, 15(4): 1627-1633.
[20] Liu P P, Zuo H F, Fu Y, et al. Exhaust gas electrostatic monitoring and gas path fault feature for turbojet engine[J]. Journal of Aerospace Power, 2013, 28(2): 473-480 (in Chinese). 刘鹏鹏, 左洪福, 付宇, 等. 涡喷发动机尾气静电监测气路故障特征[J]. 航空动力学报, 2013, 28(2): 473-480.
[21] Sun J Z, Zuo H F, Liu P P. Analysis and application of baseline model of aero-engine exhaust gas electrostatic monitoring signals[J]. Journal of Aerospace Power, 2013, 28(3): 531-540 (in Chinese). 孙建忠, 左洪福, 刘鹏鹏. 航空发动机尾气静电信号基线模型分析及应用[J]. 航空动力学报, 2013, 28(3): 531-540.
[22] Sun J Z, Zuo H F, Fu Y, et al. Analysis of factors influencing the exhaust gas electrostatic monitoring signals of a turbo-shaft engine[J]. Acta Aeronautica et Astronautica Sinica, 2012, 33(3): 709-716 (in Chinese). 孙建忠, 左洪福, 付宇, 等. 涡轴发动机尾气静电监测信号影响因素分析[J]. 航空学报, 2012, 33(3): 709-716.
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