1. Experimental investigation on electrostatic monitoring technology for civil turbofan engine
- Author
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Huijie Mao, Yibing Yin, Hongfu Zuo, Jing Cai, Hongsheng Yan, and Yu Fu
- Subjects
Engineering ,lcsh:Mechanical engineering and machinery ,Acoustics ,Thrust ,02 engineering and technology ,Propelling nozzle ,Impulse (physics) ,01 natural sciences ,Turbine ,Automotive engineering ,010305 fluids & plasmas ,sensor ,electrostatic monitoring ,exhaust ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,lcsh:TJ1-1570 ,General Materials Science ,business.industry ,Mechanical Engineering ,turbofan engine ,Turbofan ,Rubbing ,performance parameter ,Lubrication ,Curve fitting ,020201 artificial intelligence & image processing ,business - Abstract
This study analyzes the necessity, development, and principles of aero-engine electrostatic monitoring technology. An electrostatic sensor with specific size is assembled in the exhaust nozzle of an RB-211 turbofan engine located near the low-pressure turbine outlet, a stress checking procedure for safety is conducted. Two test program cycles are included in the whole experimental process. Electrostatic signal processing flow is presented, and feature parameters used for analysis are root-mean-square (RMS), activity level (AL), negative event rate (NER), positive event rate (PER), kurtosis, impulse factor, and absolute mean value. Thrust is used to parameterize the working conditions of the turbofan engine. Moreover, data fitting is conducted to determine the relations between feature and performance parameters. Accordingly, lubrication oil leakage fault and fuel-rich combustion condition are detected in two test run cycles, which result in the appearance of abnormal signals. The AL, RMS, and absolute mean values exhibit similar trends with the change in thrust. A positive linear correlation is also observed between the AL and the thrust in the varying thrust test period. The method of blade-casing rubbing fault recognition is discussed. Experiment results show that the electrostatic sensor is very sensitive to large-sized charged particles in the exhaust emissions.
- Published
- 2017