涡扇发动机故障诊断的快速原型设计

鲁峰; 黄金泉; 孔祥天

涡扇发动机故障诊断的快速原型设计

1.
南京航空航天大学能源与动力学院, 南京 210016
2.
中国航空工业集团公司航空动力控制系统研究所, 江苏无锡 214063

基金项目: 南京航空航天大学科研业务费(NS2010042)

计量
- 文章访问数: 1530
- HTML浏览量: 6
- PDF量: 633
- 被引次数: 0
出版历程
- 收稿日期: 2011-06-27
- 修回日期: 2011-09-13
- 刊出日期: 2012-02-28

Rapid prototype design for turbo-fan engine fault diagnosis

1.
College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2.
Aviation Motor Control System Institute, Aviation Industry Corporation of China, Wuxi Jiangsu 214063, China

摘要

摘要: 提出一种基于发动机基线模型的面向气路故障诊断的快速原型设计方法.考虑到基于模型的发动机全包线范围的故障诊断方法需要有较高精度的模型,选择合适的换算参数对已有的相似变换参数进行修正,建立适用于全包线的发动机基线模型,设计基于加权最小二乘算法的故障诊断模型,并将其写入至CompactRIO构建了发动机故障诊断的快速原型.通过对某型涡扇发动机试验表明:该种故障诊断的快速原型设计方法是有效的.
- 涡扇发动机 /
- 故障诊断 /
- 快速原型 /
- 加权最小二乘算法 /
- CompactRIO
Abstract: In order to meet the requirements of turbo-fan engine fault diagnosis,a kind of rapid prototype simulation design way based on the baseline of the engine for gas-path fault diagnosis was proposed.Considering the precision of the fault diagnosis in the flight envelope influenced by the engine baseline,optimal transformation index was selected in simulation transformation for the setup of baseline.The weighted least-squares algorithm was used to design the fault diagnosis model,which was downloaded to National Instrument (NI) CompactRIO to form rapid prototype simulation system.A series of test experiments on a turbo-fan engine show the effectiveness of this rapid prototype design method for gas-path fault diagnosis.
- turbo-fan engine /
- fault diagnosis /
- rapid prototype /
- weighted least-squares /
- CompactRIO

HTML

参考文献(13)

[1]	Michael P,Rubyca J.A prognostics and health management roadmap for information and electronics-rich systems[J].Microelectronics Reliability,2010,50(3):317-323.
[2]	Jaw L C,Friend R.ICEMS:a platform for advanced condition-based health management //IEEE Aerospace Conference Proceedings. :IEEE,2001:2909-2914.
[3]	Doel D L.Interpretation of weighted-least-squares gas path analysis results[J].Transactions of the ASME,2005,125(3):624-633.
[4]	Romessis C,Kamboukos P,Mathioudakis K.The use of probabilistic reasoning to improve least squares based gas path diagnostics.J.Eng.Gas Turbines Power,2007,129(4):970(7 pages).
[5]	Deppe M,Zanella M,Robrecht M,et al.Rapid prototy- ping of real-time control laws for complex mechatronic systems:a case study[J].The Journal of Systems and Software,2004,70(3):263-274.
[6]	张天宏,王继业.微型涡轮发动机快速原型控制系统[J].航空动力学报,2007,22(2):274-279. ZHANG Tianhong,WANG Jiye.A rapid prototype control system for micro turbine engine[J].Journal of Aerospace Power,2007,22(2):274-279.(in Chinese)
[7]	朱野,王旭永,陶建峰,等.实时控制系统平台xPC与LabVIEW接口分析及应用[J].上海交通大学学报,2008,42(2):266-269. ZHU Ye,WANG Xuyong,TAO Jianfeng,et al.Analysis and utilization of interface between xPC target and LabVIEW[J].Journal of Shanghai Jiaotong University,2008,42(2):266-269.(in Chinese)
[8]	Michael J.Engine health monitoring system for advanced diagnostic monitoring for gas turbine engines.AFRL-PR-WP-TR-1998-2120,1998.
[9]	Koop W.The integrated high performance turbine engine technology program.ISABE 97-7175,1997.
[10]	鲁峰,黄金泉,孔祥天.基于变权重最小二乘法的发动机气路故障诊断[J].航空动力学报,2011,26(10):2376-2381. LU Feng,HUANG Jinquan,KONG Xiangtian.Gas-path fault diagnosis for aero-engine based on variable weighted least-squares[J].Journal of Aerospace Power,2011,26(10):2376-2381.(in Chinese)
[11]	Doel D L.TEMPER:a gas-path analysis tool for commercial jet engines[J].Eng. Gas Turbines Power,Trans. ASME,1994,116(1):82-89.
[12]	Michael B,Mitch W,Tommy B,et al.Evaluating real-time platforms for aircraft prognostic health management using hardware-in-the-loop.AFRL-RZ-WP-TP-2009-2156,2009.
[13]	艾延廷,马业鹏,王志.基于LabVIEW的航空发动机远程监测系统设计[J].仪器仪表学报,2006,27(6):1820-1837. AI Yanting,MA Yepeng,WANG Zhi.Design of remote monitor system of aeroengine based on LabVIEW[J].Chinese Journal of Scientific Instrument,2006,27(6):1820-1837.(in Chinese)