北京航空航天大学学报 ›› 2004, Vol. 30 ›› Issue (06): 524-528.

• 论文 • 上一篇    下一篇

基于DTW的涡扇发动机气路故障定量诊断方法

徐波1, 唐海龙2, 李行善1   

  1. 1. 北京航空航天大学 自动化科学与电气工程学院, 北京 100083;
    2. 北京航空航天大学 能源与动力工程学院, 北京 100083
  • 收稿日期:2003-01-08 出版日期:2004-06-30 发布日期:2010-09-21
  • 作者简介:徐 波(1969-),男,湖北随州人,博士生, xuboyt@sohu.com.

DTW based quantitative fault diagnosis of gas path component in turbofan

Xu Bo1, Tang Hailong2, Li Xingshan1   

  1. 1. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
    2. School of Jet Propulsion, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
  • Received:2003-01-08 Online:2004-06-30 Published:2010-09-21

摘要: 提出了一种利用动态过程信息对气路故障进行定量诊断的新方法.采用动态时间规整(DTW, Dynamic Time Warping)技术,对动态测试样本同已知的故障模式进行相似性度量,充分利用发动机的过渡态特征信息,实现了发动机气路部件故障的定量诊断.结果表明:这种方法的漏报率和误报率低,具有很高的诊断准确性,对测量噪声和其它不确定性具有很好的鲁棒性.

Abstract: A quantitative fault diagnosis method was presented based on pattern recognition principles for gas path component in turbofan. The method consists of a preprocessing step for multivariate dynamic data, where the magnitude dependent information is standardized, and a similarity assessment step via DTW (dynamic time warping). DTW is a flexible pattern matching method used in the area of speech recognition. The method was designed to classify faults independently of inconsistencies in the operating processes of turbofan ground test-runs. Quantitative diagnosis was fulfilled by the subdivision of fault pattern database according to the fault degree of gas path component. Case studies show that the method has a low false alarm rate and a high capability in isolating faults, and moreover, it is also robust with measuring noise and other uncertainties.

中图分类号: 


版权所有 © 《北京航空航天大学学报》编辑部
通讯地址:北京市海淀区学院路37号 北京航空航天大学学报编辑部 邮编:100191 E-mail:jbuaa@buaa.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发