0
research-article

Symbolic Time Series Analysis of Gas Turbine Gas Path Electrostatic Monitoring Data

[+] Author and Article Information
Jianzhong Sun

College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing, China,211106
sunjianzhong@nuaa.edu.cn

Pengpeng Liu

System Engineering Research Institute China State Shipbuilding Corporation Beijing, China
liutianyu221@163.com

Yibing Yin

College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing, China,211106
yinyibing1992@163.com

Hongfu Zuo

College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing, China,211106
rms@nuaa.edu.cn

Chaoyi Li

College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing, China,211106
lichaoyi_nuaa@163.com

1Corresponding author.

ASME doi:10.1115/1.4036492 History: Received September 14, 2016; Revised March 22, 2017

Abstract

The aero engine gas path electrostatic monitoring system is capable of providing early warning of impending gas-path component faults. In the presented work, the principle of gas path electrostatic monitoring is briefly introduced. In view of the limited storage space and computation resource of the engine in-suit equipment, the fast symbolic time series analysis method is proposed to process the gas path electrostatic monitoring data for on-line fault detection. A case study is carried out on a data set acquired during a turbojet engine reliability testing program. It is fund that the proposed symbolic analysis techniques can be used to characterize the statistical patterns presented in the gas path electrostatic monitoring data under different health conditions. The proposed anomaly measure, i.e., the relative entropy derived from the statistical patterns, is confirmed to be able to indicate the gas path components faults.

Copyright (c) 2017 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In