A novel self-learning fault detection system for gas turbine engines

1996 ◽  
Author(s):  
V.C. Patel
Keyword(s):  
Fault Detection ◽  
Gas Turbine ◽  
Detection System ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Self Learning

Autonomously Learning Fault Detection System for Gas Turbine Engines

1997 ◽  
Vol 30 (18) ◽  
pp. 85-90 ◽  
Author(s):  
V.C. Patel ◽  
V. Kadirkamanathan ◽  
H.A. Thompson
Keyword(s):  
Fault Detection ◽  
Gas Turbine ◽  
Detection System ◽  
Turbine Engines ◽  
Gas Turbine Engines

scholarly journals Symbolic Dynamic Analysis of Transient Time Series for Fault Detection in Gas Turbine Engines

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
Soumalya Sarkar ◽  
Kushal Mukherjee ◽  
Soumik Sarkar ◽  
Asok Ray
Keyword(s):  
Time Series ◽  
Fault Detection ◽  
Gas Turbine ◽  
Symbolic Dynamic ◽  
Turbine Engines ◽  
Test Case ◽  
Gas Turbine Engines ◽  
Transient Time ◽  
Steady State Time ◽  
Dynamic Filtering

This brief paper presents a symbolic dynamics-based method for detection of incipient faults in gas turbine engines. The underlying algorithms for fault detection and classification are built upon the recently reported work on symbolic dynamic filtering. In particular, Markov model-based analysis of quasi-stationary steady-state time series is extended to analysis of transient time series during takeoff. The algorithms have been validated by simulation on the NASA Commercial Modular Aero Propulsion System Simulation (C-MAPSS) transient test-case generator.

Sign in / Sign up

Export Citation Format

Share Document