Model-based Sensor Fault Detection and Isolation for X-By-Wire Vehicles Using a Fuzzy Logic System with Fixed Membership Functions

2007 ◽  
Author(s):  
Pierre-Francois Quet ◽  
Mutasim Salman
Keyword(s):  
Fuzzy Logic ◽  
Fault Detection ◽  
Fuzzy Logic System ◽  
Fault Detection And Isolation ◽  
Membership Functions ◽  
Sensor Fault ◽  
Model Based ◽  
Sensor Fault Detection ◽  
Logic System

scholarly journals Integral Sensor Fault Detection and Isolation for Railway Traction Drive

Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1543 ◽  
Author(s):  
Fernando Garramiola ◽  
Jon del Olmo ◽  
Javier Poza ◽  
Patxi Madina ◽  
Gaizka Almandoz
Keyword(s):  
Fault Detection ◽  
Fault Detection And Isolation ◽  
Sensor Fault ◽  
Traction Drive ◽  
Railway Traction ◽  
Sensor Fault Detection

scholarly journals Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of a Baseline System

2008 ◽  
Author(s):  
Takahisa Kobayashi ◽  
Donald L. Simon
Keyword(s):  
Fault Detection ◽  
Aircraft Engine ◽  
Fault Detection And Isolation ◽  
Channel Measurements ◽  
Sensor Fault ◽  
Engine Model ◽  
Dual Channel ◽  
Sensor Fault Detection ◽  
Baseline System ◽  
On Line

In this paper, a baseline system which utilizes dual-channel sensor measurements for aircraft engine on-line diagnostics is developed. This system is composed of a linear on-board engine model (LOBEM) and fault detection and isolation (FDI) logic. The LOBEM provides the analytical third channel against which the dual-channel measurements are compared. When the discrepancy among the triplex channels exceeds a tolerance level, the FDI logic determines the cause of the discrepancy. Through this approach, the baseline system achieves the following objectives: 1) anomaly detection, 2) component fault detection, and 3) sensor fault detection and isolation. The performance of the baseline system is evaluated in a simulation environment using faults in sensors and components.

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