Discrete-Event Sensor Fault Isolation With Application to an Electro-Mechanical Break System

2002 ◽  
Author(s):  
Pierluigi Pisu ◽  
Giorgio Rizzoni
Keyword(s):  
Fault Detection ◽  
Discrete Event ◽  
Vehicle Control ◽  
Fault Isolation ◽  
Fault Detection And Isolation ◽  
Control System Design ◽  
Qualitative Modeling ◽  
Sensor Fault ◽  
Sensor Fault Detection ◽  
Single Sensor

Fault detection and isolation has become one of the most important aspects in vehicle control system design. In this paper, a new method for single sensor fault detection and isolation for automotive on-board applications that combines model-based diagnostic and qualitative modeling approach is presented. A depth one algorithm for qualitative identification is given and applied to a electro-brake system.

Sensor Fault Isolation Using Qualitative Quantized Modeling With Application to a 3-DOF Nonlinear Vehicle

2004 ◽  
Author(s):  
S. D’Silva ◽  
P. Pisu ◽  
A. Serrani ◽  
G. Rizzoni
Keyword(s):  
Fault Detection ◽  
Low Cost ◽  
Discrete Event ◽  
Computational Effort ◽  
Fault Isolation ◽  
Fault Detection And Isolation ◽  
Sensor Fault ◽  
Sensor Fault Detection ◽  
On Line ◽  
Nonlinear Vehicle Model

Fault detection and isolation has become one of the most important aspects in vehicle control system design. In this paper, we present a technique for single sensor fault detection and isolation in automotive on-board applications. It combines model-based diagnostics and a qualitative modeling approach. The proposed method is appealing as it shifts the computational effort from on-line to off-line, making the algorithm suitable for low-cost real-time applications. The methodology can be cast in the framework of discrete-event fault diagnosis. A depth one transition relation algorithm for qualitative identification which guarantees completeness is developed and applied to a 3-degree-of-freedom (DOF) nonlinear vehicle model. The paper concludes with preliminary simulation results showing the effectiveness of the proposed scheme.

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.

scholarly journals Neuro-Fuzzy for Sensor Fault Detection and Isolation

2014 ◽  
Vol 90 (17) ◽  
pp. 42-46
Author(s):  
Rajendra Sharma ◽  
Snehal Kokil ◽  
Prtit Khaire
Keyword(s):  
Fault Detection ◽  
Fault Detection And Isolation ◽  
Sensor Fault ◽  
Neuro Fuzzy ◽  
Sensor Fault Detection
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