Experience in developing system requirements specification for a sensor failure detection and identification scheme

2002 ◽  
Author(s):  
D. Del Gobbo ◽  
M. Napolitano ◽  
J. Callahan ◽  
B. Cukic
Keyword(s):  
Failure Detection ◽  
Requirements Specification ◽  
Sensor Failure ◽  
Identification Scheme ◽  
Detection And Identification ◽  
System Requirements ◽  
Developing System

A Decentralized Multiple Model Adaptive Filtering for Discrete-Time Stochastic Systems

1989 ◽  
Vol 111 (3) ◽  
pp. 371-377 ◽  
Author(s):  
Keigo Watanabe
Keyword(s):  
Discrete Time ◽  
Kalman Filtering ◽  
Adaptive Filtering ◽  
Stochastic Systems ◽  
Failure Detection ◽  
Multiple Model ◽  
Sensor Failure ◽  
Lateral Dynamics ◽  
Detection And Identification ◽  
Partial Element

A decentralized multiple model adaptive filter (MMAF) is proposed for linear discrete-time stochastic systems. The structure of decentralized multiple model studied here is based on introducing a global hypothesis for the global model and a local hypothesis for the local model, where it is assumed that the former hypothesis includes the latter one as a partial element. Algorithms for the decentralized MMAFs in unsteady and steady-state are derived using recent results in decentralized Kalman filtering. The results can be applied in designing a system for sensor failure detection and identification (FDI). An example is included to illustrate the characteristics of such a FDI system for the estimation of lateral dynamics of the hydrofoil boat.

Statistical Analysis of SHM Passive Sensing Systems

2015 ◽  
Vol 665 ◽  
pp. 241-244
Author(s):  
Marco Thiene ◽  
Zahra Sharif Khodaei ◽  
M.H. Aliabadi
Keyword(s):  
Statistical Analysis ◽  
Health Monitoring ◽  
Sensor Failure ◽  
Impact Detection ◽  
Sensing Systems ◽  
Detection And Identification ◽  
Passive Sensing ◽  
Service Load ◽  
Reliability And Robustness ◽  
Load Conditions

Structural Health Monitoring (SHM) techniques have gained an increased interest to be utilised alongside NDI techniques for aircraft maintenance. However, to take the SHM methodologies from the laboratory conditions to actual structures under real load conditions requires them to be assessed in terms of reliability and robustness. In this work, a statistical analysis is carried out for a passive SHM system capable of impact detection and identification. The sensitivity of the platform to parameters such as noise, sensor failure and in-service load conditions has been investigated and reported.

Failure detection and identification

1989 ◽  
Vol 34 (3) ◽  
pp. 316-321 ◽  
Author(s):  
M.-A. Massoumnia ◽  
G.C. Verghese ◽  
A.S. Willsky
Keyword(s):  
Failure Detection ◽  
Detection And Identification
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