Integration Issues for Vehicle Level Distributed Diagnostic Reasoners 2013-01-2294
In today's aircraft the diagnostic and prognostic systems play a crucial part in aircraft safety while reducing the operating and maintenance costs. Aircraft are very complex in their design and require consistent monitoring of systems to establish the overall vehicle health status. Most diagnostic systems utilize advanced algorithms (e.g. Bayesian belief networks or neural networks) which usually operate at system or sub-system level. The sub-system reasoners collect the input from components and sensors to process the data and provide the diagnostic/detection results to the flight advisory unit. Several sources of information must be taken into account when assessing the vehicle health, to accurately identify the health state in real time. These sources of information are independent system-level diagnostics that do not exchange any information/data with the surrounding systems. This limits the system by preventing cross check or health status information exchange amongst the related sub-systems. This article discusses the issues related to the integration of a vehicle level diagnostic reasoner to sub-system level reasoners and information exchange between the sub-system reasoners and the vehicle level reasoner.
Citation: Khan, F., Jennions, I., and Sreenuch, T., "Integration Issues for Vehicle Level Distributed Diagnostic Reasoners," SAE Technical Paper 2013-01-2294, 2013, https://doi.org/10.4271/2013-01-2294. Download Citation
Author(s):
Faisal Khan, Ian Jennions, Tarapong Sreenuch
Affiliated:
Cranfield University, IVHM Centre Cranfield University
Pages: 5
Event:
SAE 2013 AeroTech Congress & Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Neural networks
Aircraft
Diagnostics
Prognostics
Sensors and actuators
Mathematical models
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