Automatic Applications of Diagnostic Conditionaing Monitoring

Abstract

This project is sponsored by GenRad, a leading supplier of vehicle diagnostic and service information solutions for complex electrical and electronic systems in the automotive and aerospace industries. The long term goal is to create more sophisticated diagnostic systems that incorporate signal processing of noise/vibration signals and that can provide global diagnostic information (i.e. fuse information derived from multiple sources). The aim of this project is to test the feasibility of using neural networks and belief nets for condition monitoring and fault diagnosis in the automotive industry. Neural networks are used for signal processing at the individual sensor level, and Bayesian belief nets are used for reasoning about the predictions made by individual neural networks.

Publication DOI: https://doi.org/10.48780/publications.aston.ac.uk.00021551
Divisions: College of Engineering & Physical Sciences
Additional Information: Copyright © Tremblin, C, 1999. Tremblin, C asserts their moral right to be identified as the author of this thesis. This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with its author and that no quotation from the thesis and no information derived from it may be published without appropriate permission or acknowledgement. If you have discovered material in Aston Publications Explorer which is unlawful e.g. breaches copyright, (either yours or that of a third party) or any other law, including but not limited to those relating to patent, trademark, confidentiality, data protection, obscenity, defamation, libel, then please read our Takedown Policy and contact the service immediately.
Institution: Aston University
Uncontrolled Keywords: diagnostic conditioning monitoring,information engineering,automatic
Last Modified: 01 May 2025 12:47
Date Deposited: 19 Mar 2014 12:20
Completed Date: 1999
Authors: Tremblin, C.

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