Condition monitoring and diagnosis of automobile engine
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Description
The early detection of the malfunctions and faults is crucial for performance and reliability of automobiles. In the last millennium, the existing automobile on-board diagnosis systems were incapable of diagnosing some faults such as loss of engine compression, plug-not-firing and carburettor. This set of faults is very important to be detected, and more so that, automobile systems of the future will be autonomous and a self driven system with little or no human interventions. A new condition monitoring approach that uses the sense of smell was investigated to diagnose the faults of plug-not-firing, loss of compression and carburettor fault. An electronic nose based condition monitoring hardware and software was developed to obtain a smell print of the exhaust fumes of an automobile gasoline engine in different operating conditions. This work presents results of experiments based on the data obtained (1400 x 10 data samples each for ten (10) fault classes) from the developed condition monitoring scheme for gasoline fuelled automobile engine using four different algorithms.
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Product details
- Paperback | 232 pages
- 152 x 229 x 13mm | 345g
- 11 May 2012
- LAP LAMBERT Academic Publishing
- Saarbrucken, Germany
- English
- Aufl.
- 3659120766
- 9783659120763
About Arulogun Oladiran Tayo
The Author is a Senior Lecturer in the Department of Computer Science and Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria. He graduated with B.Tech. Computer Engineering (1998), M.Sc. Electrical/Electronic Engineering (2004) and Ph.D. Computer Science (2008).
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