Condition monitoring and diagnosis of automobile engine

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.

Autorentext

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).