On the Classification of Gasoline-fuelled Engine Exhaust Fume Related Faults Using Electronic Nose and Principal Component Analysis

Abstract

The efficiency and effectiveness of every equipment or system is of paramount concern to both the manufacturers and theend users, which necessitates equipment condition monitoring schemes. Intelligent fault diagnosis system using patternrecognition tools can be developed from the result of the condition monitoring. A prototype electronic nose that uses array ofbroadly tuned Taguchi metal oxide sensors was used to carry out condition monitoring of automobile engine using itsexhaust fumes with principal component analysis (PCA) as pattern recognition tool for diagnosing some exhaust relatedfaults. The results showed that the following automobile engine faults; plug-not-firing faults and loss of compression faultswere diagnosable from the automobile exhaust fumes very well with average classification accuracy of 91%.Key words: Electronic nose, Condition Monitoring, Automobile, Fault, Diagnosis, PCA.