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ReserarchID
H63YM
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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This paper attempted to assess the attitudes of students in
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Inclusion has become a priority on the global educational agenda,
An electronic nose-based condition monitoring of three automobile engines was conducted to obtain smell prints that correspond to normal operating conditions and various induced abnormal operating conditions. Fuzzy C-means clustering was used to ascertain the extent to which the smell prints can characterize faulty engine conditions. Silhouette diagrams and silhouette width figures were used to validate the clusters. Results obtained indicate that the smell prints do in general characterize the faults as most clusters have silhouette width greater than 0.5. In particular the results showed that the following automobile engine faults; plug-notfiring faults and loss of compression faults are diagnosable from the automobile exhaust fumes.
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