DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING
Permanent URI for this communityhttps://repository.ui.edu.ng/handle/123456789/478
Browse
Item Diagnosis of gasoline-fuelled engine exhaust fume related faults using electronic nose(2010) Arulogun, O. T; Waheed, M. A.; Fakolujo, O. A.; Omidora, E. O.; Olaniyi, O. M. O. M.Fault diagnosis, isolation and restoration from failure are crucial for maintenance and reliability of equipment. In this paper, a condition monitoring approach that uses the sense of smell was investigated to diagnose ignition and loss of compression faults in gasoline-fuelled engine. An electronic nose based condition monitoring system was used to obtain smell print of the exhaust fumes of an automobile gasoline engine in different normal and faulty operating conditions. The data were analyzed with fuzzy c-means, hybrid principal component analysis and artificial neural network. Fuzzy C- means clustering was used to ascertain the extent to which the smell prints can characterize the selected engine faulty and normal conditions. Silhouette diagrams and silhouette width figures were used to validate the clusters. The faults considered were all correctly classified by hybrid principal component analysis and artificial neural network algorithm with 100% accuracy.Item A framework for electronic nose based condition monitoring and diagnosis of automobile engine faults.(Nigeria Computer Society, 2009) Arulogun, O. T; Fakolujo, O. A.; Waheed, M. A.; Omidiora, E. O.; Olaniyi, O. M.A framework for condition monitoring approach that uses the sense of smell was investigated to diagnose the faults of plug-not-firing, loss of compression and carburettor faults from the exhaust fumes of gasoline fuelled automobile engine. An electronic nose based condition monitoring hardware and software was developed using the framework to obtain smell prints that correspond to normal operating conditions and various induced abnormal operating conditions. Fuzzy C-means and K means clustering were used as exploratory data visualization tools to ascertain if the obtained smell prints from the developed system could characterize the faults considered. The results of exploratory cluster analysis showed that the obtained smell print could typify the faults considered.Item Intelligent fire detection system using mobile wireless network(2010) Arulogun, O. T; Fakolujo, O. A; Olaniyi, O. M.; Ganiyu, R. A.; Okediran, O.To protect lives and valuables against colossal loss due to fire outbreak in any society, provision of proper safty measures is sine qua non. This has been achieved through installation of adequate fire extinquisher in strategic visible places, installation of smoke sensors and provision of human security personnel.These methods are not only cost prohibitive, but most times fail to provide required hazard preventive measures at appropraite time. In this paper, we present an intelligent photoelectric fire detection system to provide prompt and adequate notification mechanisms to the occupants and relevant authorities about possible outbreak of fire via existing mobile wireless networks. The result from the implemented model shows how intelligent photoelectric fire detection system can help minimize possible consequences from the risk of fire outbreak.