%0 Journal Article
	%A S. Sendhil Kumar and  M. Senthil Kumar
	%D 2015
	%J International Journal of Civil and Environmental Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 104, 2015
	%T Application of Artificial Neural Network in the Investigation of Bearing Defects
	%U https://publications.waset.org/pdf/10003247
	%V 104
	%X Maintenance and design engineers have great concern
for the functioning of rotating machineries due to the vibration
phenomenon. Improper functioning in rotating machinery originates
from the damage to rolling element bearings. The status of rolling
element bearings require advanced technologies to monitor their
health status efficiently and effectively. Avoiding vibration during
machine running conditions is a complicated process. Vibration
simulation should be carried out using suitable sensors/ transducers to
recognize the level of damage on bearing during machine operating
conditions. Various issues arising in rotating systems are interlinked
with bearing faults. This paper presents an approach for fault
diagnosis of bearings using neural networks and time/frequencydomain
vibration analysis.
	%P 1121 - 1124