M.S. (Master of Science)
Department of Mechanical Engineering
Mechanical engineering; Machinery--Vibration; Manufacturing processes--Technological innovations; Machinery--Monitoring--Technological innovations
Production and manufacturing technologies related companies are more and more opting for condition based maintenance of their machines. The condition based maintenance requires a monitoring system which collects the data from the machines through the sensors placed in them. This data can be analyzed for any deterioration of the components of the machine so the maintenance of those components can be done before catastrophic failure. Traditional approach of maintenance based on fixed time intervals may be cost ineffective. It may be noted that the trend of decreasing cost for sensors and data storage led to collection of inordinate amount of data. This posed the challenge of so called data analytics. This thesis involves data analytics for machinery condition monitoring. A machinery fault simulator instrumented with vibration sensors will be used to collect the data to be used for data analytics. NI LabVIEW and VisualBasic are mainly used for the analysis of the deteriorating performance of the components.
Sirimalla, Sunil, "Data analytics for machinery vibration" (2015). Graduate Research Theses & Dissertations. 2044.
Northern Illinois University
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