Publication Date

2016

Document Type

Dissertation/Thesis

First Advisor

Gupta, Abhijit

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Mechanical Engineering

LCSH

LabVIEW; Machinery--Vibration; Vibration--Measurement

Abstract

Machinery plays a key role for manufacturing and production companies. Most of the machines of a production company are subject to vibration signatures of one form or another. Vibration Signatures are quite often used to diagnose the health of the machines, i.e., detect problems in the machines before catastrophic failure takes place. In this thesis, first vibration data is generated using a machinery fault simulator (MFS). The piezoelectric transducers are mounted at various locations on the vibration fault simulating system to collect the data. The primary goal of this thesis deals with the data analytics to identify the source of a problem in the machine. National Instruments Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) for acquiring the data and KNIME for the statistical regression analysis are the main tools used to identify the faults which occur in the MFS.

Comments

Advisors: Abhijith Gupta.||Committee members: Pradip Majumdar; Ji-Chul Ryu.||Includes bibliographical references.||Includes illustrations.

Extent

x, 62 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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