DocumentCode
738306
Title
Ball bearing damage detection using traditional signal processing algorithms
Author
Bediaga, I. ; Mendizabal, X. ; Arnaiz, Aitor ; Munoa, Jokin
Volume
16
Issue
2
fYear
2013
fDate
4/1/2013 12:00:00 AM
Firstpage
20
Lastpage
25
Abstract
Fault detection and diagnosis of ball bearings has always been a challenge when monitoring rotating machinery. Specifically, bearing diagnostics have seen extensive research in the field of fault detection and diagnosis. This article reviews traditional algorithms used to detect and diagnose faulty bearings in heavy-duty milling machine tool spindle heads. Different kinds of faults have been created deliberately on the bearings of a test spindle head. The prediction effectiveness of several detection methods are tested when faults are in different stages of development.
Keywords
ball bearings; condition monitoring; fault diagnosis; machine tool spindles; mechanical engineering computing; milling machines; signal processing; ball bearing damage detection; fault detection; fault diagnosis; heavy-duty milling machine tool spindle heads; rotating machinery monitoring; signal processing; Ball bearings; Demodulation; Frequency measurement; Frequency modulation; Resonant frequency; Transforms; Vibrations;
fLanguage
English
Journal_Title
Instrumentation & Measurement Magazine, IEEE
Publisher
ieee
ISSN
1094-6969
Type
jour
DOI
10.1109/MIM.2013.6495676
Filename
6495676
Link To Document