Machinery vibration signals analysis and monitoring for fault diagnosis and process control
Dai J.1; Chen C.L.P.4; Xu X.-Y.3; Huang Y.2; Hu P.1; Hu C.-P.1; Wu T.1
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5226 LNCS
AbstractThe vibration signals contain a wealth of complex information that characterizes the dynamic behavior of the machinery. Monitoring rotating machinery is often accomplished with the aid of vibration sensors. Transforming this information into useful knowledge about the health of the machine can be challenging due to the presence of extraneous noise sources and variations in the vibration signal itself. This paper describes applying vibration theory to detect machinery fault, via the measurement of vibration and voice monitoring machinery working condition, also proposes a useful way of vibration analysis and source identification in complex machinery. An actual experiment case study has been conducted on a mill machine. The experiment results indicate that fewer sensors and less measurement and analysis time can achieve condition monitoring, fault diagnosis, and damage forecasting. Further applications allow feedback to the process control on production line. © 2008 Springer-Verlag Berlin Heidelberg.
KeywordCondition monitoring Fault detection Process control Reliability Vibration analysis
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Kunming University of Science and Technology
2.Yunnan University
3.Shanghai Maritime University
4.University of Texas at San Antonio
Recommended Citation
GB/T 7714
Dai J.,Chen C.L.P.,Xu X.-Y.,et al. Machinery vibration signals analysis and monitoring for fault diagnosis and process control[C],2008:696-703.
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