Title:
Multi-feature signature analysis for bearing condition monitoring using neural network methodology
Multi-feature signature analysis for bearing condition monitoring using neural network methodology
| dc.contributor.advisor | Tavakoli, Massoud S. | |
| dc.contributor.author | Cease, Barry T. | en_US |
| dc.contributor.department | Mechanical Engineering | en_US |
| dc.date.accessioned | 2008-01-24T12:33:59Z | |
| dc.date.available | 2008-01-24T12:33:59Z | |
| dc.date.issued | 1992-12 | en_US |
| dc.description.degree | M.S. | en_US |
| dc.identifier.bibid | 364230 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1853/19328 | |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.rights | Access restricted to authorized Georgia Tech users only. | en_US |
| dc.subject.lcsh | Vibration | en_US |
| dc.subject.lcsh | Neural networks (Computer science) | en_US |
| dc.subject.lcsh | Artificial intelligence | en_US |
| dc.title | Multi-feature signature analysis for bearing condition monitoring using neural network methodology | en_US |
| dc.type | Text | |
| dc.type.genre | Thesis | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | George W. Woodruff School of Mechanical Engineering | |
| local.contributor.corporatename | College of Engineering | |
| relation.isOrgUnitOfPublication | c01ff908-c25f-439b-bf10-a074ed886bb7 | |
| relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 |
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