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http://hdl.handle.net/11375/16780
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DC Field | Value | Language |
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dc.contributor.advisor | Mohrenschildt, Martin | - |
dc.contributor.author | Van de Hoef, Mattias | - |
dc.date.accessioned | 2015-02-27T19:24:35Z | - |
dc.date.available | 2015-02-27T19:24:35Z | - |
dc.date.issued | 2015 | - |
dc.identifier.uri | http://hdl.handle.net/11375/16780 | - |
dc.description.abstract | Vibration analysis (VA) is an extremely valuable technology which has been around for decades but its application and deployment techniques continue to grow. In 2006 W.S. Tyler, an industrial screening company, approached the McMaster Computing and Software department in search of a VA strategy to be used in their industry. The massive screens they produce vibrate with incredible speed and force to sort various types of materials. Over the years this department has developed a successful wireless vibration analysis tool along with software to perform analysis. The current VA tool can be used to tune the screen during commissioning as well as aid in troubleshooting during or after a failure. The next evolutionary step in the advancement of the system would be to perform condition monitoring. Predictive maintenance is a relatively new concept whereby an impending machine fault or failure is detected through condition monitoring and is corrected before it occurs. Predictive maintenance is immensely beneficial and will be discussed. The focus of this thesis is on improvements to the VA system adding longer-term, progressive data collection and analysis abilities to the current tool-set. | en_US |
dc.language.iso | en | en_US |
dc.title | Prediction and Prevention of the Progressive Degradation of Mining Screens using Wireless Vibration Analysis Tools | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Software Engineering | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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thesis.pdf | Thesis | 28.95 MB | Adobe PDF | View/Open |
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