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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/11111
Title: Condition Monitoring for Rotational Machinery
Authors: Volante, Daniel C.
Advisor: Mohrenschildt, Martin v.
Khedri, R.
Leduc, R.
Department: Computing and Software
Keywords: condition monitoring;rotational machinery;vibrating screens;vibration analysis;fault diagnoses;waveform analysis;Computational Engineering;Computational Engineering
Publication Date: Oct-2011
Abstract: <p>Vibrating screens are industrial machines used to sort aggregates through their high rotational accelerations. Utilized in mining operations, they are able to screen dozens of tonnes of material per hour. To enhance maintenance and troubleshooting, this thesis introduces a vibration based condition monitoring system capable of observing machine operation. Using acceleration data collected from remote parts of the machine, software continuously detects for abnormal operation triggered by fault conditions. Users are to be notified in the event of a fault and be provided with relevant information.</p> <p>Acceleration data is acquired from a set of sensor devices that are mounted to specified points on the vibrating screen. Data is then wirelessly transmitted to a centralized unit for digital signal processing. Existing sensor devices developed for a previous project have been upgraded and integrated into the monitoring system. Alternative communication technologies and the utilized Wi-Fi network are examined and discussed.</p> <p>The condition monitoring system's hardware and software was designed following engineering principles. Development produced a functional prototype system, implementing the monitoring process. The monitoring technique utilizes signal filtering and processing to compute a set of variables that reveal the status of the machine. Decision making strategies are then employed as to determine when a fault has occurred.</p> <p>Testing performed on the developed monitoring system has also been documented. The performance of the prototype system is examined as different fault scenarios are induced and monitored. Results and descriptions of virtual simulations and live industrial experiments are presented. The relationships between machine faults and detected fault signatures are also discussed.</p>
URI: http://hdl.handle.net/11375/11111
Identifier: opendissertations/6105
7131
2213454
Appears in Collections:Open Access Dissertations and Theses

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