Fault Detection Based on Probabilistic Robustness Techniques for Belt Conveyor Systems
| Authors: | Sader Mario, Lausitz University of Applied Sciences, Germany
Noack René, Lausitz University of Applied Sciences, Germany
Zhang Ping, University of Duisburg - Essen, Germany
Ding Steven X., University of Duisburg - Essen, Germany
Jeinsch Torsten, IAV GmbH, Germany |
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| Topic: | 6.2 Mining, Mineral & Metal Processing |
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| Session: | Technology in Mining and Metal Processing Industry |
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| Keywords: | Modelling; Simulation; Fault detection; Probabilities integration; Uncertain linear systems; Information systems |
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Abstract
In this paper, problems and application of the computation of false alarm rate (FAR) and threshold for belt conveyor systems are studied. Based on an information system which is developed to meet the requirements on monitoring and fault detection for large scale belt conveyor systems, the probability distribution of model uncertainty is assumed to be known and will be taken into account for the design of the fault detection system . The use of the probabilistic information will get a less conservative result, compared with the worst case handling of the system uncertainties. The solution and the application on the belt conveyor system will be illustrated.
