Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCA.2009.5410578
Title: Predictive modelling of the monitoring function. A predictive modelling application for fault states in a manufacturing system
Authors: Minca, E.
Racoceanu, D. 
Dragomir, O.
Stefan, V.
Dragomir, F.
Keywords: Data bases approaches
Failure
Fault tree
FT analysis
Fuzzy detection
Fuzzy logic
Fuzzy reasoning
Prediction
Predictive maintenance
Reliability engineering
T-temporized petri nets
Issue Date: 2009
Citation: Minca, E., Racoceanu, D., Dragomir, O., Stefan, V., Dragomir, F. (2009). Predictive modelling of the monitoring function. A predictive modelling application for fault states in a manufacturing system. 2009 IEEE International Conference on Control and Automation, ICCA 2009 : 1487-1492. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCA.2009.5410578
Abstract: A new tool for non-autonomous hierarchical systems modelling is proposed in this article. This tool is used for the modelling of monitoring functions and integrates the fuzzy logic in the temporal aspect of the events occurrence. The tool is also suited for the development of the hierarchical and distributed typologies structures and in modelling of recurrent functions. The proposed hierarchical systems are structured on hierarchical levels. On each level there are events with equal probabilities of occurrence/detection. The proposed typologies ensure a recurrent behaviour to the horizontal firing of the networks, which allows the detection of the occurrence/persistence of the monitored external events. In this context, the Recurrent Synchronized Fuzzy Petri Nets (PNetSinFREC) are well adapted to detection/decision modelling of the functions by a temporized fuzzy transition approach in hierarchical systems. ©2009 IEEE.
Source Title: 2009 IEEE International Conference on Control and Automation, ICCA 2009
URI: http://scholarbank.nus.edu.sg/handle/10635/40500
ISBN: 9781424447060
DOI: 10.1109/ICCA.2009.5410578
Appears in Collections:Staff Publications

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