Abstract
The multiple reconfiguration and the complexity of the modern production system lead to design intelligent monitoring aid systems. Accordingly, the use of neuro-fuzzy technics seems very promising. In this paper, we propose a new monitoring aid system composed by a dynamic neural network detection tool and a neuro-fuzzy diagnosis tool. Learning capabilities due to the neural structure permit us to update the monitoring aid system. The neuro-fuzzy network provides an abductive diagnosis. Moreover it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause. At the end, we illustrate the industrial usefulness of the proposed dynamic neuro-fuzzy monitoring system trough a flexible production system monitoring application.
| Original language | English |
|---|---|
| Pages (from-to) | 528-538 |
| Number of pages | 11 |
| Journal | Computers in Industry |
| Volume | 57 |
| Issue number | 6 |
| DOIs | |
| State | Published - Aug 2006 |
| Externally published | Yes |
Keywords
- CMMS
- Diagnosis
- FMECA
- Fault Tree
- Maintenance
- Monitoring
- Neural network
- Neuro-fuzzy
- SCADA
- UML
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