Abstract
The paper defines the main elements of a generic condition monitoring system, as an abstraction of data and services. The key target is how to facilitate asset self-awareness, to support production-level sustainable machinery operation. The proposed approach involves knowledge-rich computational elements, capable of performing incremental model building in order to capture the specific characteristics of the monitored asset behaviour. Coupled with adequate data and knowledge modelling, by means of dedicated ontology, this abstraction mechanism is envisioned to facilitate the rapid development of condition monitoring systems for diverse application needs.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of APMS 2010 International Conference on Advances in Production Management Systems |
| Subtitle of host publication | Cernobbio, Como, Italy, 11-13.10.2010 |
| Publication status | Published - 2010 |
| MoE publication type | A4 Article in a conference publication |
Keywords
- condition-based maintenance
- condition monitoring
- incremental learning
- novelty detection
- diagnosis and prognosis
- ontology