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The importance of model-learning for the analysis of the energy consumption of production plants

 
: Gilani, Syed-Shiraz; Windmann, Stefan; Pethig, Florian; Kroll, Björn; Niggemann, Oliver

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Institute of Electrical and Electronics Engineers -IEEE-:
18th IEEE Conference on Emerging Technologies and Factory Automation, ETFA 2013. Proceedings : Cagliari, Italy, 10-13 September 2013
New York, NY: IEEE, 2013
ISBN: 978-1-4799-0864-6
ISBN: 978-1-4799-0862-2 (Print)
8 S.
International Conference on Emerging Technologies and Factory Automation (ETFA) <18, 2013, Cagliari>
Englisch
Konferenzbeitrag
Fraunhofer IOSB ()

Abstract
Model-learning is the key to the new generation of intelligent automation systems: Without the automatic generation of models from system observations, models of the plant's behavior will not be available for most systems. And without such models, no intelligent capabilities such as self-diagnosis or self-optimization can be implemented. This paper therefore presents a novel classification schema for systems, models and model learning algorithms. Based on this analysis of open research questions, the new learning algorithm HyBUTLA is presented. In this paper, this solution approach is applied to the analysis and diagnosis of the energy consumption of production plants. To the best of the authors' knowledge, this is the first learning and adaptable energy anomaly detection solution for complex hybrid production systems.

: http://publica.fraunhofer.de/dokumente/N-275752.html