DocumentCode :
3687822
Title :
Pattern recognition in load profiles of electric drives in manufacturing plants
Author :
Arnim Reger;Cedric Oette;Ana Paula Aires;Rolf Steinhilper
Author_Institution :
Fraunhofer Projectgroup Processinnovation, Fraunhofer IPA, Bayreuth, Germany
fYear :
2015
Firstpage :
1
Lastpage :
10
Abstract :
With the introduction of energy management systems, an analysis of load profiles of manufacturing plants becomes increasingly important. Each manufacturing plant is characterized by a process and product specific power consumption. Often, electric drives are the main power consumers. In this paper methods for pattern recognition in load profiles of electric drives are presented on the example of a multiaxial lathe. A transfer of techniques used for speech recognition e.g. Hidden Markov Models, Fourier and Wavelet Transforms to manufacturing application is discussed. In combination with energy measurement systems, those techniques proved to be a good solution regarding energy efficiency calculations and derivation for key performance indicators. The investigated methods can also be applied to other process data with significant cost advantages, because a lot of process information can be extracted from a single sensor.
Keywords :
"Hidden Markov models","Manufacturing","Viterbi algorithm","Training","Pattern recognition","Maximum likelihood estimation","Energy consumption"
Publisher :
ieee
Conference_Titel :
Electric Drives Production Conference (EDPC), 2015 5th International
Print_ISBN :
978-1-4673-7511-5
Type :
conf
DOI :
10.1109/EDPC.2015.7323209
Filename :
7323209
Link To Document :
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