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Authors: Sebastian Feller 1 ; Yavor Todorov 1 ; Dirk Pauli 1 and Folker Beck 2

Affiliations: 1 FCE Frankfurt Consulting Engineers GmbH, Germany ; 2 John Deere Werke Zweibruecken, Germany

Keyword(s): Data compression, Time series analysis, Condition based maintenance.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Nonlinear Signals and Systems ; Robotics and Automation ; Signal Processing, Sensors, Systems Modeling and Control ; Surveillance ; Time Series and System Modeling

Abstract: In many real-world applications such as condition monitoring of technical facilities or vehicles the amount of data to process and analyze has steadily increased during the last decades. In this paper a novel approach to data compression is presented, namely the multivariate representative of the Perceptually Important Points algorithm. Furthermore, approaches are given on how multivariate data should be dealt with to preserve all relevant multivariate information during a lossy data compression. This involves an extensive analysis of the stochastic dependencies of the process data. On the one hand the presented algorithm is able to compress the multivariate time series and on the other hand the algorithm can be easily extended to reflect a model of the original time series. It is shown that suggested multivariate compression algorithm outperforms its univariate equivalent.

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Paper citation in several formats:
Feller, S.; Todorov, Y.; Pauli, D. and Beck, F. (2011). OPTIMIZED STRATEGIES FOR ARCHIVING MULTI-DIMENSIONAL PROCESS DATA - Building a Fault-diagnosis Database. In Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-8425-74-4; ISSN 2184-2809, SciTePress, pages 388-393. DOI: 10.5220/0003571803880393

@conference{icinco11,
author={Sebastian Feller. and Yavor Todorov. and Dirk Pauli. and Folker Beck.},
title={OPTIMIZED STRATEGIES FOR ARCHIVING MULTI-DIMENSIONAL PROCESS DATA - Building a Fault-diagnosis Database},
booktitle={Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2011},
pages={388-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003571803880393},
isbn={978-989-8425-74-4},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - OPTIMIZED STRATEGIES FOR ARCHIVING MULTI-DIMENSIONAL PROCESS DATA - Building a Fault-diagnosis Database
SN - 978-989-8425-74-4
IS - 2184-2809
AU - Feller, S.
AU - Todorov, Y.
AU - Pauli, D.
AU - Beck, F.
PY - 2011
SP - 388
EP - 393
DO - 10.5220/0003571803880393
PB - SciTePress

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