Information fusion under consideration of conflicting input signals / Uwe Mönks.
2017
TK7872.D48
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Title
Information fusion under consideration of conflicting input signals / Uwe Mönks.
Author
ISBN
9783662537527 (electronic book)
3662537524 (electronic book)
9783662537510
3662537524 (electronic book)
9783662537510
Publication Details
Berlin, Germany : Springer, 2017.
Language
English
Description
1 online resource (249 pages).
Item Number
10.1007/978-3-662-53752-7 doi
Call Number
TK7872.D48
Dewey Decimal Classification
621.3815/36
620
620
Summary
This work proposes the multilayered information fusion system MACRO (multilayer attribute-based conflict-reducing observation) and the µBalTLCS (fuzzified balanced two-layer conflict solving) fusion algorithm to reduce the impact of conflicts on the fusion result. In addition, a sensor defect detection method, which is based on the continuous monitoring of sensor reliabilities, is presented. The performances of the contributions are shown by their evaluation in the scope of both a publicly available data set and a machine condition monitoring application under laboratory conditions. Here, the MACRO system yields the best results compared to state-of-the-art fusion mechanisms. The author Dr.-Ing. Uwe Mönks studied Electrical Engineering and Information Technology at the OWL University of Applied Sciences (Lemgo), Halmstad University (Sweden), and Aalborg University (Denmark). Since 2009 he is employed at the Institute Industrial IT (inIT) as research associate with project leading responsibilities. During this time he completed his doctorate (Dr.-Ing.) in a cooperative graduation with Ruhr-University Bochum. His research interests are in the area of multisensor and information fusion, pattern recognition, and machine learning.
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text file PDF
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Description based on print version record.
Series
Technologien für die intelligente Automation ; Bd. 4.
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Table of Contents
Introduction
Scientific State of the Art
Preliminaries
Multilayer Attribute-based Conflict-reducing Observation
Evaluation
Summary.
Scientific State of the Art
Preliminaries
Multilayer Attribute-based Conflict-reducing Observation
Evaluation
Summary.