Overview
- Introduces the MACRO (multilayer attribute-based conflict-reducing observation) fusion system
- Contains a discussion of state-of-the-art information fusion approaches from probability, possibility, and Dempster-Shafer theory
- Compares the proposed approach to real-world application
- Includes supplementary material: sn.pub/extras
Part of the book series: Technologien für die intelligente Automation (TIA)
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Table of contents (6 chapters)
Keywords
About this book
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.
Authors and Affiliations
About 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.
Bibliographic Information
Book Title: Information Fusion Under Consideration of Conflicting Input Signals
Authors: Uwe Mönks
Series Title: Technologien für die intelligente Automation
DOI: https://doi.org/10.1007/978-3-662-53752-7
Publisher: Springer Vieweg Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature 2017
Softcover ISBN: 978-3-662-53751-0Published: 19 December 2016
eBook ISBN: 978-3-662-53752-7Published: 25 November 2016
Series ISSN: 2522-8579
Series E-ISSN: 2522-8587
Edition Number: 1
Number of Pages: XIX, 240
Number of Illustrations: 23 b/w illustrations, 35 illustrations in colour
Topics: Computational Intelligence, Signal, Image and Speech Processing, Robotics and Automation, Artificial Intelligence