Information Fusion Under Consideration of Conflicting Input Signals

  • Uwe Mönks

Part of the Technologien für die intelligente Automation book series (TIA)

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Uwe Mönks
    Pages 1-9
  3. Uwe Mönks
    Pages 11-35
  4. Uwe Mönks
    Pages 37-55
  5. Uwe Mönks
    Pages 113-152
  6. Uwe Mönks
    Pages 153-161
  7. Back Matter
    Pages 163-240

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.

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.


Conflict information Multilayered information Fusion algorithm Condition monitoring System control and monitoring Data heterogeneity

Authors and affiliations

  • Uwe Mönks
    • 1
  1. 1.inIT - Institut für industrielle InformationstechnikHochschule Ostwestfalen-LippeLemgoGermany

Bibliographic information