@inproceedings{2141,
  abstract     = {{Sensor and information fusion is recently a major topic which becomes important in machine diagnosis and conditioning for complex production machines and process engineering. It is a known fact that distributed automation systems have a major impact on signal processing and pattern recognition for machine diagnosis. Therefore, it is necessary to research and develop smart diagnosis methods which are applicable for distributed systems like resource-limited cyber-physical systems. In this paper we propose an new approach for sensor and information fusion based on Evidence Theory and socio-psychological decision-making. We show that context based condition monitoring is instantiated even in conflict situations, oc-curing in real life scenarios permanently. A simple but effective importance measure is proposed which controls the significance of conditioning propositions in a system.}},
  author       = {{Mönks, Uwe and Lohweg, Volker}},
  booktitle    = {{18th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)}},
  isbn         = {{978-1-4799-0862-2}},
  issn         = {{1946-0759 }},
  keywords     = {{Decision making, Robot sensing systems, Reliability, Production, Context, Fuzzy set theory, Data integration}},
  title        = {{{Machine Conditioning by Importance Controlled Information Fusion}}},
  doi          = {{10.1109/ETFA.2013.6647984}},
  year         = {{2013}},
}

@inproceedings{2107,
  abstract     = {{In this paper we propose a novel, extended perspective on evidential aggregation rules in machine condition monitoring. First, aspects regarding the interconnections between Dempster-Shafer, Fuzzy Set, and Possibility Theory are shown. Subsequently, a novel approach for direct determination of basic probability assignments using Fuzzy membership functions is proposed. Finally, it is applied to a pipe extrusion line's condition monitoring system, considering and reducing pairwise conflicts.}},
  author       = {{Mönks, Uwe and Voth, Karl and Lohweg, Volker}},
  booktitle    = {{IEEE CIP 2012, Third International Workshop on Cognitive Information Processing, May 28-30 2012, Parador de Baiona, Spain}},
  isbn         = {{978-1-4673-1877-8}},
  issn         = {{2327-1698 }},
  keywords     = {{Sensor phenomena and characterization, Production, Sensor fusion, Fuzzy set theory, Conferences, Possibility theory}},
  title        = {{{An Extended Perspective on Evidential Aggregation Rules in Machine Conditioning}}},
  doi          = {{10.1109/CIP.2012.6232905}},
  year         = {{2012}},
}