---
_id: '2014'
abstract:
- lang: eng
text: Industrial applications are in transition towards modular and flexible architectures
that are capable of self-configuration and -optimisation. This is due to the demand
of mass customisation and the increasing complexity of industrial systems. The
conversion to modular systems is related to challenges in all disciplines. Consequently,
diverse tasks such as information processing, extensive networking, or system
monitoring using sensor and information fusion systems need to be reconsidered.
The focus of this contribution is on distributed sensor and information fusion
systems for system monitoring, which must reflect the increasing flexibility of
fusion systems. This contribution thus proposes an approach, which relies on a
network of self-descriptive intelligent sensor nodes, for the automatic design
and update of sensor and information fusion systems. This article encompasses
the fusion system configuration and adaptation as well as communication aspects.
Manual interaction with the flexibly changing system is reduced to a minimum.
article_number: '601'
author:
- first_name: Alexander
full_name: Fritze, Alexander
last_name: Fritze
- first_name: Uwe
full_name: Mönks, Uwe
id: '1825'
last_name: Mönks
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: Fritze A, Mönks U, Holst C-A, Lohweg V. An Approach to Automated Fusion System
Design and Adaptation. Sensors. 2017;17(3). doi: https://doi.org/10.3390/s17030601
apa: Fritze, A., Mönks, U., Holst, C.-A., & Lohweg, V. (2017). An Approach to
Automated Fusion System Design and Adaptation. Sensors, 17(3). https://doi.org/ https://doi.org/10.3390/s17030601
bjps: Fritze A et al. (2017) An Approach to Automated Fusion System
Design and Adaptation. Sensors 17.
chicago: Fritze, Alexander, Uwe Mönks, Christoph-Alexander Holst, and Volker Lohweg.
“An Approach to Automated Fusion System Design and Adaptation.” Sensors
17, no. 3 (2017). https://doi.org/
https://doi.org/10.3390/s17030601.
chicago-de: Fritze, Alexander, Uwe Mönks, Christoph-Alexander Holst und Volker Lohweg.
2017. An Approach to Automated Fusion System Design and Adaptation. Sensors
17, Nr. 3. doi:
https://doi.org/10.3390/s17030601, .
din1505-2-1: 'Fritze, Alexander ;
Mönks, Uwe ; Holst,
Christoph-Alexander ; Lohweg, Volker:
An Approach to Automated Fusion System Design and Adaptation. In: Sensors
Bd. 17 (2017), Nr. 3'
havard: A. Fritze, U. Mönks, C.-A. Holst, V. Lohweg, An Approach to Automated Fusion
System Design and Adaptation, Sensors. 17 (2017).
ieee: A. Fritze, U. Mönks, C.-A. Holst, and V. Lohweg, “An Approach to Automated
Fusion System Design and Adaptation,” Sensors, vol. 17, no. 3, 2017.
mla: Fritze, Alexander, et al. “An Approach to Automated Fusion System Design and
Adaptation.” Sensors, vol. 17, no. 3, 601, 2017, doi: https://doi.org/10.3390/s17030601.
short: A. Fritze, U. Mönks, C.-A. Holst, V. Lohweg, Sensors 17 (2017).
ufg: 'Fritze, Alexander et. al. (2017): An Approach to Automated Fusion System
Design and Adaptation, in: Sensors 17 (3).'
van: Fritze A, Mönks U, Holst C-A, Lohweg V. An Approach to Automated Fusion System
Design and Adaptation. Sensors. 2017;17(3).
date_created: 2019-11-25T08:52:14Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
doi: ' https://doi.org/10.3390/s17030601'
intvolume: ' 17'
issue: '3'
keyword:
- information fusion
- intelligent sensor
- knowledge-based system
- self-configuration
- sensor fusion
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/1424-8220/17/3/601/htm
oa: '1'
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
status: public
title: An Approach to Automated Fusion System Design and Adaptation
type: journal_article
user_id: '15514'
volume: 17
year: 2017
...
---
_id: '2140'
abstract:
- lang: eng
text: 'Recent industrial applications are implemented in a modular way, resulting
in flexibility during the whole life cycle, i.e., setup, operation, and maintenance.
This applies especially to larger applications like logistic, production, and
printing processes. Their modular character is resulting from the constantly increasing
complexity of such installations, which makes their supervision for securing reliable
operation a difficult task: the data of hundreds (if not thousands) of signal
sources must be acquired, communicated, and evaluated for system diagnosis. In
this contribution we summarize the challenges arising in such applications and
show that distributed sensor and information fusion for modular self-diagnosis
tackles these challenges. Here, we propose an innovative distributed architecture
encompassing intelligent sensor nodes, self-configuring real-time communication
networks, and a suitable sensor and information fusion system for condition monitoring.
New challenges arise in the context of distributed information fusion systems,
which are identified and to which an outlook on future solutions is provided.
A number of these solutions have already been discovered, implemented, and are
evaluated in the context of a demonstrator, which resembles a real-world printing
application.'
author:
- first_name: Uwe
full_name: Mönks, Uwe
id: '1825'
last_name: Mönks
- first_name: Henning
full_name: Trsek, Henning
id: '1486'
last_name: Trsek
- first_name: Lars
full_name: Dürkop, Lars
last_name: Dürkop
- first_name: Volker
full_name: Geneiß, Volker
last_name: Geneiß
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: Mönks U, Trsek H, Dürkop L, Geneiß V, Lohweg V. Towards distributed intelligent
sensor and information fusion. Mechatronics. 2015;(34):63-71. doi:10.1016/j.mechatronics.2015.05.005
apa: Mönks, U., Trsek, H., Dürkop, L., Geneiß, V., & Lohweg, V. (2015). Towards
distributed intelligent sensor and information fusion. Mechatronics, (34),
63–71. https://doi.org/10.1016/j.mechatronics.2015.05.005
bjps: Mönks U et al. (2015) Towards Distributed Intelligent Sensor
and Information Fusion. Mechatronics 63–71.
chicago: 'Mönks, Uwe, Henning Trsek, Lars Dürkop, Volker Geneiß, and Volker Lohweg.
“Towards Distributed Intelligent Sensor and Information Fusion.” Mechatronics,
no. 34 (2015): 63–71. https://doi.org/10.1016/j.mechatronics.2015.05.005.'
chicago-de: 'Mönks, Uwe, Henning Trsek, Lars Dürkop, Volker Geneiß und Volker Lohweg.
2015. Towards distributed intelligent sensor and information fusion. Mechatronics,
Nr. 34: 63–71. doi:10.1016/j.mechatronics.2015.05.005,
.'
din1505-2-1: 'Mönks, Uwe ; Trsek,
Henning ; Dürkop, Lars ;
Geneiß, Volker ; Lohweg,
Volker: Towards distributed intelligent sensor and information fusion.
In: Mechatronics, Elsevier (2015), Nr. 34, S. 63–71'
havard: U. Mönks, H. Trsek, L. Dürkop, V. Geneiß, V. Lohweg, Towards distributed
intelligent sensor and information fusion, Mechatronics. (2015) 63–71.
ieee: U. Mönks, H. Trsek, L. Dürkop, V. Geneiß, and V. Lohweg, “Towards distributed
intelligent sensor and information fusion,” Mechatronics, no. 34, pp. 63–71,
2015.
mla: Mönks, Uwe, et al. “Towards Distributed Intelligent Sensor and Information
Fusion.” Mechatronics, no. 34, Elsevier, 2015, pp. 63–71, doi:10.1016/j.mechatronics.2015.05.005.
short: U. Mönks, H. Trsek, L. Dürkop, V. Geneiß, V. Lohweg, Mechatronics (2015)
63–71.
ufg: 'Mönks, Uwe et. al. (2015): Towards distributed intelligent sensor and
information fusion, in: Mechatronics (34), S. 63–71.'
van: Mönks U, Trsek H, Dürkop L, Geneiß V, Lohweg V. Towards distributed intelligent
sensor and information fusion. Mechatronics. 2015;(34):63–71.
date_created: 2019-12-04T09:29:07Z
date_updated: 2023-03-15T13:49:39Z
department:
- _id: DEP5023
doi: 10.1016/j.mechatronics.2015.05.005
issue: '34'
keyword:
- Cyber-physical systems
- Information fusion
- Fusion system design
- Intelligent sensors
- Self-configuration
- Intelligent networking
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.sciencedirect.com/science/article/pii/S0957415815000707
oa: '1'
page: 63-71
publication: Mechatronics
publication_identifier:
issn:
- 0957-4158
publisher: Elsevier
status: public
title: Towards distributed intelligent sensor and information fusion
type: journal_article
user_id: '68554'
year: 2015
...
---
_id: '2071'
abstract:
- lang: eng
text: In this paper, a fuzzy pattern classification tuning approach is proposed,
which is based on fusion concept. In this method, tuning parameters are learned
in a training procedure, enabling system to be capable of managing individual
classification task. Fuzzy c-means, as a specific instance of Tuning Reference,
is employed as a tool to offer membership function which is used for making decisions
and its membership function fuses (tunes) another membership function captured
from fuzzy pattern classification and then final decisions are made upon fused
one. Experiments are taken on five benchmark datasets, one of them shows an equal
performance and the other four present better results than each single classifier.
author:
- first_name: Rui
full_name: Li, Rui
id: '2000'
last_name: Li
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Li R, Lohweg V. Fuzzy Pattern Classification Tuning by Parameter Learning
based on Fusion Concept. In: In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany; 2008.'
apa: 'Li, R., & Lohweg, V. (2008). Fuzzy Pattern Classification Tuning by Parameter
Learning based on Fusion Concept. In: The 11th Conference on Information Fusion,
June 30 - July 3, Cologne, Germany.'
bjps: 'Li R and Lohweg V (2008) Fuzzy Pattern Classification Tuning by Parameter
Learning Based on Fusion Concept. In: The 11th Conference on Information Fusion,
June 30 - July 3, Cologne, Germany.'
chicago: 'Li, Rui, and Volker Lohweg. “Fuzzy Pattern Classification Tuning by Parameter
Learning Based on Fusion Concept.” In: The 11th Conference on Information Fusion,
June 30 - July 3, Cologne, Germany, 2008.'
chicago-de: 'Li, Rui und Volker Lohweg. 2008. Fuzzy Pattern Classification Tuning
by Parameter Learning based on Fusion Concept. In: . In: The 11th Conference on
Information Fusion, June 30 - July 3, Cologne, Germany.'
din1505-2-1: 'Li, Rui ; Lohweg,
Volker: Fuzzy Pattern Classification Tuning by Parameter Learning based
on Fusion Concept. In: : In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany, 2008'
havard: 'R. Li, V. Lohweg, Fuzzy Pattern Classification Tuning by Parameter Learning
based on Fusion Concept, in: In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany, 2008.'
ieee: R. Li and V. Lohweg, “Fuzzy Pattern Classification Tuning by Parameter Learning
based on Fusion Concept,” 2008.
mla: 'Li, Rui, and Volker Lohweg. Fuzzy Pattern Classification Tuning by Parameter
Learning Based on Fusion Concept. In: The 11th Conference on Information Fusion,
June 30 - July 3, Cologne, Germany, 2008.'
short: 'R. Li, V. Lohweg, in: In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany, 2008.'
ufg: 'Li, Rui/Lohweg, Volker (2008): Fuzzy Pattern Classification Tuning
by Parameter Learning based on Fusion Concept, in: .'
van: 'Li R, Lohweg V. Fuzzy Pattern Classification Tuning by Parameter Learning
based on Fusion Concept. In In: The 11th Conference on Information Fusion, June
30 - July 3, Cologne, Germany; 2008.'
date_created: 2019-11-29T14:09:33Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
keyword:
- tuning parameter
- information fusion
- fuzzy cmeans
- membership function
- fuzzy pattern classification
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/document/4632223/keywords#full-text-header
publication_identifier:
isbn:
- 978-3-8007-3092-6
publication_status: published
publisher: 'In: The 11th Conference on Information Fusion, June 30 - July 3, Cologne,
Germany'
status: public
title: Fuzzy Pattern Classification Tuning by Parameter Learning based on Fusion Concept
type: conference
user_id: '45673'
year: 2008
...