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  4. Distributed-cooperative problem solving in structural health monitoring using multi-level intelligence
 
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Distributed-cooperative problem solving in structural health monitoring using multi-level intelligence

Publikationstyp
Conference Paper
Date Issued
2006-07
Sprache
English
Author(s)
Smarsly, Kay  
Hartmann, Dietrich  
TORE-URI
http://hdl.handle.net/11420/14279
Start Page
429
End Page
436
Citation
Proceedings of the 3rd European Workshop - Structural Health Monitoring 2006: 429-436 (2006-12-01)
Contribution to Conference
3rd European Workshop Structural Health Monitoring (EWSHM 2006)  
Scopus ID
2-s2.0-84867870118
Publisher
DESTech Publications
This paper presents a new approach towards distributed-cooperative problem solving in Structural Health Monitoring (SHM). For solving the monitoring problem effectively, an intelligent, distributed software system composed of cooperating software entities has been designed. Its purpose is to autonomously process the monitoring tasks and also to support the involved human experts. Furthermore, an intelligent hardware infrastructure (sensing units) has been developed to be distributed in engineering structures. These sensing units are connected to the software system and acquire measured data from the respective structures. Moreover, the acquired data are immediately condensed and embedded on-site data analyses are autonomously executed-such as real-time plausibility checks and damage detection analyses. Both the software system and the hardware infrastructure together build a new type of distributed, autonomous SHM system. Its main benefit compared to conventional automated monitoring systems is a decentralized and pro-active safety assessment since the execution of monitoring tasks, e.g. data analyses and data condensing, are delegated to intelligent sensing units and, by that, accomplished locally and concurrently. Consequently, the network load within the SHM system caused by the transmission of large amounts of measured data is significantly decreased and, beyond that, emerging anomalies can be expeditiously detected in realtime.
DDC Class
004: Informatik
610: Medizin
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