Structural Health and Load Monitoring with Material-embedded Sensor Networks and Self-organizing Multi-Agent Systems

被引:12
作者
Bosse, Stefan [1 ,2 ]
Lechleiter, Armin [1 ]
机构
[1] Univ Bremen, Dept Math & Comp Sci, D-28359 Bremen, Germany
[2] ISIS Sensorial Mat Sci, Bremen, Germany
来源
2ND INTERNATIONAL CONFERENCE ON SYSTEM-INTEGRATED INTELLIGENCE: CHALLENGES FOR PRODUCT AND PRODUCTION ENGINEERING | 2014年 / 15卷
关键词
Structural Health Monitoring; Sensor Network; Mobile Agent; Heterogeneous Networks; Embedded Systems; Inverse Numerical Computation; INVERSE METHODS;
D O I
10.1016/j.protcy.2014.09.039
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the major challenges in Structural Health Monitoring and load monitoring of mechanical structures is the derivation of meaningful information from sensor data. This work investigates a hybrid data processing approach for material-integrated SHM and LM systems by using self-organizing mobile multi-agent systems (MAS), with agent processing platforms scaled to microchip level which offer material-integrated real-time sensor systems, and inverse numerical methods providing the spatial resolved load information from a set of sensors embedded in the technical structure. Inverse numerical approaches usually require a large amount of computational power and storage resources, not suitable for resource constrained sensor node implementations. Instead, off-line computation is performed, with on-line sensor processing by the agent system. (C) 2014 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:668 / 690
页数:23
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