Damage identification for composite structures with a Bayesian network

被引：5
|
作者：
Nguyen, M [1 ]
Wang, XM [1 ]
Su, ZQ [1 ]
Ye, L [1 ]
机构：
[1] CSIRO, Mfg & Infrastruct Technol Div, Highett, Vic 3190, Australia
来源：
Proceedings of the 2004 Intelligent Sensors, Sensor Networks & Information Processing Conference | 2004年
关键词：
D O I：
10.1109/ISSNIP.2004.1417480
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Recent development on the application of distributed sensor networks in Structural Health Monitoring (SHM) for large structural areas has resulted in more complicated system identification techniques, particularly for those with multiple information sources. This paper presents an application of bayesian inference network to detection of hole-type damages on a composite plate using multiple sensing data streams from a distributed sensor network. Representative damage features from 50 damage scenarios were used for the learning process. The Bayesian net is found to be promising when correctly diagnosing the damage ' s location and size for a validation case.
引用
收藏
页码：307 / 311
页数：5
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