.png){kind=icon}
返回
Self-healing FBG sensor network fault-detection based on a multi-class SVM algorithm
.png){kind=icon}
OA
AI
DOI：10.1364/OE.509286.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We propose a three-layer ring architecture with enhanced reconfigurable capabilities for fiber Bragg grating (FBG) sensor networks. The proposed network is capable of self-healing when three fiber links fail. In addition to self-healing, soft faults in the FBG sensors can be detected using a multi-classification support vector machine (multi-class SVM) algorithm. The detection accuracy reached 99%. Additionally, we used an artificial neural network (ANN) reliability estimation model to estimate the reliability of the FBG self-healing network. The results show that the ANN reliability analysis model can accurately estimate the reliability of the architecture at a reasonable cost.
Keyword:
SENSING SYSTEM
FIBER
ARCHITECTURE
PREDICTION
期刊
IF:
3.3
论文数:
6.1W
被引数:
14.3W
机构
引用论文
Fiber Bragg Grating Sensor System With Two-Level Ring Architecture两级环结构光纤光栅传感系统.png)
IEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
分享收藏分享收藏分享收藏Strain Sharing Assessment in Woven Fiber Reinforced Concrete Beams Using Fiber Bragg Grating SensorsSENSORS
OAAI
SENSORSIF3.5
OAAI分享收藏Fiber Bragg Gratings for Medical Applications and Future Challenges: A Review光纤布拉格光栅在医学中的应用及未来挑战IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容