针对采用支持向量机理论识别飞机机翼盒段上外加载荷位置的光纤Bragg光栅传感器网络,研究了提高位置识别精度的方法;分析了网络中部分传感器失效对位置识别精度的影响,针对故障情况提出了基于模型重构的容错位置识别算法,并对采用容错位置识别算法前后载荷位置识别精度进行了详细的比较。研究结果表明:当网络中某个传感器失效时,通过模型重构容错位置识别算法可有效地实现传感器网络的自修复能力,提高传感器网络的可靠性。
Abstract
For the fiber Bragg grating sensor network, how to increase the external load position identification precision of a certain aircraft wing box adopting to the support vector machine is an important problem. The influence degree of the position identification precision when partial optic fiber sensor failure in the network is analyzed and the fault-tolerant position identification algorithm based on the model reconstruct in terms of the failure condition is proposed.Meanwhile the load position identification precision before and after adopting to the model reconstruct position identification algorithm is compared in detail.The result indicates that the model reconstruct fault-tolerant identification algorithm can realize the self-repairing of the fiber Bragg grating sensor network effectively when partial sensor failure, and the reliability of the sensor network is improved.
关键词
计量学 /
支持向量机 /
模型重构 /
光纤Bragg光栅 /
传感器网络;自修复
Key words
Metrology /
Support vector machine /
Model reconstruct /
Fiber Bragg Grating /
Sensor network /
Self-repairing
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基金
国家自然科学基金（51275239,60907038）;江苏省科技计划（BE2011181）;江苏省自然科学基金（BK2008388）;航空科学基金（2008ZD52047）
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