基于粒子群算法的FBG传感系统数据采集速率优化

发布时间：2018-06-20 03:29

  本文选题：FBG传感 + 可调谐法布里-珀罗滤波器　； 参考：《光通信技术》2017年09期

【摘要】：首先介绍了光纤光栅(FBG)远程传感系统的组成及解调方法。针对FBG传感系统在远程设置零点时,数据处理速率波动引起的数据采集速率与数据处理速率不匹配问题,提出引入粒子群(PSO)算法实时在线优化光谱扫描速率,使动态传感系统持续处于系统可能达到的最高数据采集速率,降低传感系统测量精度。最后通过实验平台验证了该算法的有效性。
[Abstract]:The composition and demodulation method of fiber Bragg grating (FBG) remote sensing system are introduced. Aiming at the mismatch between the data acquisition rate and the data processing rate caused by the fluctuation of the data processing rate when the FBG sensor system sets the zeros remotely, a particle swarm optimization (PSO) algorithm is proposed to optimize the spectral scanning rate in real time. The dynamic sensing system is kept at the maximum data acquisition rate which can be achieved by the system, and the measurement accuracy of the sensing system is reduced. Finally, the effectiveness of the algorithm is verified by the experimental platform.
【作者单位】： 上海电力学院自动化工程学院;
【基金】：国家留学基金委留学基金资助项目(2009102131)资助 国家自然科学基金青年基金(61003089)资助 上海市地方院校能力建设专项项目(15160500800)资助
【分类号】：TN253;TP212
，

本文编号：2042732