大数据分析技术的光纤传感谱形复用技术研究

光纤传感谱形复用研究属于传感网络设计里的核心问题,针对当光纤传感谱形复用技术存在的误差大,耗时长等缺陷,结合光纤传感谱形复用的特点,设计了一种基于大数据分析技术的光纤传感谱形复用技术。首先采用大数据分析技术得到法得到光纤传感重叠光谱数据,并对其进行一定的预处理,然后引入粒子群算法对光纤传感重叠光谱数据实施光纤传感谱形复用解调,从而优化光纤传感谱形复用性能,最后与其它技术进行了仿真对比实验,结果表明:本文技术对低维、高维的光纤传感谱形复用数据分类精度高,在解调2个光纤传感谱形复用时,误差低,耗时少,速度快,获得了多光纤传感谱形复用理想的解调效果。

Research on optical fiber sensing spectral multiplexing technology of big data analysis technology

The research of optical fiber sensing spectral multiplexing belongs to the core problem in the design of sensor network.Regarding the defects of optical fiber sensing spectral multiplexing technology,such as large error and long time-consuming,combined with the characteristics of optical fiber sensing spectral multiplexing,an optical fiber sensing spectral multiplexing technology based on big data analysis technology is designed.Firstly,the method of big data analysis is used to get overlapped spectrum data of optical fiber sensor,and some preprocessing is carried out.Then particle swarm optimization algorithm is introduced to carry out the spectral multiplexing and demodulation of optical fiber sensor overlapped spectrum data,so as to optimize the spectral multiplexing performance of optical fiber sensor.Finally,the simulation and comparison experiments with other technologies are carried out,and the results show that the technology in this paper is suitable for low dimension when demodulating two optical fiber sensing spectrums,the error is low,the time-consuming is small and the speed is fast.