摘要
针对光纤布拉格光栅(FBG)传感网络中重叠光谱的中心波长解调问题,提出一种基于门控循环单元(GRU)网络的波长检测方法。该方法将FBG重叠光谱的波长解调问题转换为模型回归问题,同时考虑到光谱数据的序列特征和频谱特性,采用GRU网络实现对光谱数据的特征学习,训练得到相应的波长检测模型,从而实现对重叠光谱的精确快速解调。经实验验证,所提方法能够解决FBG传感网络光谱部分重叠或完全重叠条件下的中心波长的精确解调问题,其方均根小于1 pm的测试结果占总数的88.2%。相比现有的解调方式,所提方法在检测精度和稳定性上均有一定的提升,为提高FBG传感网络的复用能力提供了新的途径。
A wavelength detection method based on gated recurrent unit(GRU) network was proposed to demodulate the central wavelength of overlapping spectra in fiber Bragg grating(FBG) sensor networks. The proposed method transformed the wavelength demodulation problem of overlapping spectra in FBG into a regression problem and considered the sequence and spectrum characteristics of the spectral data. To learn the spectral data characteristics and train to achieve the corresponding wavelength detection model, the GRU network was used. Thus, the overlapping spectra could be quickly and accurately demodulated. Experimental results show that the proposed method can overcome the precise demodulation problem of the central wavelength for partially or completely overlapping spectra of FBG sensor networks. The test results with root mean square less than 1 pm account for 88.2% of the test results. The detection accuracy and stability of the proposed method provide enhanced results compared with existing demodulation methods. The proposed method provides a novel way to improve the multiplexing capability of FBG sensor networks.
作者
江灏
王尤刚
陈静
黄新宇
Jiang Hao;Wang Yougang;Chen Jing;Huang Xinyu(College of Electrial Engineering and Automation,Fuzhou University,Fuzhou,Fujan 350108,China;Research Institute of Pruer System&Porwer Equipment,Fuzhou University,Fuzhou,Fujian 350108,China)
出处
《光学学报》
EI
CAS
CSCD
北大核心
2020年第7期6-13,共8页
Acta Optica Sinica
基金
国家自然科学基金(61703106,61703105)
福建省自然科学基金面上项目(2017J01500)
福建省教育厅中青年科研项目(JAT170107)
福建省高校青年自然科学基金重点项目(JZ160415)。
作者简介
陈静,E-mail:chenj@fzu.edu.cn。
