Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China.
State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China.
Sensors (Basel). 2023 Mar 16;23(6):3165. doi: 10.3390/s23063165.
We proposed an optical frequency domain reflectometry based on a multilayer perceptron. A classification multilayer perceptron was applied to train and grasp the fingerprint features of Rayleigh scattering spectrum in the optical fiber. The training set was constructed by moving the reference spectrum and adding the supplementary spectrum. Strain measurement was employed to verify the feasibility of the method. Compared with the traditional cross-correlation algorithm, the multilayer perceptron achieves a larger measurement range, better measurement accuracy, and is less time-consuming. To our knowledge, this is the first time that machine learning has been introduced into an optical frequency domain reflectometry system. Such thoughts and results would bring new knowledge and optimization to the optical frequency domain reflectometer system.
我们提出了一种基于多层感知器的光频域反射计。应用分类多层感知器来训练和掌握光纤中瑞利散射光谱的指纹特征。通过移动参考光谱并添加补充光谱来构建训练集。通过应变测量来验证该方法的可行性。与传统的互相关算法相比，多层感知器具有更大的测量范围、更好的测量精度，并且耗时更少。据我们所知，这是机器学习首次被引入光频域反射计系统。这样的思路和结果将为光频域反射计系统带来新的知识和优化。
