基于极限学习机的FBG波长漂移量预测方法

Prediction method for FBG wavelength shift based on extreme learning machine

针对光纤布喇格光栅(FBG)传感系统的中心波长漂移问题,提出一种基于极限学习机(ELM)的FBG波长漂移量预测和泛化方法。该方法通过构建中心波长与波长漂移量的映射关系训练神经网络,实现对波长漂移量的预测和泛化。实验结果表明:该方法对FBG波长漂移量的预测误差小于1 pm,泛化误差小于2 pm,为FBG传感系统的现场校准提供了有益的探索。

Aiming at the center wavelength shift problem in the fiber Bragg grating(FBG)sensing system,an FBG wavelength shift predict and generalization method based on extreme learning machine(ELM)is proposed.The method trains the neural network by constructing the mapping relationship between the center wavelength and the wavelength shift.It can realize the prediction and generalization of the wavelength shift.The experiment results show that the predicted error of FBG wavelength shift is less than 1 pm and the generalized error of FBG wavelength shift is less than 2 pm,which provides a useful exploration for the field calibration of FBG sensor system.