光纤光栅温度传感器应变补偿系统研究

Study of the FBG Temperature Sensor Stain Compensation System

提出采用D-S证据理论融合的多传感器信息融合BP神经网络模型方法,来解决光纤光栅温度传感器的应变补偿问题,即改善光纤光栅的交叉敏感现象。通过程序仿真和实验证实,此方法可以实现对光纤光栅温度传感器的应变补偿,达到光纤光栅温度传感器温度和应变的精确分离,其测量温度误差约为10-2,同时有效地抑制了光纤光栅传感器非线性的影响。

In order to solve strain compensation problem of the fiber Bragg grating（FBG） temperature sensor,the sensor information fusion and BP neural network model method of the D-S evidence theory is adopted in the paper,including to improve cross-sensitivity phenomenon of FBG.The results of program simulations and experiments illustrate that the method can realize strain compensation,separate the temperature and the strain exactly in the FBG temperature sensor and the measuring temperature error is about 10-2.The method also restrains the influence of nonlinear effectively in the FBG sensor.