Fiber Grating Sensor Temperature Prediction Based on Relevance Vector Machine

Fiber grating sensor network plays an important role in evaluating the bridge health condition and gaining bridge structure characteristic.Bridge structural distortion and variation of stress is associated with temperature.So it is essential to make temperature prediction bases on the length of wave which gained from fiber grating sensor network system.Traditionally, we apply least square method to predict temperature.In this paper,we use method of relevance vector machine (RVM) to make it.