一种基于卡尔曼最优平滑方程的开关电容网络——第三代(光纤传感)轴温探测器的信号处理

A Switched Capacitor Network Based on Kalman Optimal Smoothing Equations —Data Processing for the Third Generation Temperature Detectors of Railway Vehicle Axles

列车轴温光纤传感探测器的输入信号十分微弱并混有噪声，为此研制一种特殊的滤波器就显得尤为必要。文中分析了该探测器的噪声源，并根据光电变换信号的微分表达式建立了卡尔曼最优平滑方程，采用开关电容滤波器精确实现了该方程，解决了列车轴温光纤传感探测器中的信号平滑滤波问题，大大提高了系统的探测率。

It is necessary to develop a particular filter for the optical fiber temperature sensor of railway vehicle axles because the input signal is not only very feeble but also mixed with noises. In this paper, the noise sources are analyzed. Kalman optimal smoothing equations are derived according to the photoelectric converting differential equations. Meanwhile, a switched capacitor filter network is utilized to realize the equations precisely. The smoothing problem for random signal in the optical fiber temperature sensor for railway vehicle axles is solved, and the detectivity of the system is increased greatly.