基于卡尔曼滤波的闭式循环蒸汽温度在线处理方法

Kalman Filter-Based Closed Cycle Steam Temperature Processing Method

Li/SF_6能源系统是一种新型高能热源,其能量密度高、无产物排放的特点可支持水下装备构建闭式循环动力系统。能源系统中的螺旋管出口温度作为影响反应过程的关键反馈量,在测量噪声和系统噪声干扰下会影响系统调控精度和稳定性,对航行器的可靠工作产生负面作用。文中基于一维分布参数法仿真得到的蒸汽出口温度变化曲线,针对常用降噪方法的不足,设计了一种基于卡尔曼滤波原理在线降噪处理方法。经过与常规采用的滑动平均滤波和1阶低通滤波方法的对比可知,该方法不仅在误差概率分布、信噪比方面具有明显优势,而且能够缩短系统稳定时间,改善系统动态特性。

Li/SF6 energy system is a new type of high energy power source,which can support the construction of a closed cycle power system for underwater equipment due to its high energy density and no product emission.As a key feedback parameter that affects the reaction process,the helical tube outlet temperature in the energy system will impact the precision and stability of the system control under the disturbance of measurement noise and system noise,bringing a negative effect on the reliability of the vehicle.In this paper,the steam outlet temperature curve was obtained by one-dimensional distributed parameter simulation.In view of the shortcomings of common noise reduction methods,an online noise reduction method based on Kalman filter principle was proposed.By comparing with the conventional sliding average filtering and first-order low-pass filtering methods,it can be seen that the proposed method has distinct advantages in terms of error probability distribution and signal-to-noise ratio.Besides,it can shorten the stable time and improve the dynamic characteristics of the system.