Kalman Filter-Based Closed Cycle Steam Temperature Processing Method

Abstract

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.

Keywords

• closed cycle
• kalman filter
• steam temperature
• signal processing