Real-time identification of out-of-control and instability in process parameter for gasification process: Integrated application of control chart and kalman filter

Abstract

Due to the parameters’ complex variation in gasification process, traditional monitoring method detecting the observed data directly may case missing alarm. This paper proposed a real-time identification model with high accuracy using Kalman filter and control chart jointly. The observed data is divided into state value and deviation value using Kalman filter, then they are separately monitored by control char. Simulation experiments on gasifier temperature monitoring in three typical fluctuation modes and field application on H2 and CO monitoring for a gasifier under there different starting condition were carried out. The proposed method respectively identified 4, 6 and 2 alarms in simulation experiments, and identified 10, 3, 12, 68, 2 and 4 alarms in filed application. Besides, the proposed method also accurately identified the presented the preset sinusoidal fluctuations and upward shift when monitoring temperature and 4 systematic variations and 23 special variations when monitoring H2 and CO. The performance of the proposed method is significantly more accuracy than that of traditional methods. So the integrated application of control chart and Kalman filter in gasification process parameter monitoring has the advantages of high sensitivity of outlier alarm, high identification of variation and high applicability of multimode fluctuations under various conditions.