Kalman filter based fault detection for two-dimensional systems. (April 2015)

• Record Type: Journal Article
• Authors: Wang, Zhenheng; Shang, Helen
• Is Part Of: Journal of process control. Volume 28(2015:Apr.)
• Page Start: 83
• Page End: 94
• Publication Date: 2015-04
• Subjects: Fault detection -- 2-D systems -- Kalman filter; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2015.03.002
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract : Highlights: A 2-D Kalman filter based fault detection is developed. A residual generator is obtained using a recursive 2-D Kalman filter. A model describing the residual signal over a 2-D evaluation window is provided. 2-D residual evaluation is performed using statistical approaches. Abstract: Fault detection and isolation for two-dimensional (2-D) systems represent a great challenge in both theoretical development and applications. Use of Kalman filters in fault detection has been well developed for one-dimensional (1-D) system. In this paper, a fault detection algorithm is developed for 2-D systems described by the Fornasini & Marchesini (F–M) model. Based on the state estimate from a recursive 2-D Kalman filter, a residual is generated. From the model of residual over a 2-D evaluation window, the residual is explicitly related to faults within the evaluation window. Using generalized likelihood ratio (GLR), residual evaluation is carried out and compared with a calculated threshold value for fault detection. Simulation results indicate that faults can be detected effectively using the proposed method.