Qualitative study of Riccati difference equation on maneuvering target tracking and fault diagnosis of wind turbine gearbox. Issue 1 (1st January 2019)

• Record Type: Journal Article
• Authors: Sumathy, M.; Kilicman, Adem; Manuel, M. Maria Susai; Mary, Jesintha
• Other Names: Pham Duc reviewing-editor.
• Is Part Of: Cogent engineering. Volume 6:Issue 1(2019)
• Publication Date: 2019-01-01
• Subjects: Riccati difference equations -- state estimation -- Kalman filter -- target tracking -- wind turbine -- gearbox; 39A21 -- 39A22 -- 39A30 -- 39A60; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: Https://www.tandfonline.com/doi/10.1080/23311916.2019.1621423
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: Various performance analyses using Interacting Multiple Model (IMM) algorithm for the stability of tracking a maneuvering target are dealt with the state error covariance. A noble way of analyzing the stability of the IMM algorithm for a linear systems with the upper and lower bounds of the error covariance is analyzed. For this persuasion, a two-model Interacting Multiple Model Kalman Filter (IMMKF) with constant acceleration and constant jerk model has been applied for two different case studies. One is tracking a maneuvering target, and the another is tracking a vibration of wind turbine gearbox, which helps to identify failure component in wind energy system. The required data are collected from a radar and a defected gear box of a test wind turbine, and the efficiency of IMM algorithm is analyzed by simulation experiments.