UNSCENTED P ARTICLE FILTER AND LOG LIKELIHOOD RATIO BASED FAULT DIAGNOSIS OF NONLINEAR
SYSTEM IN NON-GAUSSIAN NOISES

GE Zhexue  YANG Yongmin  HU Zheng  CHEN Zhongsheng

(College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073)

Abstract: As for the problem of fault diagnosis of nonlinear system in non-Gaussian noises, a new method based on the unscented particle filter(UPF) is proposed, concerning of the shortcoming of degeneracy and estimation precision of generic particle filter. Firstly, normal/abnormal UPF models are established separately, and the calculation method of likelihood probability density function and log likelihood ratio are deducted. Then, the fault detection and diagnosis rule are given, which can forecast both the happening time and type of the fault. At last, some experiments of nonlinear actuator loop of helicopter are carried out, which can demonstrate the validity and superiority of the proposed method.

Key words: Unscented particle filter  Log likelihood ratio  Fault diagnosis  Nonlinear  Non-Gaussian

CLC No: TP277

国家自然科学基金(50375153)和维修工程预先研究(413270303)资助项目. Received 20061017, received in revised form 20070812