TY - GEN
T1 - A novel fault detection method based on the UKF and its application to a fifth-order two-phase nonlinear motor system
AU - Liu, Chang
AU - Wang, Honglun
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/20
Y1 - 2015/11/20
N2 - Small faults are difficult to be detected under noisy conditions. And the small sensor faults will introduce modeling errors in the observation equations. Therefore, small faults need be detected successfully and quickly. A novel small fault detection (FD) method is proposed using the residuals generated by the unscented Kalman filter (UKF) for a fifth-order two-phase nonlinear motor. Firstly, the introduction of the UKF is given. Secondly, on the basis of the UKF, a fault detection scheme based on a local approach is proposed. The local approach is used to detect small faults from residuals obtained from the UKF. Besides, the comparison between local approach and generalized likelihood test approach is introduced to illustrate the effectiveness of the proposed method. Finally, the proposed fault detection method is applied to detect faults of a fifth-order two-phase nonlinear motor system.
AB - Small faults are difficult to be detected under noisy conditions. And the small sensor faults will introduce modeling errors in the observation equations. Therefore, small faults need be detected successfully and quickly. A novel small fault detection (FD) method is proposed using the residuals generated by the unscented Kalman filter (UKF) for a fifth-order two-phase nonlinear motor. Firstly, the introduction of the UKF is given. Secondly, on the basis of the UKF, a fault detection scheme based on a local approach is proposed. The local approach is used to detect small faults from residuals obtained from the UKF. Besides, the comparison between local approach and generalized likelihood test approach is introduced to illustrate the effectiveness of the proposed method. Finally, the proposed fault detection method is applied to detect faults of a fifth-order two-phase nonlinear motor system.
KW - Fault detection
KW - Local approach
KW - Noisy conditions
KW - Nonlinear motor system
KW - Unscented Kalman filter
UR - https://www.scopus.com/pages/publications/84954519269
U2 - 10.1109/IHMSC.2015.177
DO - 10.1109/IHMSC.2015.177
M3 - 会议稿件
AN - SCOPUS:84954519269
T3 - Proceedings - 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2015
SP - 304
EP - 307
BT - Proceedings - 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2015
Y2 - 26 August 2015 through 27 August 2015
ER -