Sensor Fault Diagnosis for Improving the Availability of Electrical Drives

被引:0
|
作者
Diao, S. [1 ]
Makni, Z. [1 ]
Bisson, J-F. [1 ]
Diallo, D. [2 ]
Marchand, C. [2 ]
机构
[1] Valeo Grp Elect Expertise & Dev Serv, 2 Rue Andre Boulle, F-94000 Creteil, France
[2] Univ Paris Sud, CNRS, Lab Genie Elect Paris, UMR 8507, F-91192 Gif Sur Yvette, France
来源
39TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2013) | 2013年
关键词
Electrical drive; Extended Kalman Filter; Fault detection; fault diagnosis; fault isolation; Model Reference Adaptive System; Permanent magnet Motor; observers; sensor fault;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The paper describes a Fault Detection and Diagnosis structure of mechanical and current sensors faults of a Permanent Magnet Synchronous Machine (PMSM) drive. The method is based on two interconnected observers: an Extended Kalman Filter (EKF) and a Model Reference Adaptive System (MRAS) observer. The EKF, thanks to its optimality is designed to estimate the position in case of mechanical sensor fault and despite sensor current fault. The MRAS estimates the phase currents using the actual position and speed. The computation and sort of the residuals (difference between measured and estimated values) allows the fault isolation. The structure is evaluated on a 1.1 kW test bed with mechanical and phase current sensor faults. The experimental results are so far promising with the capability of detection and diagnosis of the proposed structure.
引用
收藏
页码:3108 / 3113
页数:6
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