scholarly journals Fault diagnosis for permanent magnet synchronous generator under chaos conditions：LMI approach

2013 ◽  
Vol 62 (15) ◽  
pp. 150507
Author(s):  
Wu Zhong-Qiang ◽  
Yang Yang ◽  
Xu Chun-Hua
Keyword(s):  
Fault Diagnosis ◽  
Permanent Magnet ◽  
Synchronous Generator ◽  
Permanent Magnet Synchronous Generator

scholarly journals LPV Model Based Sensor Fault Diagnosis and Isolation for Permanent Magnet Synchronous Generator in Wind Energy Conversion Systems

2018 ◽  
Vol 8 (10) ◽  
pp. 1816 ◽  
Author(s):  
Zhimin Yang ◽  
Yi Chai ◽  
Hongpeng Yin ◽  
Songbing Tao
Keyword(s):  
Fault Diagnosis ◽  
Permanent Magnet ◽  
Synchronous Generator ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Permanent Magnet Synchronous Generator ◽  
Multiple Sensor ◽  
Residual Generator

This paper deals with the current sensor fault diagnosis and isolation (FDI) problem for a permanent magnet synchronous generator (PMSG) based wind system. An observer based scheme is presented to detect and isolate both additive and multiplicative faults in current sensors, under varying torque and speed. This scheme includes a robust residual generator and a fault estimation based isolator. First, the PMSG system model is reformulated as a linear parameter varying (LPV) model by incorporating the electromechanical dynamics into the current dynamics. Then, polytopic decomposition is introduced for H ∞ design of an LPV residual generator and fault estimator in the form of linear matrix inequalities (LMIs). The proposed gain-scheduled FDI is capable of online monitoring three-phase currents and isolating multiple sensor faults by comparing the diagnosis variables with the predefined thresholds. Finally, a MATLAB/SIMULINK model of wind conversion system is established to illustrate FDI performance of the proposed method. The results show that multiple sensor faults are isolated simultaneously with varying input torque and mechanical power.

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