Particle Filter-Based Estimation of Instantaneous Frequency for the Diagnosis of Electrical Asymmetries in Induction Machines

被引:29
作者
Climente-Alarcon, Vicente [1 ]
Alfonso Antonino-Daviu, Jose [2 ]
Haavisto, Ari [1 ]
Arkkio, Antero [1 ]
机构
[1] Aalto Univ, Dept Elect Engn & Automat, FI-00076 Aalto, Finland
[2] Univ Politecn Valencia, Inst Ingn Energet, Valencia 46022, Spain
关键词
Fault diagnosis; induction motors; particle filters; prognosis; time-frequency analysis; variable load; Wigner-Ville distribution (WVD); wind energy; SIGNATURE ANALYSIS; ROTOR ASYMMETRIES; WIND; GENERATORS; TRANSFORM; ALGORITHM;
D O I
10.1109/TIM.2014.2310113
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Fault diagnosis of induction machines operating under variable load conditions is still an unsolved matter. Under those regimes, the application of conventional diagnostic techniques is not suitable, since they are adapted to the analysis of stationary quantities. In this context, modern transient-based methodologies become very appropriate. This paper improves a technique, based on the application of Wigner-Ville distribution as time-frequency decomposition tool, using a particle filtering method as feature extraction procedure, to diagnose and quantify electrical asymmetries in induction machines, such as wound-rotor induction generators used in wind farms. The combination of both tools allows tracking several variable frequency harmonics simultaneously and computing their energy with high accuracy, yielding magnitudes and values similar to those obtained by the application of the fast Fourier transform in stationary operation. The experimental results show the validity of the approach for rapid speed variations, independently of any speed sensor.
引用
收藏
页码:2454 / 2463
页数:10
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