Wind turbine condition monitoring by detecting the transient period of a single generator stator current signal

A wind farm often consists of a number of wind turbines (WTs) operating simultaneously, which not only challenges the operation of the wind farm but makes the condition monitoring (CM) more costly than ever before if each turbine is equipped with a standard commercially available WT CM system (e.g. SKF's WindCon system). With the continual increase of wind farm size, the operator is under increasing pressure to lower the CM cost so that the energy cost can be accordingly reduced in the end. The research presented in this paper is for meeting such a requirement by developing a new cost-effective CM technique based on detecting the transient period of a single WT generator stator current signal. Instead of collecting multiple numbers of CM signals from WT key components, the new technique relies on the use of only a single electric current signal collected from WT generator stator. Moreover, the new technique directly deals with the time waveform of the signal without using any artificial transforms (e.g. Fourier transform). Therefore, it is potentially able to provide more reliable CM result. Experiments have shown that the proposed technique is valid for detecting both the electrical and mechanical faults emulated on a specially designed WT drive train test rig.

[1]  Michele Vadursi,et al.  On the use of the warblet transform for instantaneous frequency estimation , 2005, Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510).

[2]  LJubisa Stankovic,et al.  Quantitative Performance Analysis of Scalogram as Instantaneous Frequency Estimator , 2008, IEEE Transactions on Signal Processing.

[3]  Wenxian Yang,et al.  Wind Turbine Condition and Power Quality Monitoring by the Approach of Fast Individual Harmonic Extraction , 2013 .

[4]  Wenxian Yang,et al.  An online technique for condition monitoring the induction generators used in wind and marine turbines , 2013 .

[5]  W. M. Zhang,et al.  Polynomial Chirplet Transform With Application to Instantaneous Frequency Estimation , 2011, IEEE Transactions on Instrumentation and Measurement.

[6]  Peter Tavner,et al.  Review of condition monitoring of rotating electrical machines , 2008 .

[7]  Allan Kardec Barros,et al.  Heart instantaneous frequency (HIF): an alternative approach to extract heart rate variability , 2001, IEEE Transactions on Biomedical Engineering.

[8]  Yingning Qiu,et al.  Wind turbine condition monitoring: technical and commercial challenges , 2014 .

[9]  Wenxian Yang,et al.  Condition Monitoring of the Power Output of Wind Turbine Generators Using Wavelets , 2010, IEEE Transactions on Energy Conversion.

[10]  Leopoldo Angrisani,et al.  A measurement method based on a modified version of the chirplet transform for instantaneous frequency estimation , 2002, IEEE Trans. Instrum. Meas..

[11]  Wenxian Yang,et al.  Cost-Effective Condition Monitoring for Wind Turbines , 2010, IEEE Transactions on Industrial Electronics.

[12]  R. G. Wiley,et al.  A practical procedure for estimation of instantaneous frequency , 1981, IEEE Transactions on Instrumentation and Measurement.

[13]  Paulo F. Ribeiro,et al.  Power Systems Signal Processing for Smart Grids , 2013 .

[14]  Wei Qiao,et al.  Imbalance Fault Detection of Direct-Drive Wind Turbines Using Generator Current Signals , 2012, IEEE Transactions on Energy Conversion.

[15]  B.C. Lovell,et al.  The statistical performance of some instantaneous frequency estimators , 1992, IEEE Trans. Signal Process..

[16]  Srdjan Stankovic,et al.  An analysis of instantaneous frequency representation using time-frequency distributions-generalized Wigner distribution , 1995, IEEE Trans. Signal Process..