Inspection enhancement of wind turbine blades using novel signal-processing approaches

In this paper, a signal-processing approach is applied to enhance the inspection of wind turbine blades. This method starts with a time-frequency representation of signals, where a generalized time-bandwidth product method integrated with short-time Fourier transform is developed and applied. It is followed by the utilization of convex set to help justify the contour map such that the blade-condition monitoring can be better realized. Through test signals received from the sensors, it was found that the proposed approach would discriminate the damaged structure from the healthy one under several scenarios, thereby ensuring a higher efficiency of wind power generation.

[1]  Anindya Ghoshal,et al.  Structural health monitoring techniques for wind turbine blades , 2000 .

[2]  Robert J. Marks,et al.  Kernel synthesis for generalized time-frequency distributions using the method of alternating projections onto convex sets , 1994, IEEE Trans. Signal Process..

[3]  Walter Musial,et al.  Determining equivalent damage loading for full-scale wind turbine blade fatigue tests , 2000 .

[4]  PETER SANTAGO,et al.  Using Convex Set Techniques for Combined Pixel and Frequency Domain Coding of Time-Varying Images , 1987, IEEE J. Sel. Areas Commun..

[5]  Orhan Arikan,et al.  Short-time Fourier transform: two fundamental properties and an optimal implementation , 2003, IEEE Trans. Signal Process..

[6]  W. N. Martin,et al.  A Continuous Sensor to Measure Acoustic Waves in Plates , 2001 .

[7]  M. Lange,et al.  Physical Approach to Short-Term Wind Power Prediction , 2005 .

[8]  Les E. Atlas,et al.  Optimizing time-frequency kernels for classification , 2001, IEEE Trans. Signal Process..

[9]  T.S. Basso,et al.  IEEE 1547 series of standards: interconnection issues , 2004, IEEE Transactions on Power Electronics.

[10]  A. G. Beattie,et al.  Acoustic emission monitoring of a wind turbine blade during a fatigue test , 1997 .

[11]  A. G. Dutton,et al.  Acoustic Emission Monitoring of Small Wind Turbine Blades , 2002 .

[12]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[13]  C. Doncarli,et al.  Optimal kernels of time-frequency representations for signal classification , 1998, Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380).