Progress In Electromagnetics Research
ISSN: 1070-4698, E-ISSN: 1559-8985
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By J. Moll, J. Simon, M. Malzer, V. Krozer, D. Pozdniakov, R. Salman, M. Durr, M. Feulner, A. Nuber, and H. Friedmann

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This paper presents an imaging radar system for structural health monitoring (SHM) of wind turbine blades. The imaging radar system developed here is based on two frequency modulated continuous wave (FMCW) radar sensors with a high output power of 30 dBm. They have been developed for the frequency bands of 24,05 GHz-24,25 GHz and 33.4 GHz-36.0 GHz, respectively. Following the successful proof of damage detection and localization in laboratory conditions, we present here the installation of the sensor system at the tower of a 2 MW wind energy plant at 95 m above ground. The realization of the SHM-system will be introduced including the sensor system, the data acquisition framework and the signal processing procedures. We have achieved an imaging of the rotor blades using inverse synthetic aperture radar techniques under changing environmental and operational condition. On top of that, it was demonstrated that the front wall and back wall radar echo can be extracted from the measured signals demonstrating the full penetration of wind turbine blades during operation.

J. Moll, J. Simon, M. Malzer, V. Krozer, D. Pozdniakov, R. Salman, M. Durr, M. Feulner, A. Nuber, and H. Friedmann, "Radar Imaging System for in-Service Wind Turbine Blades Inspections: Initial Results from a Field Installation at a 2 MW Wind Turbine," Progress In Electromagnetics Research, Vol. 162, 51-60, 2018.

1. Marquez, F. P. G., J. M. P. Perez, A. P. Marugan, and M. Papaelias, "Identification of critical components of wind turbines using FTA over the time," Renewable Energy, Vol. 87, 869-883, March 2016.

2. Yang, R., Y. He, and H. Zhang, "Progress and trends in nondestructive testing and evaluation for wind turbine composite blade," Renewable and Sustainable Energy Reviews, Vol. 60, 1225-1250, July 2016.

3. Ciang, C. C., J.-R. Lee, and H.-J. Bang, "Structural health monitoring for a wind turbine system: A review of damage detection methods," Measurement Science and Technology, Vol. 19, No. 12, 122001, December 2008.

4. Adams, D., J. White, M. Rumsey, and C. Farrar, "Structural health monitoring of wind turbines: Method and application to a HAWT," Wind Energy, Vol. 14, No. 4, 603-623, May 2011.

5. Lu, B., Y. Li, X. Wu, and Z. Yang, "A review of recent advances in wind turbine condition monitoring and fault diagnosis," Power Electronics & Machines in Wind Applications, PEMWA, 1-7, 2009.

6. Qiao, W. and D. Lu, "A survey on wind turbine condition monitoring and fault diagnosis — Part I: Components and subsystems," IEEE Transactions on Industrial Electronics, Vol. 62, No. 10, 6536-6545, October 2015.

7. Zhou, H. F., H. Y. Dou, L. Z. Qin, Y. Chen, Y. Q. Ni, and J. M. Ko, "A review of full-scale structural testing of wind turbine blades," Renewable and Sustainable Energy Reviews, Vol. 33, 177-187, May 2014.

8. Kharkovsky, S. and R. Zoughi, "Microwave and millimeter wave nondestructive testing and evaluation — Overview and recent advances," IEEE Instrumentation & Measurement Magazine, Vol. 10, No. 2, 26-38, April 2007.

9. Zhu, Y.-K., G.-Y. Tian, R.-S. Lu, and H. Zhang, "A review of optical NDT technologies," Sensors, Vol. 11, No. 12, 7773-7798, August 2011.

10. Li, Z., A. Haigh, C. Soutis, A. Gibson, and R. Sloan, "Microwaves sensor for wind turbine blade inspection," Applied Composite Materials, November 2016.

11. Fukasawa, R., "Terahertz imaging: Widespread industrial application in non-destructive inspection and chemical analysis," IEEE Transactions on Terahertz Science and Technology, Vol. 5, No. 6, 1121-1127, 2015.

12. Wetzel, K., K. Lee, A. Tran, B. Stakenborghs, and R. J. Woodward, "Volumetric inspection of wind turbine blades using a microwave interferometric technique," Materials Evaluation, 477-484, 2016.

13. Ghasr, M. T., M. J. Horst, M. R. Dvorsky, and R. Zoughi, "Wideband microwave camera for real-time 3-D imaging," IEEE Transactions on Antennas and Propagation, Vol. 65, No. 1, 258-268, January 2017.

14. Hsu, D. K., K.-S. Lee, J.-W. Park, Y.-D. Woo, and K.-H. Im, "NDE inspection of terahertz waves in wind turbine composites," International Journal of Precision Engineering and Manufacturing, Vol. 13, No. 7, 1183-1189, July 2012.

15. Li, C., Z. Peng, T.-Y. Huang, T. Fan, F.-K. Wang, T.-S. Horng, J.-M. Munoz-Ferreras, R. GomezGarcia, L. Ran, and J. Lin, "A review on recent progress of portable short-range noncontact microwave radar systems," IEEE Transactions on Microwave Theory and Techniques, 1-15, 2017.

16. Moll, J., P. Arnold, M. M¨alzer, V. Krozer, D. Pozdniakov, R. Salman, S. Rediske, M. Scholz, H. Friedmann, and A. Nuber, "Radar-based structural health monitoring of wind turbine blades: The case of damage detection," Structural Health Monitoring: An International Journal, 147592171772144, August 2017.

17. Arnold, P., J. Moll, M. Malzer, V. Krozer, D. Pozdniakov, R. Salman, S. Rediske, M. Scholz, H. Friedmann, and A. Nuber, "Radar-based structural health monitoring of wind turbine blades: The case of damage localization," Wind Energy, January 2018.

18. Moll, J., V. Krozer, P. Arnold, M. D¨urr, R. Zimmermann, R. Salman, D. H¨ubsch, H. Friedmann, A. Nuber, M. Scholz, and P. Kraemer, "Radar-based structural health monitoring of wind turbine blades," 19th World Conference on Non-Destructive Testing, 1-8, Munich, Germany, 2016.

19. Moll, J., M. Malzer, J. Simon, V. Krozer, M. Feulner, H. Friedmann, A. Nuber, R. Salman, D. Pozdniakov, and M. Durr, "Field demonstration of radar-based SHM of wind turbine blades at a 2 MW wind turbine: Installation, data acquisition and signal analysis," 11th International Workshop on Structural Health Monitoring, 1-8, Stanford, USA, 2017.

20. Scholz, N., J. Moll, M. Malzer, K. Nagovitsyn, and V. Krozer, "Random bounce algorithm: realtime image processing for the detection of bats and birds: Algorithm description with application examples from a laboratory flight tunnel and a field test at an onshore wind energy plant," Signal, Image and Video Processing, Vol. 10, No. 8, 1449-1456, November 2016.

21. Moll, J. and V. Krozer, "Radar-based mechanical vibration sensing for structural health monitoring applications: A comparison of radar transceiver measurements at 24 GHz and 100 GHz," 8th European Workshop on Structural Health Monitoring, 1-6, 2016.

22. Moll, J., M. Malzer, V. Krozer, D. Pozdniakov, R. Salman, J. M. Beetz, and M. Kossl, "Activity monitoring of bats in a laboratory flight tunnel using a 24 GHz FMCW radar system," 11th European Conference on Antennas and Propagation, 2541-2545, Paris, France, 2017.

23. Soumekh, M., Synthetic Aperture Radar Signal Processing with MATLAB Algorithms, Wiley, New York, OCLC: 833493976, 1999.

24. Sakamoto, T., T. Sato, P. Aubry, and A. Yarovoy, "Frequency-domain Kirchhoff migration for near-field radar imaging," IEEE Conference on Antenna Measurements & Applications, 1-4, 2015.

25. Sakamoto, T., T. Sato, P. J. Aubry, and A. G. Yarovoy, "Ultra-wideband radar imaging using a hybrid of kirchhoff migration and stolt F-K migration with an inverse boundary scattering transform," IEEE Transactions on Antennas and Propagation, Vol. 63, No. 8, 3502-3512, 2015.

26. Zhuge, X. and A. G. Yarovoy, "Three-dimensional near-field MIMO array imaging using range migration techniques," IEEE Transactions on Image Processing, Vol. 21, No. 6, 3026-3033, 2012.

27. Gorham, L. A. and L. J. Moore, "SAR image formation toolbox for MATLAB,", 769906-769906-13, April 2010.

28. Arnold, P., J. Moll, and V. Krozer, "Design of a sparse antenna array for radar-based structural health monitoring of wind turbine blades," IET Radar, Sonar & Navigation, Vol. 11, No. 8, 1259-1265, August 2017.

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