Wind and Structures

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Vibration-based identification of rotating blades using Rodrigues' rotation formula from a 3-D measurement

  • Loh, Chin-Hsiung (Department of Civil Engineering, National Taiwan University) ;
  • Huang, Yu-Ting (Department of Civil Engineering, National Taiwan University) ;
  • Hsiung, Wan-Ying (Department of Civil Engineering, National Taiwan University) ;
  • Yang, Yuan-Sen (Department of Civil Engineering, National Taipei University of Technology) ;
  • Loh, Kenneth J. (Department of Structural Engineering, University of California at San Diego)
  • Received : 2015.09.03
  • Accepted : 2015.12.06
  • Published : 2015.12.25
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Abstract

In this study, the geometrical setup of a turbine blade is tracked. A research-scale rotating turbine blade system is setup with a single 3-axes accelerometer mounted on one of the blades. The turbine system is rotated by a controlled motor. The tilt and rolling angles of the rotating blade under operating conditions are determined from the response measurement of the single accelerometer. Data acquisition is achieved using a prototype wireless sensing system. First, the Rodrigues' rotation formula and an optimization algorithm are used to track the blade rolling angle and pitching angles of the turbine blade system. In addition, the blade flapwise natural frequency is identified by removing the rotation-related response induced by gravity and centrifuge force. To verify the result of calculations, a covariance-driven stochastic subspace identification method (SSI-COV) is applied to the vibration measurements of the blades to determine the system natural frequencies. It is thus proven that by using a single sensor and through a series of coordinate transformations and the Rodrigues' rotation formula, the geometrical setup of the blade can be tracked and the blade flapwise vibration frequency can be determined successfully.

Keywords

Acknowledgement

Supported by : Ministry of Science and Technology of the Republic of China

References

  1. Barlas, T. and van Kuik, G. (2010), "Review of the state of the art in smart rotor control research for wind turbines", Prog. Aerosp. Sci., 46(1), 1-27. https://doi.org/10.1016/j.paerosci.2009.08.002
  2. Bart, P. and Guido, D.R. (1999), "Reference-based stochastic subspace identification for output-only modal analysis", Mech. Syst. Signal Pr., 13(6) 855-878. https://doi.org/10.1006/mssp.1999.1249
  3. Belongie, Serge, Rodrigues' Rotation Formula, From MathWorld--A Wolfram Web Resource, created by Eric W. Weisstein. http://mathworld.wolfram.com/RodriguesRotationFormula.html.
  4. Brinker, R., Zhang, L. and Andersen, P. (2000), "Modal identification for ambient responses using frequency domain decomposition", Proceedings of IMAC XVIII.
  5. Ciang, C.C., Lee, J.R. and Bang, H.J. (2008), "Structural health monitoring for a wind turbine system: A review of damage detection methods", Measurement Sci. Technol., 19 (122001), 1-20.
  6. Fan, Z., Feng, X. and Zhou, Z. (2013), "A novel transmissibility concept based on wavelet transform for structural damage detection", Smart Struct. Syst., 12(3-4), 291-308. https://doi.org/10.12989/sss.2013.12.3_4.291
  7. Ghoshal, A., Sundaresan, M.J., Schulz, M.J. and Pei, F.P. (2000), "Structural health monitoring techniques for wind turbine blades", J. Wind Eng. Ind. Aerod., 85(3), 309- 324. https://doi.org/10.1016/S0167-6105(99)00132-4
  8. James III, G.H. (1996), Development of structural health monitoring techniques using dynamic testing, SANDIA REPORT: SAND96-0810, UC-706, April.
  9. Lading, L., McGugan, M., Sendrup, P., Rheinlander, J. and Rusborg, J. (2002), Fundamentals for Remote Structural Health Monitoring of Wind Turbine Blades - a Preproject. Annex B - Sensors and Non-Destructive Testing Methods for Damage Detection in Wind Turbine Blades Riso National Laboratory, Roskilde, Denmark.
  10. Loh, C.H., Liu, Y.C. and Ni, Y.Q. (2012), "SSA-based stochastic subspace identification of structures from output-only vibration measurements", Smart Struct. Syst., 10(4-5), 331-351. https://doi.org/10.12989/sss.2012.10.4_5.331
  11. Loh, C.H. and Liu, Y.C. (2013), "Application of recursive SSA as data pre-processing filter for stochastic subspace identification", Smart Struct. Syst., 11(1) 19-34.
  12. Murray, R.M., Li, Z. and Sastry, S.S. (1994), A Mathematical Introduction to Robotic Manipulation, Boca Raton, FL: CRC Press.
  13. Murtagh, P.J., Basu, B. and Broderick, B.M. (2005), "Along-wind response of a wind turbine tower with blade coupling subjected to rotationally sampled wind loading", Eng. Struct., 27(8), 1209-1219. https://doi.org/10.1016/j.engstruct.2005.03.004
  14. Ness, S. and Sherlock, C.N. (1996), Nondestructive Testing Handbook, Vol. 10, Nondestructive Testing Overview, American Society for Nondestructive Testing.
  15. Simmermacher, T., James III, G.H. and Hurtado, J.E. (1997), "Structural health monitoring of wind turbines", Proceedings of the International Workshop on Structural Health Monitoring, Stanford, CA, September 18-20.

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