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Application of HHT for Online Detection of Inter-Area Short Circuits of Rotor Windings of Turbo-Generators Based on the Thermodynamics Modeling Method

  • Wang, Liguo (Dept. of Electrical Engineering, Harbin Institute of Technology) ;
  • Wang, Yi (School of Mechanical Engineering and Automation, Harbin Institute of Technology) ;
  • Xu, Dianguo (Dept. of Electrical Engineering, Harbin Institute of Technology) ;
  • Fang, Bo (Dept. of Aerospace Engineering and Mechanics, Harbin Institute of Technology) ;
  • Liu, Qinghe (Design Departments, Harbin Electric Machinery Co. Ltd.) ;
  • Zou, Jing (Dept. of Electrical Engineering, Harbin Institute of Technology)
  • Received : 2010.08.26
  • Published : 2011.09.20

Abstract

This paper focuses on monitoring and predicting the short circuit faults of the rotor windings of large turbo-generator systems. For the purpose of increasing efficiency and decreasing maintenance cost, a method that combines the HHT (Hilbert Huang Transform) with a wavelet has been studied. This method is based on analyzing a classical Albright detecting coil. Due to the Empirical Mode Decomposition (EMD) and the Intrinsic Mode Functions (IMF) of the HHT the exact location of a short circuit of rotor windings may be given. However, a part of the useful information is eliminated by the unreasonable decomposing scale of the wavelet. Based on the thermodynamics modeling method, this study was illustrated with a 50MW turbo-generator system that is installed in Northern China. The analysis results, which have very good agreement with those of a previous study, show that the method of combining the HHT with a wavelet is an effective way to analyze and predict the short circuit faults of the rotor windings of large generators, such as supercritical turbo-generator systems and wind turbo-generator systems. This work can offer a useful reference for analyzing smart grids by improving the power quality of a distribution network that is supplied by a turbo-generator system.

Keywords

References

  1. S. Han, B. Sun, C. Wu and L.-Q. He, "Dynamic characteristic analysis of power system low frequency oscillation using hilbert-huang transform," in Proceeding of IEEE PSCE, pp. 1-6, Seattle, Mar. 2009.
  2. H. Li, Y. Wang, and Y. Ma, "Ensemble empirical mode decomposition and Hilbert-Huang transform applied to bearing fault diagnosis," in Proceeding of IEEE CISP, pp. 341 -3417, Yantai, Oct. 2010.
  3. J.-G. Song, S.-h. Lin, C.-X. Zhao, and H.-J Liu, "Decomposition of seismic signal based on Hilbert-Huang transform," in Proceeding of IEEE BMEI, pp. 813-816, GuangZhou, May 2011.
  4. X. Li, T. Jing, and X. Li. "Image splicing detection based on moment features and Hilbert-Huang Transform," in Proceeding of IEEE ICITIS, pp.1127-1130, Beijing, Dec. 2010.
  5. R. Yan, R. X. Gao, "Hilbert-Huang. transform-based vibration signal analysis for machine health monitoring," Journal of Instrumentation and Measurement, Vol. 55, No. 6, pp. 2320-2329, Dec. 2007.
  6. A. R. Messina, V. Vittal. "Nonlinear, non-stationary analysis of inter area oscillations via hilbert spectral analysis," Journal of Power System, Vol. 21, No. 5, pp. 1234-1241, Aug. 2006. https://doi.org/10.1109/TPWRS.2006.876656
  7. R. Yan and R. X. Gao, "Transient Signal Analysis Based on Hilbert- Huang Transform," in Proceeding of IEEE IMTC, pp.17-19, Ottawa, May. 2005.
  8. L. Tianyun, G. Lei, C. Xiaodong, W. Hongyi, "Parameter Identification of synchronous machine based on Hilbert-Huang transform," Journal of Proceedings of the Chinese Society for Electrical Engineering, Vol. 26, No. 8, pp. 153-158, Apr. 2006.
  9. L. Xiang, G. Tang, Y. Zhu, "Vibration signal analysis of rotor system based on time-frequency attributes," in Proceeding of IEEE ICYCS, pp. 2713 -2717, Hunan, Jun. 2008.
  10. W. Jiao. "A method for time-frequency feature extraction from vibration signal based on Hilbert-Huang transform," in Proceeding of IEEE WCICA, pp. 8460- 8464, Hunan, Nov. 2008.
  11. D. S. Laila, A. R. Messina, B. C. Pal, "A refined Hilbert–Huang transform with applications to inter-area oscillation monitoring," in Proceeding of PES, pp. 610-620, Calgary, Jul. 2009.
  12. L. Lin, W. Lu, and F. Chu. "Application of AE techniques for the detection of wind turbine using Hilbert-Huang transform," in Proceeding of PHM, pp. 1-7, Macao, Jan. 2010.
  13. F. Couenne, C. Jallut, B. Maschke, M. Tayakout, and P. Breedveld, "Structured modeling for processes: a thermo-dynamical network theory," Journal of Computers and Chemical Engineering, Vol. 32, No.6, pp. 1120-1134, Apr. 2008. https://doi.org/10.1016/j.compchemeng.2007.04.012
  14. C. Schmitke and J. McPhee, "Using linear graph theory and the principle of orthogonality to model multibody, multi-domain systems," Journal of Advanced Engineering Informatics, Vol. 22, No.2, pp.147-160, Apr. 2008. https://doi.org/10.1016/j.aei.2007.08.002
  15. N. E. Huang, Z. Shen, S. R. Long and etc. "The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis," The Royal Society, pp.454: 903-995, 1998.
  16. Q. Liu, W. Cai, D. Xu, "Study of on-line detection of inter-turn short circuit in turbo-generator rotor windings," Journal of Proceedings of the Chinese Society for Electrical Engineering, Vol. 24, No. 9, pp. 234 -237, Sep. 2004.