Skip to main content

Joint Time–Frequency Analysis of the Electrical Signal

  • Chapter
Power Quality

Part of the book series: Power Systems ((POWSYS))

Abstract

As is well known, a signal may be described in numerous ways. Classically, signals have been studied as a function of time or as a function of frequency separately. In these separate fields, time-domain functions indicate the evolution of the signal amplitude over time, while a function in the frequency domain shows how quickly such changes takes place.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Gröchenig K (2001) Foundations of Time–Frequency Analysis. Birkhäuser, Boston

    MATH  Google Scholar 

  2. Hogan J, Lakey J (2005) Time–Frequency and Time–Scale Methods. Birkhäuser, Boston

    MATH  Google Scholar 

  3. Ben–Arie K, Raghunath K (1992) Image expansion by non–orthogonal wavelets for optimal template matching, Pattern Recognition, Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 650–654.

    Google Scholar 

  4. Bravo JC, Borrás D, Castilla M, Montaño JC, López A, Gutiérrez J, (2005), Joint wavelet–Fourier analysis of power system disturbances, Proc. of the 9CHLIE05, Marbella, Spain.

    Google Scholar 

  5. Montaño JC, Castilla M, Bravo JC, López A, Gutiérrez J, Borrás D, (2004), Analysis of Electrical Signal Disturbances. A New Strategy, Proc. of the ICREPQ04, Barcelona, Spain.

    Google Scholar 

  6. Borrás D, Bravo JC, Montaño JC, Castilla M, López A, Gutiérrez J, (2005), A new advanced hybrid analysis method in power systems, IDAACS 2005, Sofia, Bulgaria.

    Google Scholar 

  7. Borrás D, Castilla M, Moreno N, Montaño JC (2001) Wavelet and neural structure: a new tool for diagnostic of power system disturbances. IEEE Trans on Industry App 37(1):184–190

    Article  Google Scholar 

  8. Dugan RC, McGranaghan MF, Beaty HW (1996) Electrical Power Systems Quality. McGraw–Hill, NY

    Google Scholar 

  9. Arrillaga J, Bradley DA, Bodger PS (1985) Power Systems Harmonics. JohnWiley & Sons, New York

    Google Scholar 

  10. Derek AP (1995) Power Electronic Converter Harmonics. IEEE Press, New York

    Google Scholar 

  11. Pillary P, Ribeiro P, Pan Q (1996) Power quality modeling using wavelets, IEEE Proc. of the 7th International Conference on Harmonics and Quality of Power (ICHQP), Las Vegas, Nevada, USA, 625–631.

    Google Scholar 

  12. Angrisani L, Daponte P, D'Apuzzo M, Testa A, (1998), A Measurement Method Based on the Wavelet Transform for Power Quality Analysis, IEEE Transactions on Power Delivery, 13, 4.

    Google Scholar 

  13. Robertson DC, Camps OI, Mayer JS, Gish WB (1996) Wavelets and electromagnetic power system transients. IEEE Trans Power Delivery 11(2):1050–1058

    Article  Google Scholar 

  14. Poisson O, Rioual R, Meunier M (2000) Detection and Measurement of Power Quality Disturbances Using Wavelet Transform. IEEE Trans Power Delivery 15(3):1039–1044

    Article  Google Scholar 

  15. Bollen MHJ (2000) Understanding Power Quality Problems. IEEE Press, New York

    Google Scholar 

  16. Martínez–Velasco JA (1997) Computer Analysis of Electric Power System Transients. IEEE Press, New York

    Google Scholar 

  17. Mallat S (2001) A Wavelet Tour of Signal Processing. Academic Press, London

    Google Scholar 

  18. Daubechies I (1990) The wavelet transform, time–frequency localization, and signal analysis. IEEE Trans lnfinn Theory, 961–1005.

    Google Scholar 

  19. Wickerhauser MV (1994) Adapted Wavelet Analysis from theory to software. IEEE Press, New York

    MATH  Google Scholar 

  20. Gröchenig K (2003) Uncertainty principles for time–frequency representations. In Advances in Gabor Analysis, pp. 11–30. Birkhäuser, Boston

    Google Scholar 

  21. Qian S, Chen D (1996) Joint Time–Frequency analysis. Methods and applications. Englewood Cliffs, NJ, Prentice Hall

    Google Scholar 

  22. Qian S, Chen D, (1999), Understanding the nature of signals whose power spectra change with time. Joint analysis, IEEE Signal Processing Magazine.

    Google Scholar 

  23. Qian S, Chen D (1993) Discrete Gabor transform. IEEE Trans Signal Processing 41(7):2429–2439

    Article  MATH  Google Scholar 

  24. Farkash S, Raz S (1990) Time–variant filtering via the Gabor expansion, Signal Processing I/: Theories and Applications. Elsevier, New York, pp 509–512

    Google Scholar 

  25. Hlawatsch F and Krattcnthaler W (1992) Bilinear signal synthesis. IEEE Trans Signal Processing 40(2):352–363

    Article  MATH  Google Scholar 

  26. Walnut DF (2002) An Introduction to Wavelet Analysis. Birkhäuser, Boston

    MATH  Google Scholar 

  27. Mallat S (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans on Pattern Anal and Mach Intell 11:674–693

    Article  MATH  Google Scholar 

  28. Burrus CS, Gopinath RA, Guo H (1998) Introduction to Wavelets and Wavelet Transforms. Prentice Hall, New Jersey

    Google Scholar 

  29. Kumar PS, Satish DL (1998) Multiresolution Signal Decomposition: A new tool for fault detection in power transformers during impulse test. IEEE Trans on Power Delivery, 13, 4.

    Google Scholar 

  30. Cohen L, (1995), Time–frequency Analysis, Englewood Cliffs, Nat. Inst., Prentice Hall.

    Google Scholar 

  31. Yin Q, Ni Z, Qian S, Chen D, (1997), Adaptive oriented orthogonal projective decomposition, J. Electron. (Chinese), 25, 4, 52–58.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Juan-Carlos Montaño , Juan-Carlos Bravo or María-Dolores Borrás .

Editor information

Antonio Moreno-Muñoz

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Montaño, JC., Bravo, JC., Borrás, MD. (2007). Joint Time–Frequency Analysis of the Electrical Signal . In: Moreno-Muñoz, A. (eds) Power Quality. Power Systems. Springer, London. https://doi.org/10.1007/978-1-84628-772-5_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-84628-772-5_3

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84628-771-8

  • Online ISBN: 978-1-84628-772-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics