Skip to main content
SpringerLink
Log in

Gear Parameter Identification in Wind Turbines Using Diagnostic Analysis of Gearbox Vibration Signals

  • Conference paper
  • First Online:
Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

The correct diagnosis of faulty components in rotating machines requires a pre-knowledge of the characteristics of the system being monitored and the identification of the frequencies of interest. In gearboxes, the number of gear stages and the number of teeth for each gear are required to calculate the gear mesh frequencies and monitor these frequencies and their sidebands. It is not always possible to have this information available, especially in old equipment. In this chapter a fresh approach is presented to deduce such crucial information from the measured vibration signal. The approach focuses on fine tuning harmonic/sideband cursors to capture different gear mesh families. The approach is illustrated on a signal taken from a wind turbine gearbox, which poses the extra challenge of the variable speed within the measurement record. Results show the possibility of identifying the number of teeth for the first two stages with much more confidence than the planetary stage, where a trial and error approach was used to decide on the most likely combination for the ring, sun and planetary gears. This chapter sets a good practice example for understanding the system characteristics by detailed analysis of the vibration signal using finely tuned harmonic and sideband cursors.

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

Access this chapter

Log in via an institution
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 EPUB and 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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Forrester BD (1991) Time-frequency domain analysis of helicopter transmission vibration, department of defence, Aeronautical Research laboratory, Propulsion Report 180

    Google Scholar 

  2. Randall RB (2011) Vibration-based condition monitoring: industrial, aerospace and automotive applications. Wiley, NY

    Book  Google Scholar 

  3. Bonnardot F, El Badaoui M, Randall RB, Danière J, Guillet F (2005) Use of the acceleration signal of a gearbox in order to perform angular resampling (with limited speed fluctuation). Mech Sys Signal Process 19:766–785

    Article  Google Scholar 

  4. Combet F, Gelman L (2007) An automated methodology for performing time synchronous averaging of a gearbox signal without speed sensor. Mech Sys Signal Process 21(6):2590–2606

    Article  Google Scholar 

  5. Coats MD, Sawalhi N, Randall RB (2009) Extraction of Tacho information from a vibration signal for improved synchronous averaging, Paper presented at ACOUSTICS 2009, Australian Acoustical Soc, 23–25 Nov, Adelaide

    Google Scholar 

  6. Combet F, Zimroz R (2009) A new method for the estimation of the instantaneous speed relative fluctuation in a vibration signal based on the short time scale transform. Mech Sys Signal Process 23(4):1382–1397

    Article  Google Scholar 

  7. McFadden PD, Smith JD (1985) An explanation for the asymmetry of the modulation sidebands about the tooth meshing frequency in epicyclic gear vibration., Proc. I.Mech. E. Part CJ. Mech. Eng. Sci. 199(1):65–70

    Article  Google Scholar 

Download references

Acknowledgments

This work is partially supported by Mechanical Solutions Inc. and by Australia’s Defence Science and Technology Organisation (DSTO). Signals used for demonstration purposes were provided by Mechanical Solutions Inc., NJ, USA, and were obtained under a research project funded by NYSERDA. NYSERDA has not reviewed the information contained herein and the opinions expressed in this chapter do not necessarily reflect those of NYSERDA or the State of New York.

Author information

Authors and Affiliations

  1. Mechanical Engineering Department, Prince Mohammad Bin Fahd University (PMU), Al Khobar, Dhahran, 31952, Saudi Arabia

    Nader Sawalhi

  2. School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, 2052, Australia

    Robert B. Randall

Authors
  1. Nader Sawalhi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Robert B. Randall
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nader Sawalhi .

Editor information

Editors and Affiliations

  1. Engineering Department, University of Ferrara, Ferrara, Italy

    Giorgio Dalpiaz

  2. Department of Science and Engineering Methods, University of Modena and Reggio Emilia, Reggio Emilia, Italy

    Riccardo Rubini

  3. Engineering Department, University of Ferrara, Ferrara, Italy

    Gianluca D'Elia

  4. Department of Science and Engineering Methods, University of Modena and Reggio Emilia, Reggio Emilia, Italy

    Marco Cocconcelli

  5. Mechanical Engineering Department, National School of Engineers of Sfax, Sfax, Tunisia

    Fakher Chaari

  6. Institute of Mining Engineering, Diagnostics and Vibro-Acoustics Science Laboratory, Wrocław University of Technology, Wrocław, Poland

    Radoslaw Zimroz

  7. Institute of Mining Engineering, Diagnostics and Vibro-Acoustics Science Laboratory, Wrocław University of Technology, Wrocław, Poland

    Walter Bartelmus

  8. Mechanical Engineering Department, National School of Engineers of Sfax, Sfax, Tunisia

    Mohamed Haddar

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sawalhi, N., Randall, R.B. (2014). Gear Parameter Identification in Wind Turbines Using Diagnostic Analysis of Gearbox Vibration Signals. In: Dalpiaz, G., et al. Advances in Condition Monitoring of Machinery in Non-Stationary Operations. Lecture Notes in Mechanical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39348-8_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39348-8_23

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39347-1

  • Online ISBN: 978-3-642-39348-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation