Skip to main content
SpringerLink
Log in

Vibration-Based Condition Assessment Methods

  • Chapter
  • First Online:
Condition Monitoring Algorithms in MATLAB®

Part of the book series: Springer Tracts in Mechanical Engineering ((STME))

  • 1690 Accesses

Abstract

This Chapter turns previously introduced signal processing techniques into particular machine diagnostic methods. It proposed general division into scalar-based diagnostic analysis and figure-based diagnostic analysis. The Chapter gives many practical recipes concerning calcualtion of both types of assessment methods. Scalar indicators covered in this Chapter range from basic statistical indicators to conceptual advanced markers. Presented figures range from basic time or frequency-domain plots to recent, advanced 3D maps.

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 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 279.99
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

Notes

  1. 1.

    Available @ https://home.agh.edu.pl/~ajab/.

  2. 2.

    It is recommended to investigate Table 5.4 simultaneously with Table 4.5.

  3. 3.

    The author has encountered some engineers who understand “waterfall” and “cascade” plots completely opposite, so the names are not claimed constant.

  4. 4.

    See Sect. 4.2.2 for details.

References

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

    Google Scholar 

  2. Bruel and Kjaer (1983) Primer: vibration testing. Denmark. Available https://www.bksv.com/media/doc/br0094.pdf

  3. Yoon J et al (2014) Planetary gearbox fault diagnosis using a single piezoelectric strain sensor. In: Proceedings of the annual conference on the prognostics and health management society 2014, pp 118–127

    Google Scholar 

  4. Sharma V, Parey A (2016) A review of gear fault diagnosis using various condition indicators. Procedia Eng 144:253–263

    Article  Google Scholar 

  5. Vecer P, Kreidl M, Smid R (2005) Condition indicators for gearbox condition monitoring systems, Czech Technical University in Prague. Acta Polytechn 45(6)

    Google Scholar 

  6. Zhu J et al (2014) Survey of condition indicators for condition monitoring systems. In: Proceedings of the annual conference on the prognostics and health management society 2014

    Google Scholar 

  7. Yongzhi Qu et al (2014) Gearbox tooth cut fault diagnostics using acoustic emission and vibration sensors—a comparative study. Sensors 14:1372–1393

    Article  Google Scholar 

  8. Maczak J, Jasinski M (2017) Model-based detection of local defects in gears. Arch Appl Mech

    Google Scholar 

  9. Dynamic Energy Index (DEI), GE Energy Fact Sheet Template, Bently Nevada Asset Condition Monitoring, 2011

    Google Scholar 

  10. Zapalla D et al (2013) Sideband algorithm for automatic wind turbine gearbox fault detection and diagnosis (Preprint). European Wind Energy Association 2013 Annual Event, Vienna, Austria. Available at https://www.nrel.gov/docs/fy13osti/57395.pdf

  11. Hanna J et al (2011) Detection of wind turbine gear tooth defects using sideband energy Ratio™. China Wind Power 19–21 (Beijing, China)

    Google Scholar 

  12. Randall RB (2016) A history of Cepstrum analysis and its application to mechanical problems. Mech Syst Signal Process 97

    Google Scholar 

  13. Barszcz T, Jablonski A (2011) A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram. Mech Syst Signal Process 25(1):431–451

    Article  Google Scholar 

  14. Antoni J (2007) Fast computation of the kurtogram for the detection of transient faults. Mech Syst Signal Process 21(1):108–124

    Article  Google Scholar 

  15. Urbanek J et al (2012) Detection of signal component modulations using modulation intensity distribution. Mech Syst Signal Process 28:399–413

    Article  Google Scholar 

  16. Antoni J (2009) Cyclostationarity by examples. Mech Syst Signal Process 23(4):987–1036

    Article  Google Scholar 

  17. Dziedziech K, Dworakowski Z, Jablonski A (2019) Epicyclic gearbox fault detection by instantaneous circular pitch cycle map. Mech Syst Signal Process 121(12):600–614

    Article  Google Scholar 

  18. Urbanek J et al (2016) Application of angular-temporal spectrum to exploratory analysis of generalized angular-temporal deterministic signals. Appl Acoust 109:27–36

    Article  Google Scholar 

  19. Maczak J (2013) Local meshing plane analysis as a source of information about the gear quality. Mech Syst Signal Process 38(1):154–164

    Article  Google Scholar 

  20. Zielinski T (2013) Digital signal processing. From theory to applications. (Original tile in Polish: Cyfrowe przetwarzanie sygnalow. Od teorii do zastosowań). WKL

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Robotics and Mechatronics, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, Krakow, Poland

    Adam Jablonski

Authors
  1. Adam Jablonski
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Adam Jablonski .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Jablonski, A. (2021). Vibration-Based Condition Assessment Methods. In: Condition Monitoring Algorithms in MATLAB®. Springer Tracts in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-62749-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-62749-2_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62748-5

  • Online ISBN: 978-3-030-62749-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation