Skip to main content
SpringerLink
Log in

Vibration-based fault diagnosis of dynamic rotating systems for real-time maintenance monitoring

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

This paper presents a diagnostic study on the monitoring, detection, and localization of faults in mechanical rotor dynamic systems. It is well known that the vital function of machine condition monitoring relies on the ability to reliably measure the “vital signs” of a machine, of which vibration is among the most important. The current diagnostic methods and other measurement and detection tools now allow for a much broader assessment of a machine’s condition from its monitored vibration than simply checking the vibration level against the healthiest machines, i.e., the machine’s vibration levels will exceed or have already exceeded the “normal” or the “allowable” levels based on experience for the machine. With this in perspective, this paper presents a study on the monitoring of bearing imbalance and failure through vibration analysis. The detection of imbalance and early deterioration of a bearing is highlighted by the use of a temporal quantity and the kurtosis. The proposed methodology can easily detect the most frequent imbalance and bearing faults and reflect their severity. It allows making better recommendations and maintenance decisions. It allows the development of a new form of maintenance commonly called conditional maintenance as well as the evaluation of predictive maintenance.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

Not applicable.

Code availability

Not applicable.

References

  1. Renforth, Lee, et al., (2013) Continuous, remote on-line partial discharge (OLPD) monitoring of HV EX/ATEX motors in the oil and gas industry. Industry Applications Society 60th Annual Petroleum and Chemical Industry Conference. IEEE

  2. Pennacchi, Paolo, et al., (2011) An experimental based assessment of the deviation of the bearing characteristic frequencies. proceedings of the 6th International Conference Acoustic and Vibratory Surveillance Methods and Diagnostic Techniques. Institute of Technology of Chartres.

  3. Borghesani P et al (2013) Application of cepstrum pre-whitening for the diagnosis ofbearing faults under variable speed conditions. Mech Syst Sig Process 36(2):370–384

    Article  Google Scholar 

  4. Liang M et al (2010) An energy operator approach to joint application of amplitude and frequency-demodulations for bearing fault detection. Mech Syst Sig Process 24(5):1473–1494

    Article  Google Scholar 

  5. Vishwakarma M, Purohit R, Harshlata V, Rajput P (2017) Vibration analysis & condition monitoring for rotating machines: a review material today. Mat Today:Proc 4(2 Part A):2659–2664

  6. Nithin SK, Hemanth K, Shamanth V, Mahale RS, Sharath PC, Patil A (2022) PatilImportance of condition monitoring in mechanical domain. Mater Today Proc 54(Part 2):234–239

  7. Khadersab A, Schivakumar S (2018) analysis techniques for rotating machinery and its effect on bearing faults. 2nd Int Conf Mater Manuf Des Eng Procedia Manuf 20:247–252

    Google Scholar 

  8. Cao, Xiaole, et al.  (2021) Piezoelectric nanogenerators derived self‐powered sensors for multifunctional applications and artificial intelligence. Adv Funct Mater 31(33):2102983

  9. Siddiqui, Khadim Moin, Kuldeep Sahay, V. K. Giri (2014) Health monitoring and fault diagnosis in induction motor-a review. Int J Adv Res Electr Electron Instrum Eng 3(1):6549–6565

  10. Yan R, Gao RX, Chen X (2014) An Wavelets for fault diagnosis of rotary machines: a review with applications. J Sig Process 96:1–15 Elsevier

    Article  Google Scholar 

  11. Khadersab, A., and S. Shivakumar (2018) Parametric vibration analysis of rotating machinery." Materials Today: Proceedings 5(11):25688–25696

  12. Swanson, Erik, Chris D. Powell, Sorin Weissman  (2015) A practical review of rotating machinery critical speeds and modes. Sound Vib 39(5):16–17

  13. Muszynska A (1995) Vibrational diagnostics of rotating machinery malfunctions. Int J Rotating Mach 1(3–4):237–266

    Article  Google Scholar 

  14. Borghesani P, Ricci R, Chatterton S, Pennacchi P (2013) A new procedure for using envelope analysis for rolling element bearing diagnostics invariable operating conditions. Mech Syst Sig Process 38:23–35

    Article  Google Scholar 

  15. Chandra, N. Harish, A. S. Sekhar  (2016) Fault detection in rotor bearing systems using time frequency techniques. Mech Syst Signal Proc 72:105–133

  16. Chen J, Zi Y, He Z, Yuan J (2013) Compound faults detection of rotating machinery using improved adaptive redundant lifting multi wavelet. Mech Syst Sig Process 38(1):36–54 Elsevier

    Article  Google Scholar 

  17. Chen J, Li Z, Pan J, Chen G, Zi Y, Yuan J, Chen B, He Z (2016) Wavelet transform based on inner product in fault diagnosis of rotating machinery: a review. Mech Syst Sig Process 70–71:1–35 Elsevier

    Article  Google Scholar 

  18. Cioch W, Knapik O, Les’kowa J (2013) Finding a frequency signature for a cyclostationary signal with applications to wheel bearing diagnostics. Mech Syst Sig Process 38:55–64 Elsevier

    Article  Google Scholar 

  19. Feng Z, Liang M, Chu F (2013) Recent advances in time–frequency analysis methods for machinery fault diagnosis: review with application examples. Mech Syst Sig Process 38:165–205 Elsevier

    Article  Google Scholar 

  20. Zhang J, Ma W, Lin J, Ma L, Jia X  (2015) Fault diagnosis approach for rotating machinery based on dynamic model and computational intelligence. Meas 59:73–87

  21. Sihler C (2006) A novel torsional exciter for modal vibration testing of large rotating machinery. Mech Syst Sig Process 20:1725–1740 Elsevier

    Article  Google Scholar 

Download references

Acknowledgements

This research is a field case study project carried out by agreement between the Faculty of Technology of the University of Sidi Bel-Abbes and the Lafarge industrial cement plant under the auspices of the Academic Development Program of the Ministry of Research and Higher Education (MESRS).

Funding

The work is financed by the Algerian Ministry of Higher Education and Scientific Research.

Author information

Authors and Affiliations

  1. Laboratory Mechanics of Structure and Solids, Mechanical Engineering Department, Faculty of Technology, University of Sidi Bel Abbes, Sidi Bel Abbes, Algeria

    Sail Hadj Laaradj & Lousdad Abdelkader

  2. Mechanics Research Centre (CRM), Po, Box 73B, 25021, Constantine, Algeria

    Bouamama Mohamed & Nouioua Mourad

Authors
  1. Sail Hadj Laaradj
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lousdad Abdelkader
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bouamama Mohamed
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nouioua Mourad
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nouioua Mourad.

Ethics declarations

Ethics approval

I certify that the paper follows the ethical rules of good scientific practice mentioned in the “Ethical Responsibilities of Authors” of the journal.

Consent to participate

Not applicable.

Consent for publication

Nouioua Mourad hereby declares that I participated in the study and in the development of the manuscript and authorize the full the publishing of manuscript data.

Competing interests

The authors declare no competing interests.

Additional declarations for articles in life science journals that report the results of studies involving humans and/or animals

Not applicable.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Laaradj, S.H., Abdelkader, L., Mohamed, B. et al. Vibration-based fault diagnosis of dynamic rotating systems for real-time maintenance monitoring. Int J Adv Manuf Technol 126, 3283–3296 (2023). https://doi.org/10.1007/s00170-023-11320-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-023-11320-5

Keywords

Search

Navigation