Skip to main content
SpringerLink
Log in

Anomaly detection of tripod shafts using modified Mahalanobis distance

  • Published:
Journal of Mechanical Science and Technology Aims and scope Submit manuscript

Abstract

The tripod shafts used in high-speed trains transmit the power of a motor to axle reduction units. A tripod shaft is designed as a shaft with a protective fuse because the load applied to the reduction units is very large during operation. Fuse failure can lead to accidents and economic loss, such as train service interruption and repair problems at the accident site. Therefore, detecting the faults of fuses used in tripod shafts by using sensors is necessary. In this study, torsion fatigue tests for the failure modes were conducted, and strain data were collected by strain sensors from around the fuse of the shaft. The modified Mahalanobis distance was employed as the health indicator, and the fuse thresholds for the anomaly detection (AD) were defined using the three-sigma method. The AD performance of the tripod shafts was evaluated by comparing the results with real crack detection times.

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

Similar content being viewed by others

References

  1. S.-W. Han et al., Improvement derived through the highspeed train derailment case study, 2015 Autumn Conference of The Korean society for Railway (2015) 309–319.

    Google Scholar 

  2. C. W. Lee, D. H. Lee and H. J. Kim, Design life adequacy study of reduction gear system for KTX train, 2013 Autumn Conference of The Korean society for Railway (2013) 122–123.

    Google Scholar 

  3. RAIB, Passenger train derailment near East Langton, Rail Accident Investigation Branch (2010) 5–91.

  4. D.-H. Lee, S. J. Kwon, B.-S. Park, D.-Y. Cho and J.-W. Kim, Development of condition monitoring system for reduction unit of high-speed rail, J. Korean Soc. Precis. Eng., 30 (7) (2013) 667–672.

    Article  Google Scholar 

  5. D.-W. Jung, Y.-Y. Lee and E.-S. Kim, A study of maintenance measures of the KTX decelerator, 2009 Autumn Conference of The Korean society for Railway (2009) 1191–1197.

    Google Scholar 

  6. S.-S. Kim, Y.-G. Kim, K.-H. Kim and C.-S. Park, Torque measurement of tripod shaft for HSR-350x, J. of the Korean Society for Railway, 10 (5) (2007) 660–664.

    Google Scholar 

  7. J. H. Lee, D. S. Kim, T. Y. Nam, T. Y. Lee and H. Y. Cho, Experimental investigation on torsional analysis and fracture of tripod shaft for high-speed train, Trans. Korean Soc. Mech. Eng. A, 40 (11) (2016) 979–986.

    Article  Google Scholar 

  8. K. H. Moon, D.-H. Lee, J. C. Kim and H. Y. Ji, Analysis on the vibration characteristics of reduction gear units for high-speed trains, J. Korean Soc. Precis. Eng., 30 (7) (2013) 694–701.

    Article  Google Scholar 

  9. S. Lee, I. Jeon and D.-C. Baek, Deviation based fault detection method for shackles under variable loading, J. of Mechanical Science and Technology, 32 (2) (2018) 753–760.

    Article  Google Scholar 

  10. M. G. Pecht, Prognostics and health management of electronics, John Wiley & Sons (2008) 47–67.

    Book  Google Scholar 

  11. M. Pecht and R. Jaai, A prognostics and health management roadmap for information and electronics-rich systems, Microelectronics Reliability, 50 (3) (2010) 317–323.

    Article  Google Scholar 

  12. J. Fan, C. Qian, X. Fan, G. Zhang and M. Pecht, In-situ monitoring and anomaly detection for LED packages using a Mahalanobis distance approach, 2015 First International Conference on Reliability Systems Engineering (ICRSE) (2015) 1–6.

    Google Scholar 

  13. N. Patil, S. Menon, D. Das and M. Pecht, Anomaly detection of non punch through insulated gate bipolar transistors (IGBT) by robust covariance estimation techniques, 2010 2nd International Conference on Reliability, Safety and Hazard (ICRESH-2010) (2010) 68–72.

    Google Scholar 

  14. N. Patil, D. Das and M. Pecht, Anomaly detection for IGBTs using Mahalanobis distance, Microelectronics Reliability, 55 (7) (2015) 1054–1059.

    Article  Google Scholar 

  15. J. Chen, D. Zhou, C. Lyu and C. Lu, A novel health indicator for PEMFC state of health estimation and remaining useful life prediction, International J. of Hydrogen Energy, 42 (31) (2017) 20230–20238.

    Article  Google Scholar 

  16. S. Kumar, T. W. S. Chow and M. Pecht, Approach to fault identification for electronic products using Mahalanobis distance, IEEE Transactions on Instrumentation and Measurement, 59 (8) (2010) 2055–2064.

    Article  Google Scholar 

  17. J. L. Godwin, P. Matthews and C. Watson, Robust multivariate statistical ensembles for bearing fault detection and identification, 2014 International Conference on Prognostics and Health Management (2014) 1–11.

    Google Scholar 

  18. P. Wang, B. D. Youn, C. Hu, J. M. Ha and B. Jeon, A probabilistic detectability-based sensor network design method for system health monitoring and prognostics, J. of Intelligent Material Systems and Structures, 26 (9) (2015) 1079–1090.

    Article  Google Scholar 

  19. Y. Jungwon, J. Jaeyel, Y. Jaeyeong and K. Sungshin, Fault detection method for steam boiler tube using Mahalanobis distance, J. of Korean Institute of Intelligent Systems, 26 (3) (2016) 246–252.

    Article  Google Scholar 

  20. M. Chamay, S.-d. Oh and Y.-J. Kim, Development of a diagnostic system using LPC/cepstrum analysis in machine vibration, J. of Mechanical Science and Technology, 27 (9) (2013) 2629–2636.

    Article  Google Scholar 

  21. G. Box and D. Cox, An analysis of transformations, J. of Royal Statistical Society, 26 (1964) 211–252.

    MathSciNet  MATH  Google Scholar 

  22. D. Zeng, D. E. Schaubel and J. Cai, Semiparametric transformation rate model for recurrent event data, Statistics in Biosciences, 3 (2) (2011) 187–207.

    Article  Google Scholar 

  23. B. Bhardwaj, R. Kumar and P. K. Singh, An improved surface roughness prediction model using Box-Cox transformation with RSM in end milling of EN 353, J. of Mechanical Science and Technology, 28 (12) (2014) 5149–5157.

    Article  Google Scholar 

  24. L. Ignatiades, M. Karydis and P. Vounatsou, A possible method for evaluating oligotrophy and eutrophication based on nutrient concentration scales, Marine Pollution Bulletin, 24 (5) (1992) 238–243.

    Article  Google Scholar 

  25. S. R. Das, D. Dhupal and A. Kumar, Study of surface roughness and flank wear in hard turning of AISI 4140 steel with coated ceramic inserts, J. of Mechanical Science and Technology, 29 (10) (2015) 4329–4340.

    Article  Google Scholar 

  26. T. Xiang, L. Gu and J. Xu, The meshing angular velocity and tangential contact force simulation for logarithmic spiral bevel gear based on Hertz elastic contact theory, J. of Mechanical Science and Technology, 30 (8) (2016) 3441–3452.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Chonnam National University, Gwangju, 61186, Korea

    Sunghyun Lee & Insu Jeon

  2. Department of Reliability Assessment, Korea Institute of Machinery and Materials, Daejeon, 34103, Korea

    Sunghyun Lee, Jong-Won Park, Do-Sik Kim & Dong-Cheon Baek

Authors
  1. Sunghyun Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jong-Won Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Do-Sik Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Insu Jeon
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dong-Cheon Baek
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Insu Jeon or Dong-Cheon Baek.

Additional information

Sunghyun Lee is a Ph.D. candidate of Mechanical Engineering at Chonnam National University, Republic of Korea. He is also studying at the Department of Reliability Assessment at the Korea Institute of Machinery and Materials. His research interests include fault detection and prognostics of mechanical systems.

Jong-Won Park received his B.S. and M.S. degrees in Mechanical Engineering from Hongik University in 1996 and 1998, respectively. He received his Ph.D. from Seoul National University in 2003. He joined the Department of Reliability Assessment at the Korea Institute of Machinery and Materials in 2003, and is now the Head of the department. His research interests include mechanical system analysis and control, reliability assessment via accelerated life test, system reliability analysis, and artificial intelligence.

Do-Sik Kim is a Senior Researcher at the Department of Reliability Assessment at the Korea Institute of Machinery and Materials. He received his Ph.D. in Mechanical Design Engineering from Chungnam National University in 2017. His research interest includes power transmission units in heavy-duty vehicles.

Insu Jeon received his Ph.D. in Mechanical Engineering from the Korea Advanced Institute of Science and Technology in 2000. He joined the School of Mechanical Engineering at Chonnam National University in 2006 as a faculty member. His research interests incude fracture mechanics, biomechanics, and biomaterials.

Dong-Cheon Baek is a Senior Researcher at the Department of Reliability Assessment at the Korea Institute of Machinery and Materials. He received his B.S., M.S., and Ph.D. (2009) in Mechanical Engineering from the Korea Advanced Institute of Science and Technology. His research interests include is the prognostics and health management of the mechanical system.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, S., Park, JW., Kim, DS. et al. Anomaly detection of tripod shafts using modified Mahalanobis distance. J Mech Sci Technol 32, 2473–2478 (2018). https://doi.org/10.1007/s12206-018-0504-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12206-018-0504-2

Keywords

Search

Navigation