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Tipping Point Analysis of Electrical Resistance Data with Early Warning Signals of Failure for Predictive Maintenance

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Abstract

We apply tipping point analysis to measurements of electronic components commonly used in applications in the automotive or aviation industries and demonstrate early warning signals based on scaling properties of resistance time series. The analysis is based on a statistical physics framework with a stochastic model representing the system time series as a composition of deterministic and stochastic components estimated from measurements. The early warning signals are observed much earlier than those estimated from conventional techniques, such as threshold-based failure detection, or bulk estimates used in Weibull failure analysis. The introduced techniques may be useful for real-time predictive maintenance of power electronics, with industrial applications. We suggest that this approach can be applied to various electric measurements in power systems and energy applications.

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References

  1. Ashwin P., Wieczorek S., Vitolo R., Cox P. (2012) Tipping points in open systems: bifurcation, noise-induced and rate-dependent examples in the climate system. Phil Trans Royal Soc A 370(1962):1166–1184

    Article  Google Scholar 

  2. Chauhan P., Mathew S., Osterman M., Pecht M. (2014) In situ interconnect failure prediction using canaries. IEEE Transactions on Device and Materials Reliability 14(3):826–832

    Article  Google Scholar 

  3. Dakos V et al (2012) Methods for detecting early warnings of critical transitions in time series illustrated using simulated ecological data. PLoS ONE 7(7):e41010. https://doi.org/10.1371/journal.pone.0041010

    Article  Google Scholar 

  4. Ditlevsen P, Johnsen S (2010) Tipping points: early warning and wishful thinking. Geophys Res Lett 37:L19703

    Article  Google Scholar 

  5. Held H, Kleinen T (2004) Detection of climate system bifurcations by degenerate fingerprinting. GRL 31(23):L23207

    Article  Google Scholar 

  6. IPC Specification (2002) “Performance Test Methods and Qualification Requirements for Surface Mount Solder Attachments”. Institute for Interconnecting and Packaging Electronic Circuits

  7. JEDEC standard (2014) “Temperature cycling” JESD22-A104E, Joint Electron Device Engineering Council

  8. Lenton T et al (2008) Tipping elements in the Earth’s climate system. In: Proceedings of the National Academy of Sciences USA, vol 105, no. 6, pp. 1786–1793

  9. Livina V, Lenton T (2007) A modified method for detecting incipient bifurcations in a dynamical system. Geophys Res Lett 34(3):L03712. https://doi.org/10.1029/2006GL028672

    Article  Google Scholar 

  10. Livina V, Barton E, Forbes A (2014) Tipping point analysis of the NPL footbridge. J Civ Struct Health Monit 4:91–98

    Article  Google Scholar 

  11. Livina V, Kwasniok F, Lenton T (2010) Potential analysis reveals changing number of climate states during the last 60 kyr. Clim Past 6:77–82

    Article  Google Scholar 

  12. Livina V, Kwasniok F, Lohmann G, Kantelhardt J, Lenton T (2011) Changing climate states and stability: from Pliocene to present. Climate Dymamics 37(11-12):2437–2453

    Article  Google Scholar 

  13. Livina V, Ditlevsen P, Lenton T (2012) An independent test of methods of detecting system states and bifurcations in time-series data. Physica A 391(3):485–496

    Article  Google Scholar 

  14. Prettyman J, Kuna T, Livina V (2018) A novel scaling indicator of early warning signals helps anticipate tropical cyclones. Europhys Lett 121:10002

    Article  Google Scholar 

  15. Prettyman J, Kuna T, Livina V (2019) Generalised early warning signals in multivariate and gridded data. Chaos 29:073105

    Article  MathSciNet  Google Scholar 

  16. Scheffer M et al (2009) Early warning signals for critical transitions. Nature 461:53–59

    Article  Google Scholar 

  17. Scholz F (1999) Weibull reliability analysis. Boeing Seminal Paper 425-865-3623:7L-22. http://faculty.washington.edu/fscholz/Reports/weibullanalysis2002.pdf

    Google Scholar 

Download references

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Authors and Affiliations

  1. National Physical Laboratory, Teddington, United Kingdom

    Valerie N. Livina, Adam P. Lewis & Martin Wickham

Authors
  1. Valerie N. Livina
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  2. Adam P. Lewis
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  3. Martin Wickham
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Correspondence to Valerie N. Livina.

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Responsible Editor: S. N. Demidenko

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Livina, V.N., Lewis, A.P. & Wickham, M. Tipping Point Analysis of Electrical Resistance Data with Early Warning Signals of Failure for Predictive Maintenance. J Electron Test 36, 569–576 (2020). https://doi.org/10.1007/s10836-020-05899-w

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  • DOI: https://doi.org/10.1007/s10836-020-05899-w

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