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Reliability Evaluation of Complex Equipment Based on Virtual Samples and Performance Degradation

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Published:19 September 2018Publication History

ABSTRACT

Aiming at the difficulties in reliability evaluation of small samples and multi-performance parameter products, a reliability evaluation method based on virtual samples and performance degradation is proposed. Firstly, the multi-performance parameter distance concept is introduced, and the original parameter is virtual augmented with the performance parameter distance. Secondly, the improved Elman neural network is used to process the sample to obtain the complete degradation trajectory. Finally, this method is combined with the performance prediction method based on performance degradation to process the degradation data of a certain type of space relay and obtain a lifetime of 128 hours. The result shows the method effectively solves the processing problem of the rare sample data in the accelerated degradation test, which has certain reference significance.

References

  1. Zhang, J., Zhang, W., and Mei, B. 2011. Assessment of System Performance Degradation and Reliability. J. Tactical Missile Technology, (Nov. 2011), 55--59.Google ScholarGoogle Scholar
  2. Chao, M. 1999. Degradation analysis and related topics: some thoughts and a reviews. C. Proc. Natl. Sci. Counc. ROC(A). (May. 1999). 555--566.Google ScholarGoogle Scholar
  3. Meeker, W. Q., and Hamada, M. 1999. Statistical tools for the rapid development & evaluation of high-reliability products. J. IEEE Trans. (Feb. 1995), 187--198.Google ScholarGoogle Scholar
  4. Crk, V. 2000. Reliability assessment from degradation data. C. Proc. Annual Reliability and Maintainability Symposium, 155--161.Google ScholarGoogle ScholarCross RefCross Ref
  5. Lu, H., Kolarik, W. J., and Lu, S. S. 2001. Real time performance reliability prediction. J. IEEE Transaction on Reliability. 50, 4. (Apr. 2001), 353--357.Google ScholarGoogle Scholar
  6. Zhao, J., and Liu, F. 2007. Reliability assessment of the metallized film capacitors from degradation data. J. Microelectronics Reliability, 2007, 434--436.Google ScholarGoogle ScholarCross RefCross Ref
  7. Chao, D. H., Ma, J., and Chen, S. Y. 2011. Assessment of storage reliability for FOGs by multivariate degradation data. J. Optics and Precisio n Engineering. 19 (Jan. 2011), 35--40.Google ScholarGoogle Scholar
  8. Lu, S., Lu, H., and Kolarik, W. J. 2001. Kolarik. Multivariate performance reliability prediction in real-time. Reliability Engineering and System Safety, 2001. 39--45.Google ScholarGoogle ScholarCross RefCross Ref
  9. Wang, Y. M., 2009. Reliability analysis of electronic products based on performance degradation data. Shijiazhuang, Ordnance Engineering Academy, 2009.Google ScholarGoogle Scholar
  10. Fan, L. X., Zheng, X. J., and Fang. J. 2014. Assessment of life reliability for weapon barrel by multivariate degradation data. J. Sichuan military Engineering Journal. 35, 2 (Feb. 2014), 52--54+77.Google ScholarGoogle Scholar
  11. Zhong, Q. H., Zhang, Z. H., and Liang, S. J. 2011. Reliability analysis approach based on multivariate degradation data. J. Systems Engineering---Theory&Practice. 31, 3 (Mar. 2011), 544--551.Google ScholarGoogle Scholar
  12. Zhang, G. L., Cai, J. Y., Liang, Y. Y., Lv, M., and Lu, G. A fault prediction approach for multiple performance measures based on distance analysis. J. Electronics Optics & Control, 21, 2 (Feb. 2014), 32--35.Google ScholarGoogle Scholar
  13. Li, W. H., Shen, P. G. and Ma, S. N. Study on multi-parameters storage life prediction method for aerospace relay in accelerated degradation. J. Journal of Electrical Engineering. 12, 1 (Jan. 2017.), 22--27.Google ScholarGoogle Scholar
  14. Xu, Y. L., Chen, X. H., Sun, J. Z., Liu, R. F., and Fan, H. 2013. Reliability assessment for complicated electronic equipment with virtual samples of accelerated degradation tests. J. Journal of Xi'an JiaoTong University. 47, 6. (Jun. 2013), 79--84.Google ScholarGoogle Scholar
  15. Lv, W. M., Xiao, Y., Xu, K. W., and Jiang, S. W. 2017. Prediction for electronic component performance based on modified elman neural network. J. Modern Defence Technology. 45, 1(Jan. 2017), 153--160+180.Google ScholarGoogle Scholar
  16. Doksum, K. A., and Hoyland, A. 1993. Models for variable-stress accelerated life testing experiments based on wiener processes and the inverse gaussian distribution. J. Theory of Probability & Its Applications. 37. 1993. 137--139.Google ScholarGoogle Scholar
  17. Wang, H. W., Xu, T. X., and Wang, B. 2014, Lifetime prediction of missile electrical connector based on wiener model. J. Tactical Missile Technology.2014. 42--45.Google ScholarGoogle Scholar
  18. Su, C. Y., Li, S. L., Niu, T. H., and Jing, Y. Y. 2012. Storage reliability estimation method base on performance degradation data of dormant electronics. J. Tactical Missile Technology. 2012. 50--53.Google ScholarGoogle Scholar

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      cover image ACM Other conferences
      EEET '18: Proceedings of the 2018 International Conference on Electronics and Electrical Engineering Technology
      September 2018
      246 pages
      ISBN:9781450365413
      DOI:10.1145/3277453

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      Publication History

      • Published: 19 September 2018

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