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Maintainability Test Method of Army Armored Equipment based on Small Sample Size

Volume 15, Number 1, January 2019, pp. 200-208
DOI: 10.23940/ijpe.19.01.p20.200208

Chuang Lia, Da Xua, Qinglong Jiaoa, Jieyin Huangb, and Han Linc

aDepartment of Weapon and Control, Army Academy of Armored Force, Beijing, 100072, China
bInstitute of Reliability Engineering, Military Representative Office in Four Four Seven Factory, Baotou, 014000, China
cFujian Police Academy, Fuzhou, 350000, China

(Submitted on October 10, 2018; Revised on November 17, 2018; Accepted on December 15, 2018)


In view of the large manpower and financial resources required for the maintenance test of the armored equipment of the army, as well as the long acquisition period of the maintenance test data, this paper focuses on the maintenance test method based on small sample size and establishes the maintenance test verification based on the Bayes small sample theory. Assessing the model and proposing an equipment maintenance test based on this method effectively reduces the number of samples needed to validate the indicators. At the same time, it is validated with the aid of model equipment maintainability tests. The accuracy is high, and maintenance and verification are reduced. The proposed method is of great reference value for reducing the cost of equipment testing and shortening the equipment development cycle in the development of army equipment.


References: 20

      1. J. K. Zhang, Q. Liu, and J. Feng, “Bayesian Methods in Test Analysis,” National University of Defense Technology Press, Changsha, 2007
      2. X. S. Zhang, K. L. Huang, P. C. Yan, G. Y. Lian, and S. G. Wang, “Evaluation of Complex Equipment Testability based on Mixed Prior Distribution,” Journal of Vibration, Measurement & Diagnosis, Vol. 35, No. 4, pp. 697-701, 2015
      3. GB/T 9414.1-2012, “Maintainability-Part 1: Application Guide,” China Quality Inspection Publishing House, Beijing, 2014
      4. Z. J. Chen, Q. C. Wang, and Y. X. Chen, “Determination Method of Acceleration Factor based on Life Distribution and Bayes,” Systems Engineering and Electronics, Vol. 37, No. 5, pp. 1224-1228, 2015
      5. B. C. Dong, B. W. Song, Q. W. Liang, and Z. Y. Mao, “Research on the Maintenance Test and Evaluation Method for Small Samples of Weapons and Equipment,” Acta Armamentarii, Vol. 32, No. 3, pp. 327-330, 2011
      6. M. Han, “E-Bayesian Estimation Method of Parameter and its Ap-Plications in Reliability Engineering,” Acta Armamentarii, Vol. 33, No. 11, pp. 1473-1476, 2009
      7. G. Luo, X. H. Mu, Y. T. Niu, F. P. Du, J. H. Chen, and Y. N. Wang, “Optimal Design Method for Accelerometer Step-Down-Stress Accelerated Life Testing on Condition of Small Sample,” Journal of Chinese Inertial Technology, Vol. 23, No. 5, pp. 696-700, 2015
      8. H. B. Yang, H. Cai, and S. F. Zhang, “Evaluation of Missile Guidance Precision based on Hybrid Prior Distribution,” Acta Aeronautica Et Astronautica Sinica, Vol. 30, No. 5, pp. 855- 860, 2009
      9. H. B. Yang, S. F. Zhang, and H. Cai, “Bayesian Modified Power Prior Approach for Product Reliability Assessment with Only Safe-or Failure Pattern,” Journal of Solid Rocket Technology, Vol. 32, No. 2, pp. 131-134, 2009
      10. J. J. Yang and T. Hu, “Research on System Reliability Competition Model based on Small Sample Multiple Failure Modes,” Fire Control & Command Control, Vol. 41, No. 8, pp. 88-92, 2016
      11. H. Liu and B. Guo, “Bayes Assessment for Reliability of Success or Failure Product in the Development Phases,” Electronic Product Reliability and Environmental Testing, Vol. 24, No. 5, pp. 25- 29, 2006
      12. J. Y. Miao, P. C. Yan, G. Y. Lian, R. Chen, and W. H. Qiu, “Research Status on Weapon Equipment Maintainability Verification Test Method,” Computer Measurement & Control, Vol. 24, No. 3, pp. 122-126, 2016
      13. A. W. Shen, J. L. Guo, Z. J. Wang, and Q. L. Zhang, “Sensitivity Analysis of Objective Bayesian Evaluation under Random Right Censoring and Weilbull Distribution,” Systems Engineering and Electronics, Vol. 39, No. 8, pp. 1891-1897, 2017
      14. Y. Y. Tan, C. H. Zhang, X. Chen, et al., “Bayes-Ian Analysis based on Dirichlet Prior Distribution of Dominant Failure Modes for Electromechanical Products,” Acta Armamentarii, Vol. 33, No. 2, pp. 209- 213, 2012
      15. X. Jiang, H. Z. Liu, J. J. Zi, D. N. Yuan, and L. L. Liu, “Extremely Small Sample’S Reliability of a Motorized Spindle based on Bayes Method,” Journal of Vibration and Shock, Vol. 34, No. 4, pp. 121-127, 2015
      16. W. J. Zhang, H. B. Yang, and S. F. Zhang, “Reliability Assessment for Device with Only Safe-or-Failure Pattern based on Bayesian Hybrid Prior Approach,” Acta Armamentarii, Vol. 37, No. 3, pp. 506-511, 2016
      17. Y. W. Yin, C. X. Shang, J. Y. Cai, Y. H. Ma, and G. Li, “Bayesian Verification Method based on Equipment Testability Growth,” Journal of Vibration, Measurement & Diagnosis, Vol. 36, No. 3, pp. 488-491, 2016
      18. W. L. Li, D. L. Yuan, H. Z. Liu, and T. Zhang, “Reliability Research on the Mechanism System Wear Simulation under the Case of the Small-Scale Sample,” Journal of Mechanical Engineering, Vol. 51, No. 13, pp. 235-244, 2015
      19. R. Q. Wang, F. Liu, D. Y. Hu, and D. Li, “Uncertainty Quantification in Low Cycle Fatigue Life Model based on Bayesian Theory,” Acta Aeronautica et Astronautica Sinica, Vol. 38, No. 9, pp. 220832-1-220832-10, 2017
      20. Y. L. Wang, Z. K. Li, B. Zhou, and M. J. Gu, “Extreme-Small-Sample Accelerated Test Method based on Segmented Section Step-Stress Experimental Principle in Life Cycle,” Journal of Huazhong University of Science and Technology (Natural Science Edition), Vol. 45, No. 6, pp. 68-72, 2017


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