Data Processing of Test of Fuze Arming Distance Measured Using Langlie Method Based on Bayesian Method

doi:10.3969/j.issn.1000-1093.2021.01.003

Abstract

Abstract: For the contradiction between smaller sample size and large evaluation error in measuring the fuze arming distance by Langlie method, Bayesian method is used to process the data of fuze arming distance measured by Langlie method. A Bayesian mathematical model is established, and the prior distribution choice and the posterior distribution form are clarified. The prior data hyperparameters are determined from the experimental data, and the posterior distribution is solved from the prior information. The simulated and experimental results show that the influence of the Langlie method on accuracy of variance can be improved, and the accuracy of variance can be increased by 20%. The error of 95% and 5% points of the fuze arming distance that can be reduced is controlled within 5%. The inconsistent test results that are caused by test conditions are corrected to reduce the influence of condition errors on the mean and variance, and obtain the relationship between modified mean and variance. Bayesian method can modify the variance of Langlie method, and also weaken the influence of the test conditions on the results.

Key words: fuze, Bayesianmethod, Langliemethod, fuzearmingdistance

CLC Number:

TJ430.2

ZHAO Xin, JI Yongxiang, LIU Shefeng, CHEN Zhong, NING Xiaolei. Data Processing of Test of Fuze Arming Distance Measured Using Langlie Method Based on Bayesian Method[J]. Acta Armamentarii, 2021, 42(1): 26-32.

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