基于多毁伤等级标准的导弹毁伤效能贝叶斯鉴定试验设计

陈童; 刘昊邦; 胡涛

doi:10.13700/j.bh.1001-5965.2023.0282

基于多毁伤等级标准的导弹毁伤效能贝叶斯鉴定试验设计

doi: 10.13700/j.bh.1001-5965.2023.0282

海军工程大学管理工程与装备经济系，武汉 430033

基金项目: 国家自然科学基金(71501183)

详细信息

通讯作者:
E-mail：D23181102@nue.edu.cn

中图分类号: E917
计量
- 文章访问数: 212
- HTML全文浏览量: 67
- PDF下载量: 4
- 被引次数: 0
出版历程
- 收稿日期: 2023-05-25
- 录用日期: 2023-08-11
- 网络出版日期: 2023-09-11
- 整期出版日期: 2025-05-31

Bayesian identification test design of missile damage effectiveness based on multiple damage grades standards

Department of Management Engineering and Equipment Economics，Naval University of Engineering，Wuhan 430033，China

Funds: National Natural Science Foundation of China (71501183）

More Information

Corresponding author: E-mail：D23181102@nue.edu.cn

摘要

摘要:
导弹毁伤效能合格是充分发挥战斗力的重要保障，为检验导弹毁伤效能是否达标，开展毁伤效能鉴定试验研究尤为必要。针对现有“单发毁伤概率”毁伤效能定量表征指标依据单一毁伤标准难以全面描述导弹毁伤效能的局限性，考虑单枚导弹打击目标形成的不同毁伤等级结果，以不同毁伤等级结果发生概率表征毁伤效能，从多毁伤等级标准角度进行导弹鉴定，有利于全面检验导弹毁伤效能。并且为克服小样本导弹整装试验信息不足难题，在鉴定试验设计中利用贝叶斯方法结合体系贡献度融合多源先验信息，提出信息利用充分、双方风险可控的试验方法。研究结果表明：相比单一毁伤标准定量表征指标，所提方法能够全面描述导弹毁伤效能，并与改进后的二项分布假设检验法进行对比，验证了所提方法的优越性。
- 导弹毁伤效能 /
- 鉴定试验 /
- 多毁伤等级标准 /
- 体系贡献度 /
- 贝叶斯
Abstract:
Qualified missile damage effectiveness is an important guarantee to give full play to combat effectiveness. The damage effectiveness identification test research is especially important to determine whether the missile damage effectiveness is up to par. In view of the limitations of the existing damage effectiveness quantitative characterization index of "single-shot damage probability", it is difficult to fully describe the missile's damage effectiveness based on a single damage standard. The damage effectiveness is represented by the probability of occurrence of different damage grade results, taking into account the results of multiple damage grades created by a single missile striking the target. The missile damage effectiveness is identified from the perspective of multiple damage grade standards, which are helpful for a thorough examination of the missile damage effectiveness. In addition, in order to overcome the problem of insufficient information on small sample missile assembly tests, the Bayesian method is used to fuse multiple sources of prior information with the system contribution in the design of identification tests, and the test schemes with sufficient information utilization and controllable risk of both parties are designed. The example shows that compared with the quantitative characterization index of a single damage standard, this research describes the missile damage effectiveness more comprehensively, and compares it with the improved binomial distribution hypothesis test method, which verifies the superiority of this method.
- missile damage effectiveness /
- identification test /
- multiple damage grades standards /
- system contribution /
- Bayesian

HTML全文

给定 $n=15$ 双方风险随 ${m_i}$ 的变化情况

Given the variation of risk of both parties in $n=15$ with respect to ${m_i}$

下载: 全尺寸图片幻灯片

给定 $m_i^ *$ 双方风险随 $n$ 的变化情况

Given the variation of risk of both parties in $m_i^ *$ with respect to $n$

下载: 全尺寸图片幻灯片

表 1 目标毁伤效果等级划分

Table 1. Classification of target damage effect

目标毁伤等级	毁伤情况
零毁伤	目标轻微受损或无损伤，作战效能损失在5%以内
轻度毁伤	目标性能受到轻度损失，如果不及时进行修理，会影响作战性能，作战效能损失5%～20%
中度毁伤	目标损伤较为严重，需要换件修理，作战效能损失20%～50%
重度毁伤	目标严重受损，需要返厂大修，且修理耗时较长，作战效能损失50%～80%
摧毁歼灭	目标完全摧毁，且无法修复，作战效能损失在80%以上

下载: 导出CSV

表 2 导弹毁伤效能鉴定试验参数

Table 2. Missile damage effectiveness identification test parameters

毁伤等级标准	方法1鉴定试验参数 ${p_i}({p_i}^{'})$	方法2鉴定试验参数 ${p_{\alpha_i}}={p_{\beta_i}}$	专家知识信息先验分布 ${\text{B}}\left( {{a_1},{b_1}} \right)$	仿真试验信息先验分布 ${\text{B}}\left( {{a_2},{b_2}} \right)$
轻度毁伤标准	0.9 (0.8)	0.9	$\left( {4,0.5} \right)$	$\left( {4.5,0.5} \right)$
中度毁伤标准	0.7 (0.6)	0.7	$\left( {3,1.5} \right)$	$\left( {3.5,1} \right)$
重度毁伤标准	0.4 (0.3)	0.4	$\left( {2.5,3.5} \right)$	$\left( {1.5,2.5} \right)$
摧毁歼灭标准	0.2 (0.1)	0.2	$\left( {1.5,4.5} \right)$	$\left( {1,3.5} \right)$

下载: 导出CSV

表 3 先验信息专家隶属度打分

Table 3. Prior information expert membership rating

专家序号	可靠隶属度 $\omega _{{\delta _j}}^d$		不可靠隶属度 $\upsilon _{{\delta _j}}^d$
专家序号	专家知识信息 ${\delta _1}$	仿真试验信息 ${\delta _2}$	专家知识信息 ${\delta _1}$	仿真试验信息 ${\delta _2}$
1	0.5	0.5	0.3	0.4
2	0.6	0.7	0.3	0.2
3	0.8	0.5	0.2	0.4
4	0.4	0.4	0.4	0.3
5	0.6	0.6	0.4	0.4

下载: 导出CSV

给定 $n=15$ 鉴定试验方案

Given $n=15$ identification test scheme

毁伤等级标准	$m_i^ *$ 取值	$m_i^ *$ 最优值
轻度毁伤标准	1	1
中度毁伤标准	4,5	5
重度毁伤标准	7,8,9	9
摧毁歼灭标准	9,10,11,12,13,14	12

下载: 导出CSV

给定 $m_i^ *$ 鉴定试验方案

Given $m_i^ *$ identification test scheme

毁伤等级标准	$m_i^ *$	$n$ 取值	$n$ 最优值
轻度毁伤标准	2	19,20,21,22,23	21
中度毁伤标准	5	19	19
重度毁伤标准	9	15,16,17,18,19	16
摧毁歼灭标准	12	15,16,17,18	16

下载: 导出CSV

参考文献(26)

[1]	徐豫新, 蔡子雷, 吴巍, 等. 弹药毁伤效能评估技术研究现状与发展趋势[J]. 北京理工大学学报, 2021, 41(6): 569-578. XU Y X, CAI Z L, WU W, et al. Current research and development of ammunition damage effect assessment technology[J]. Transactions of Beijing Institute of Technology, 2021, 41(6): 569-578(in Chinese).
[2]	谷鸿平, 王玉, 舒彬, 等. 制导榴弹对典型舰船的毁伤效能研究[J]. 火力与指挥控制, 2020, 45(10): 39-42. GU H P, WANG Y, SHU B, et al. Research on damage efficiency of guided grenade against typical ships[J]. Fire Control & Command Control, 2020, 45(10): 39-42(in Chinese).
[3]	LI H S, HAO Y, ZHANG X Q. Numerical calculation method of target damage effectiveness evaluation under uncertain information of warhead fragments[J]. Mathematics, 2022, 10(10): 1688. doi: 10.3390/math10101688
[4]	FAN J, TANG X, WANG B H, et al. Research on the damage effectiveness of AHEAD against the LSS UAV clusters[J]. Journal of Physics: Conference Series, 2023, 2460(1): 012013. doi: 10.1088/1742-6596/2460/1/012013
[5]	赵晓旭, 韩旭光, 吴浩, 等. 制导杀爆弹毁伤效能评估的应用研究[J]. 北京理工大学学报, 2019, 39(6): 551-557. ZHAO X X, HAN X G, WU H, et al. Applied research on damage effectiveness evaluation of guided explosive bomb[J]. Transactions of Beijing Institute of Technology, 2019, 39(6): 551-557(in Chinese).
[6]	朱莉娜, 李翰山. 基于ANSYS/LS-DYNA的博弈对抗目标毁伤效能评估[J]. 计算机应用与软件, 2021, 38(6): 66-72. doi: 10.3969/j.issn.1000-386x.2021.06.011 ZHU L N, LI H S. Target damage effectiveness evaluation of game confrontation based on ANSYS/LS-DYNA[J]. Computer Applications and Software, 2021, 38(6): 66-72(in Chinese). doi: 10.3969/j.issn.1000-386x.2021.06.011
[7]	高源, 王树山, 梁振刚, 等. 破障火箭弹终点毁伤效能评估研究[J]. 火力与指挥控制, 2020, 45(12): 87-91. GAO Y, WANG S S, LIANG Z G, et al. Evaluation of terminal damage effectiveness of concrete-piercing rocket projectile[J]. Fire Control & Command Control, 2020, 45(12): 87-91(in Chinese).
[8]	侯鹏, 裴扬, 张睿文, 等. 地空导弹破片式打击军机的瞄准点选择方法[J]. 北京航空航天大学学报, 2023, 49(6): 1434-1445. HOU P, PEI Y, ZHANG R W, et al. Selection method of aim point for surface-to-air missile fragment against military aircraft[J]. Journal of Beijing University of Aeronautics and Astronautics, 2023, 49(6): 1434-1445(in Chinese).
[9]	贠来峰, 缪云飞, 王国平, 等. 一种新的弹药产品密集度计量型抽样检验方法[J]. 弹道学报, 2020, 32(2): 50-55. YUN L F, MIAO Y F, WANG G P, et al. A new sampling inspection method of variables for dispersion of ammunition product[J]. Journal of Ballistics, 2020, 32(2): 50-55(in Chinese).
[10]	王玮, 王军波, 黄景德. 一个可靠性二次抽样方案的分析及改进[J]. 兵工学报, 2006, 27(2): 360-362. WANG W, WANG J B, HUANG J D. Analysis and improvement of secondary sampling plan of the reliability[J]. Acta Armamentarii, 2006, 27(2): 360-362(in Chinese).
[11]	LI K, SHI X M, LI J, et al. Bayesian estimation of ammunition demand based on multinomial distribution[J]. Discrete Dynamics in Nature and Society, 2021, 2021(1): 5575335.
[12]	LIU H B, SHI X M. Damage effectiveness calculation of hitting targets with ammunition based on Bayesian multinomial distribution[J]. Symmetry, 2022, 14(5): 892. doi: 10.3390/sym14050892
[13]	谭尧, 赵骞, 王文峰, 等. 考虑专家信息的威布尔型产品定时截尾可靠性验收试验方案设计[J]. 系统工程与电子技术, 2022, 44(4): 1409-1416. TAN Y, ZHAO Q, WANG W F, et al. Type I censored reliability acceptence test plan for Weibull distributed products by considering expert information[J]. Systems Engineering and Electronics, 2022, 44(4): 1409-1416(in Chinese).
[14]	刘海涛, 张志华, 董理. 成败型产品可靠性的Bayes验收方案研究[J]. 兵工学报, 2016, 37(3): 565-569. LIU H T, ZHANG Z H, DONG L. Bayesian acceptance test scheme for reliability of binomial products[J]. Acta Armamentarii, 2016, 37(3): 565-569(in Chinese).
[15]	解亚, 邓安仲, 范振. 基于云模型的机动式基地系统毁伤评估方法研究[J]. 军事运筹与评估, 2022, 36(3): 37-43. XIE Y, DENG A Z, FAN Z. A study on damage assessment method of mobile base system based on cloud model[J]. Military Operations Research and Assessment, 2022, 36(3): 37-43(in Chinese).
[16]	LIU H B, SHI X M, CHEN X J, et al. Bayesian inference of ammunition consumption based on normal-inverse gamma distribution[J]. Discrete Dynamics in Nature and Society, 2022, 2022(1): 6365712. doi: 10.1155/2022/6365712
[17]	ZHAO Q, JIA X, CHENG Z J, et al. Bayesian estimation of residual life for weibull-distributed components of on-orbit satellites based on multi-source information fusion[J]. Applied Sciences, 2019, 9(15): 3017. doi: 10.3390/app9153017
[18]	李康, 史宪铭, 李广宁, 等. 基于正态-逆伽马分布的反巡航导弹命中概率估计方法[J]. 系统工程与电子技术, 2022, 44(8): 2621-2627. LI K, SHI X M, LI G N, et al. Estimation method of hit probability of anti-cruise missile weapon based on normal-inverse Gamma distribution[J]. Systems Engineering and Electronics, 2022, 44(8): 2621-2627(in Chinese).
[19]	BOURGUIGNON M. An alternative conjugate prior distribution for positive parameters[J]. Annals of Data Science, 2019, 6(2): 237-243. doi: 10.1007/s40745-018-0174-z
[20]	WANG H, ZHAO C Y, ZANG F, et al. Spatiotemporal patterns of precipitation based on the Bayesian maximum entropy method in a typical catchment of the Heihe River watershed, northwest China[J]. International Journal of Digital Earth, 2022, 15(1): 911-933. doi: 10.1080/17538947.2022.2083248
[21]	MAIOR C B S, MACÊDO J B, LINS I D, et al. Bayesian prior distribution based on generic data and experts’ opinion: a case study in the O&G industry[J]. Journal of Petroleum Science and Engineering, 2022, 210: 109891. doi: 10.1016/j.petrol.2021.109891
[22]	ZHANG X Y, ZHANG Q, ZHENG J F. Research on optimization method of weapon equipment system contribution rate evaluation index based on meta-evaluation[J]. Scientific Journal of Intelligent Systems Research, 2021, 3(11): 87-99.
[23]	DU M, CHENG Z H, SHI X W. Contribution rate evaluation of army air defence brigade equipment system based on vector model[J]. Journal of Physics: Conference Series, 2020, 1650(3): 032158. doi: 10.1088/1742-6596/1650/3/032158
[24]	赵汝东, 史宪铭, 苏小波, 等. 基于Bayesian体系融合的新型弹药消耗预计方法[J]. 兵器装备工程学报, 2020, 41(2): 75-80. doi: 10.11809/bqzbgcxb2020.02.017 ZHAO R D, SHI X M, SU X B, et al. New ammunition consumption prediction method based on Bayesian system fusion[J]. Journal of Ordnance Equipment Engineering, 2020, 41(2): 75-80(in Chinese). doi: 10.11809/bqzbgcxb2020.02.017
[25]	GU X B, MA Y, WU Q H, et al. The application of intuitionistic fuzzy set-topsis model on the level assessment of the surrounding rocks[J]. Shock and Vibration, 2022(7): 1-12.
[26]	ZHAO R D, SHI X M, WANG Q, et al. Bayesian inference for ammunition demand based on Gompertz distribution[J]. Journal of Systems Engineering and Electronics, 2020, 31(3): 567-577. doi: 10.23919/JSEE.2020.000035