Applications of experimental design in study of explosive network's reliability
-
摘要: 为了设计和评价爆炸网络的可靠性,研究了影响爆炸网络可靠性的主要因素与可靠性特征量之间的定量关系。通过正交试验和均匀试验方法,首先对23个可能的影响因素建立正交试验分析,筛选出7个影响爆速的主要因素;然后基于主要影响因素构造有效的均匀试验,对试验结果进行回归分析,得到主要因素的取值与爆速间的定量模型。Abstract: Explosive networks are the key components to the initiations of aimed warheads and shaped charge warheads, which become the important way for the logicalization of ammunition detonating system. For designing and evaluating the reliability of an explosive network, it is important to find out the quantitative relationship between the reliability characteristic quantities and the major factors affecting the reliability. The quantitative models between the detonation velocity and its main factors were determined by the orthogonal and uniform experiments. First, the orthogonal experiment was carried out to select seven major factors from the twenty-three possible factors, and then these major factors were applied to create an effective uniform experiment to do regression analysis on the experimental results, finally the quantitative models between the detonation velocity and the main factors were figured out.
-
Key words:
- mechanics of explosion /
- reliability /
- orthogonal design /
- explosive logic network /
- uniform design /
- Lasso /
- Elastic Net
-
表 1 筛选试验方案表头设计
Table 1. The table head design for filtering experimental plan
列号 因素 1 C 2 F 3 CF 4 A 5 AC 6 AF 8 B 9 BC 10 BF 12 AB 13 GH 14 EH 17 E 18 G 19 CG 21 AE 22 AG 23 BH 25 BE 26 BG 27 AH 31 CH 31 H 表 2 筛选试验数据
Table 2. Filtering experimental data
试验 Y 1 7.857 6 2 7.301 7 3 7.254 0 4 7.627 9 5 7.719 1 6 7.619 5 7 7.409 7 8 5.904 6 9 7.779 8 10 7.992 1 11 7.892 5 12 7.847 6 13 7.679 5 14 7.763 5 15 未爆炸 16 未爆炸 17 7.833 5 18 7.841 8 19 7.237 9 20 7.734 6 21 7.683 4 22 7.688 3 23 7.529 4 24 7.572 6 25 7.892 2 26 7.903 5 27 7.980 3 28 8.393 2 29 7.779 8 30 7.839 6 31 未爆炸 32 未爆炸 表 3 极差分析结果
Table 3. The range analytical result
因素 R C 0.203 813 F 1.567 000 CF 0.099 613 A 2.136 325 AC 0.045 837 AF 1.941 025 B 2.111 913 BC 0.110 150 BF 1.702 638 AB 2.057 638 GH 0.087 125 EH 1.893 413 E 0.160 775 G 0.123 063 CG 0.131 700 AE 0.042 800 AG 0.089 487 BH 0.077 925 BE 0.105 338 BG 0.003 150 AH 0.019 963 CH 0.156 075 H 0.157 488 表 4 筛选试验方差分析表
Table 4. The variance analysis table of filtering experiment
因素 Ss f Sms F P C 0.33 1 0.33 2.918 0.126 F 19.64 1 19.64 172.506 1.07×10-6 A 36.51 1 36.51 320.628 9.70×10-8 B 35.68 1 35.68 313.342 1.06×10-7 E 0.21 1 0.21 1.816 0.215 G 0.12 1 0.12 1.064 0.332 H 0.20 1 0.20 1.742 0.223 CF 0.08 1 0.08 0.697 0.428 CA 0.02 1 0.02 0.148 0.711 FA 30.14 1 30.14 264.685 2.05×10-7 CB 0.10 1 0.10 0.852 0.383 FB 23.19 1 23.19 203.662 5.67×10-7 AB 33.87 1 33.87 297.443 1.30×10-7 GH 0.06 1 0.06 0.533 0.486 EH 28.68 1 28.68 251.859 2.49×10-7 CG 0.14 1 0.14 1.219 0.302 AE 0.01 1 0.01 0.129 0.729 AG 0.06 1 0.06 0.563 0.475 BH 0.05 1 0.05 0.427 0.532 BG 0 1 0 0.001 0.98 AH 0 1 0 0.028 0.871 CH 0.19 1 0.19 1.711 0.227 BE 0.09 1 0.09 0.780 0.403 δ 0.91 8 0.113 75 ∑ 210.28 31 -
[1] Wu C F J, Hamada M.试验设计与分析及参数优化[M].张润楚, 郑海燕, 兰燕, 译.北京: 中国统计出版社, 2003: 32-80. [2] 茆诗松, 周纪芗, 陈颖.试验设计[M].北京: 中国统计出版社, 2004: 67-129. [3] 何晓群, 刘文卿.应用回归分析[M].北京: 中国人大出版社, 2007: 23-180. [4] 方开泰, 刘民千, 周永道.试验设计与建模[M].北京: 高等教育出版社, 2011. [5] 吴喜之.复杂数据统计方法[M].北京: 中国人大出版社, 2012: 2-50.