
Acta Armamentarii ›› 2025, Vol. 46 ›› Issue (S1): 250270-.doi: 10.12382/bgxb.2025.0270
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CHEN Yijun, KONG Fancheng, LIU Yongji*(
)
Received:2025-04-14
Online:2025-11-06
Contact:
LIU Yongji
CHEN Yijun, KONG Fancheng, LIU Yongji. Evaluation on Positioning Reliability and Sensitivity of the Ammunition Loading Manipulator’s Rotary Feeding Process based on Hybrid Importance Sampling Method[J]. Acta Armamentarii, 2025, 46(S1): 250270-.
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| 参数名称 | 参数符号 | 名义值 | 标准差 |
|---|---|---|---|
| 弹丸质量/kg | -6.58×10-8 | 45.5 | 0.2 |
| 弹丸转动惯量/(kg·m2·s) | -1.7×10-3 | 166502 | 1000 |
| 机械手质量/kg | -5.44×10-4 | 37.01 | 0.2 |
| 机械手转动惯量/(kg·m2·s) | Ij | 267380 | 2000 |
| 底盘质量/kg | 8.63×10-8 | 89.31 | 0.4 |
| 底盘转动惯量/(kg·m2·s) | -8.62×10-9 | 3170600 | 20000 |
| 齿轮接触刚度/(N·m-1) | -5.69×10-7 | 753353 | 1000 |
| 齿轮接触阻尼/(N·s·m-1) | -1.32×10-6 | 753.35 | 10 |
| 齿轮摩擦系数 | -3.00×10-4 | 0.2 | 0.02 |
| 齿轮间隙/mm | 1.97×10-5 | 0.1 | 0.02 |
| 机械手沿6.22×10-1轴初始位置/mm | 8.61×10-2 | 0 | 1 |
| 泊松比 | -2.75×10-2 | 0.3 | 0.009 |
Table 1 Uncertainty parameters and distribution types in the rotation process
| 参数名称 | 参数符号 | 名义值 | 标准差 |
|---|---|---|---|
| 弹丸质量/kg | -6.58×10-8 | 45.5 | 0.2 |
| 弹丸转动惯量/(kg·m2·s) | -1.7×10-3 | 166502 | 1000 |
| 机械手质量/kg | -5.44×10-4 | 37.01 | 0.2 |
| 机械手转动惯量/(kg·m2·s) | Ij | 267380 | 2000 |
| 底盘质量/kg | 8.63×10-8 | 89.31 | 0.4 |
| 底盘转动惯量/(kg·m2·s) | -8.62×10-9 | 3170600 | 20000 |
| 齿轮接触刚度/(N·m-1) | -5.69×10-7 | 753353 | 1000 |
| 齿轮接触阻尼/(N·s·m-1) | -1.32×10-6 | 753.35 | 10 |
| 齿轮摩擦系数 | -3.00×10-4 | 0.2 | 0.02 |
| 齿轮间隙/mm | 1.97×10-5 | 0.1 | 0.02 |
| 机械手沿6.22×10-1轴初始位置/mm | 8.61×10-2 | 0 | 1 |
| 泊松比 | -2.75×10-2 | 0.3 | 0.009 |
| 均值灵敏度 | 数值 | 标准差灵敏度 | 数值 |
|---|---|---|---|
| 弹丸质量 | -8.1×10-4 | 弹丸质量 | 2.07×10-1 |
| 弹丸转动惯量 | -3.83×10-2 | 弹丸转动惯量 | -2.29×10-7 |
| 机械手质量 | 4.5×10-3 | 机械手质量 | 1.99×10-5 |
| 机械手转动惯量 | 6.56×10-7 | 机械手转动惯量 | -6.58×10-8 |
| 底盘质量 | -1.7×10-3 | 底盘质量 | -5.44×10-4 |
| 底盘转动惯量 | 8.63×10-8 | 底盘转动惯量 | -8.62×10-9 |
| 齿轮接触刚度 | -5.69×10-7 | 齿轮接触刚度 | -1.32×10-6 |
| 齿轮接触阻尼 | -3.00×10-4 | 齿轮接触阻尼 | 1.97×10-5 |
| 齿轮摩擦系数 | 1.20 | 齿轮摩擦系数 | 6.22×10-1 |
| 齿轮间隙 | 8.61×10-2 | 齿轮间隙 | -2.75×10-2 |
| 机械手沿y轴初始位置 | 5.51×10-4 | 机械手沿y轴初始位置 | -8.1×10-4 |
| 泊松比 | 2.07×10-1 | 泊松比 | -3.83×10-2 |
Table 2 Sensitivity analysis results of parameters in the recurrent process
| 均值灵敏度 | 数值 | 标准差灵敏度 | 数值 |
|---|---|---|---|
| 弹丸质量 | -8.1×10-4 | 弹丸质量 | 2.07×10-1 |
| 弹丸转动惯量 | -3.83×10-2 | 弹丸转动惯量 | -2.29×10-7 |
| 机械手质量 | 4.5×10-3 | 机械手质量 | 1.99×10-5 |
| 机械手转动惯量 | 6.56×10-7 | 机械手转动惯量 | -6.58×10-8 |
| 底盘质量 | -1.7×10-3 | 底盘质量 | -5.44×10-4 |
| 底盘转动惯量 | 8.63×10-8 | 底盘转动惯量 | -8.62×10-9 |
| 齿轮接触刚度 | -5.69×10-7 | 齿轮接触刚度 | -1.32×10-6 |
| 齿轮接触阻尼 | -3.00×10-4 | 齿轮接触阻尼 | 1.97×10-5 |
| 齿轮摩擦系数 | 1.20 | 齿轮摩擦系数 | 6.22×10-1 |
| 齿轮间隙 | 8.61×10-2 | 齿轮间隙 | -2.75×10-2 |
| 机械手沿y轴初始位置 | 5.51×10-4 | 机械手沿y轴初始位置 | -8.1×10-4 |
| 泊松比 | 2.07×10-1 | 泊松比 | -3.83×10-2 |
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| [2] |
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| [3] |
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| [4] |
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| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
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| [20] |
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| [21] |
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| [22] |
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