航空推进系统气动安全阀结构参数分析及优化

doi:10.16265/j.cnki.issn1003-3033.2023.02.0983

摘要/Abstract

摘要：

为改善某型航空推进系统气动安全阀的性能,建立航空推进系统双级气体减压器和安全阀组成的高压气路AMESim数值模型,搭建安全阀性能测试试验台,验证模型准确性,分析结构参数对安全阀特性的影响机制。采用响应曲面法(RSM),建立结构参数与安全阀压力超调量和响应时间的显著不失拟回归模型,通过方差分析 (ANOVA)研究结构参数交互作用对安全阀压力超调量和响应时间影响的显著性差异,并基于自适应范围多目标遗传算法 (ARMOGA),优化入口长度、入口直径和弹簧刚度参数。研究结果表明:入口长度、入口直径、弹簧刚度对超调量和响应时间的影响依次降低,入口长度与直径的交互作用最为显著;入口长度、入口直径、弹簧刚度分别为 14.587 8 mm、 14.898 0 mm、48.966 8 N/mm时安全阀性能最佳,优化后超调量降低6.917%,响应时间降低6.383%。

关键词: 航空推进系统, 气动安全阀, 结构参数, 超调量和响应时间, 多目标优化

Abstract:

In order to improve the working performance of the pneumatic safety valve for aviation propulsion system, the AMESim numerical model of the high-pressure gas line of a double-stage gas pressure reducer and a safety valve was established. A safety valve test performance experimental bench was built to verify the accuracy of the model, and the influence law of structural parameters on the characteristics of the safety valve was studied. A significant regression model of structural parameters and safety valve pressure overshoot and response time was established using response surface methodology (RSM). The significant differences in the effects of structural parameter interactions on safety valve pressure overshoot and response time were investigated using Analysis of Variance (ANOVA). The parameters of inlet length, inlet diameter and spring stiffness were optimized based on an Adaptive Range Multi-objective Genetic Algorithm (ARMOGA). The results of the study show that the influence of inlet length, inlet diameter, and spring stiffness on overshoot and response time decreases in descending order, with the interaction between inlet length and diameter being the most significant. The best performance of the safety valve is achieved when the inlet length, inlet diameter and spring stiffness are 14.587 8 mm, 14.898 0 mm and 48.966 8 N/mm, respectively, and the optimized overshoot is reduced by 6.917% and the response time is reduced by 6.383%.

Key words: aviation propulsion system, pneumatic safety valve, structural parameters, overshoot and response time, multi-objective optimization

王慧, 周国强, 王禹涧, 岳星岐, 张一鸣. 航空推进系统气动安全阀结构参数分析及优化[J]. 中国安全科学学报, 2023, 33(2): 48-58.

WANG Hui, ZHOU Guoqiang, WANG Yujian, YUE Xingqi, ZHANG Yiming. Structural parameter analysis and optimization of pneumatic safety valve in aviation propulsion system[J]. China Safety Science Journal, 2023, 33(2): 48-58.

图/表 24

图1

图2

表1

图3

图4

图5

图6

图7

图8

图9

图10

图11

图12

图13

表2

表3

表4

回归模型ANOVA结果

方差来源	平方和		自由度		统计量F值		显著性概率P值
方差来源	Y₁	Y₂	Y₁	Y₂	Y₁	Y₂	Y₁	Y₂
模型	0.065	4.210 × 10^-4	9	9	272.09	356.89	< 0.000 1	< 0.000 1
X₁	0.021	1.505 × 10^-4	1	1	802.53	1 148.31	< 0.000 1	< 0.000 1
X₂	0.033	2.258 × 10^-4	1	1	1 241.46	1 722.58	< 0.000 1	< 0.000 1
X₃	9.005 × 10^-3	5.000 × 10^-9	1	1	339.43	0.038	< 0.000 1	0.850 7
X₁X₂	5.593 × 10^-4	4.032 × 10^-5	1	1	21.08	307.64	0.002 5	< 0.000 1
X₁X₃	9.000 × 10^-6	5.421 × 10^-20	1	1	0.34	4.136 × 10^-13	0.578 5	0.998 7
X₂X₃	2.025 × 10^-5	1.000 × 10^-8	1	1	0.76	0.076	0.411 3	0.790 4
$X 1 2$	7.378 × 10^-4	6.579 × 10^-10	1	1	27.81	5.019 × 10^-3	0.001 2	0.915 5
$X 2 2$	2.927 × 10^-4	4.316 × 10^-6	1	1	11.03	32.93	0.012 7	0.000 7
$X 3 2$	2.985 × 10^-5	5.921 × 10^-9	1	1	1.13	0.045	0.324 0	0.837 7
残差值	1.857× 10^-4	9.175 × 10^-7	7	7	—	—	—	—
失拟度	1.857× 10^-4	9.175 × 10^-7	3	3	—	—	—	—

表4

图14

图15

图16

图17

图18

图19

表5

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标号	参数及单位
E1	质量0.034 kg
E2	质量0.043 kg
E3	质量0.015 kg
F1	面积7.068 mm²
F2	面积60 mm²
H	进口长度16.5 mm;进口直径15.0 mm
S1	面积0.01 mm²
T1	刚度96 N/mm;预紧力1 163 N
T2	刚度58 N/mm
T3	刚度8.767 N/mm;预紧力38 N
T4	刚度240 N/mm;弹力12 N
T5	刚度29.66 N/mm;预紧力241.84 N
V1	容积1.295 mL
V2	容积19 mL
V7	容积0.17 mL
V8	容积20 mL

标准方案	试验方案	X₁	X₂	X₃	δ	响应时间/s
7	1	6.50	15.00	49.66	0.320 3	0.010 2
17	2	16.50	15.00	29.66	0.284 8	0.014 1
标准方案	试验方案	X₁	X₂	X₃	δ	响应时间/s
5	3	6.50	15.00	9.66	0.390 7	0.010 1
3	4	6.50	21.00	29.66	0.306 0	0.012 6
4	5	26.50	21.00	29.66	0.185 6	0.028 3
13	6	16.50	15.00	29.66	0.284 8	0.014 1
2	7	26.50	9.00	29.66	0.330 4	0.011 3
16	8	16.50	15.00	29.66	0.284 8	0.014 1
12	9	16.50	21.00	49.66	0.196 9	0.020 4
6	10	26.50	15.00	9.66	0.278 1	0.018 1
9	11	16.50	9.00	9.66	0.399 2	0.009 8
1	12	6.50	9.00	29.66	0.403 5	0.008 3
10	13	16.50	21.00	9.66	0.259 2	0.020 5
8	14	26.50	15.00	49.66	0.213 7	0.018 2
14	15	16.50	15.00	29.66	0.284 8	0.014 1
11	16	16.50	9.00	49.66	0.327 9	0.009 9
15	17	16.50	15.00	29.66	0.284 8	0.014 1

响应	优化前	优化后
Y₁	0.284 8	0.265 1
Y₂	0.014 1	0.013 2