Design of asymmetric space optical remote sensor active thermal control system by multi-objective optimization
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摘要:针对大口径、离轴、非对称结构的空间光学遥感器主动热控功率最小分配的难题,提出一种基于多目标遗传算法的功率优化方法。首先根据空间相机结构建立有限元模型。然后,凭借设计者的经验,根据相机结构特点及大致热分布规律,初步划分热控区域,规划设计变量和目标变量。之后,将设计变量和目标变量代入多目标遗传算法求出Pareto最优解集。最后,在最优解集中选出合适的功率分配代入到仿真模型中进行计算,得到优化后的功率分配及温度场。对某离轴三反空间相机进行了功率优化和地面热平衡试验。经TMG仿真计算,优化后整机波动范围在低温工况和高温工况分别降低了4.76%和35.7%,并且总功耗降低了6.85%。经地面热平衡试验表明,整机温度场温差控制在±0.5℃以内,满足±2℃的指标要求。Abstract:As for active thermal control problem of minimum power allocation in space optical remote sensor with large diameter, off-axis, symmetric structure, a power optimization method based on multi objective genetic algorithm is proposed in this paper. First of all, according to the spatial structure of the camera a finite element model is created. The next, heat distribution is divided by the experience of the designer's depending on the camera structural characteristics. Design variables and target variables are selected. Then, we plug the design variables and target variables into the multiple objective genetic algorithm and Pareto sets are obtained. Finally, suitable power allocation is selected from the set of optimal solution and substituted into the simulation model. Then the optimization of power distribution and temperature field are obtained. In this paper an off-axis three mirrors space camera is optimized and tested. After optimization and TMG simulation, the total temperature difference is reduced by 4.76% under low temperature condition and 35.7% under high temperature condition. The result of the heat balance shows that the temperature field of the whole camera is controlled within ±0.5 ℃ or less, which is far less than the target requirements of ±2 ℃.
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Key words:
- remote sensor/
- thermal design/
- multi-objective genetic algorithm
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表 1相机热控分区
Table 1.Thermal control district of cameras
序号 加热区位置 H1 左梁前段 H2 左梁后段 H3 右梁前段 H4 右梁后段 H5 次镜背板 H6 折迭镜背板 H7 支撑板 H8 焦面 H9 遮光罩1 H10 遮光罩2 H11 遮光罩3 H12 遮光罩4 H13 三镜对应背板 H14 主镜对应背板 H15 支撑架1 H16 支撑架2 H17 支撑架3 H18 电控箱 表 2常规方法分区热控功率分配
Table 2.Power distribution of common subarea thermal control
序号 设计功率/W H1 8 H2 8 H3 16 H4 16 H5 4 H6 12 H7 6 H8 0 H9 5 H10 5 H11 5 H12 5 H13 15 H14 16 H15 3 H16 3 H17 3 H18 0 总功率 130 表 3设计变量编号及位置
Table 3.Designed variable number and location
编号 加热区位置 H1 左梁前段 H2 左梁后段 H3 右梁前段 H4 右梁后段 H5 次镜背板 H6 折迭镜背板 H7 支撑板 H9 遮光罩 H10 三镜对应背板 H11 主镜对应背板 H12 支撑架1 H13 支撑架2 H14 支撑架3 表 4目标变量编号及位置
Table 4.Target variable number and location
编号 代表区域 节点号 目标/℃ ZJ 主镜 12058 20 CJ 次镜 10368 20 SJ 三镜 11244 20 ZDJ 折叠镜 11655 20 表 5设计变量的约束
Table 5.Constraints of the designed variables
编号 上边界/mW 下边界/mW H1 1×106 5.6×107 H2 1×106 5.6×107 H3 1×106 5.6×107 H4 1×106 5.6×107 H5 1×106 5.6×107 H6 1×106 5.6×107 H7 1×106 5.6×107 H9 1×106 5.6×107 H10 1×106 5.6×107 H11 1×106 5.6×107 H12 1×106 5.6×107 H13 1×106 5.6×107 H14 1×106 5.6×107 表 6整理后的优化结果
Table 6.Optimization results after finishing
编号 优化结果 H1 7 H2 8.3 H3 16 H4 12.3 H5 3 H6 10.5 H7 6 H9 18.2 H10 15.2 H11 15.8 H12 3 H13 3 H14 2.8 总功率 121.1 表 7优化前后稳态分析结果对比
Table 7.Results contrast of steady-state analysis before and after optimization
名称 优化前/℃ 优化后/℃ 优化率/% 低温工况 高温工况 低温工况 高温工况 低温工况 高温工况 主镜 18.8~19.5 19.0~19.9 18.8~19.4 19.0~19.6 14.3 33.3 次镜 18.8~19.0 20.0~20.1 18.8~19.0 20.0~20.1 0 0 三镜 20.7~20.9 20.4~20.7 20.7~20.8 20.4~20.6 50 33.3 折叠镜 19.7~20.1 20.3~20.4 19.8~20.1 20.3~20.4 25 0 整机 18.8~20.9 19.1~21.9 18.8~20.8 19.1~20.9 4.76 35.7 总功耗 130 W 121.1 W 6.85% -
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