秦国华, 郭翊翔, 王华敏, 侯源君, 娄维达. 飞机整体结构件的“加工变形-疲劳寿命”多目标结构优化方法[J]. 工程力学, 2021, 38(8): 222-236. DOI: 10.6052/j.issn.1000-4750.2020.07.0517
引用本文: 秦国华, 郭翊翔, 王华敏, 侯源君, 娄维达. 飞机整体结构件的“加工变形-疲劳寿命”多目标结构优化方法[J]. 工程力学, 2021, 38(8): 222-236. DOI: 10.6052/j.issn.1000-4750.2020.07.0517
QIN Guo-hua, GUO Yi-xiang, WANG Hua-min, HOU Yuan-jun, LOU Wei-da. MULTIPLE OBJECTIVE STRUCTURAL OPTIMIZATION ON “MACHINING DEFORMATION - FATIGUE LIFE” OF AERONAUTICAL MONOLITHIC COMPONENTS[J]. Engineering Mechanics, 2021, 38(8): 222-236. DOI: 10.6052/j.issn.1000-4750.2020.07.0517
Citation: QIN Guo-hua, GUO Yi-xiang, WANG Hua-min, HOU Yuan-jun, LOU Wei-da. MULTIPLE OBJECTIVE STRUCTURAL OPTIMIZATION ON “MACHINING DEFORMATION - FATIGUE LIFE” OF AERONAUTICAL MONOLITHIC COMPONENTS[J]. Engineering Mechanics, 2021, 38(8): 222-236. DOI: 10.6052/j.issn.1000-4750.2020.07.0517

飞机整体结构件的“加工变形-疲劳寿命”多目标结构优化方法

MULTIPLE OBJECTIVE STRUCTURAL OPTIMIZATION ON “MACHINING DEFORMATION - FATIGUE LIFE” OF AERONAUTICAL MONOLITHIC COMPONENTS

  • 摘要: 在毛坯制造过程中,材料力学性能的非均匀性导致铝合金厚板内产生残余应力,以致在后续的高速切削加工过程中,随着材料的大量去除,残余应力的释放使得整体结构件发生变形,严重影响着整体结构件的尺寸稳定性。因此,研究零件结构与零件变形之间的关系对于实现加工过程的高效化和精密化至关重要。首先,将铝厚板内残余应力的释放合理地等效为外载荷的施加,利用材料力学弯曲变形公式建立铝厚板在厚度方向上加工变形的挠度模型。由实际加工测量可知:加工变形的公式解析值、有限元仿真值与实际测量值吻合得很好。为了进一步分析零件结构与疲劳寿命之间的关系,通过名义应力法对零件的最小疲劳寿命与疲劳载荷下零件的最大应力进行等效以简化分析,对部分具有代表性的结构进行静力分析后将其作为样本进行神经网络拟合,得到了以3个腹板位置为输入、零件最大加工变形及最大疲劳应力为输出的神经网络模型。最后利用神经网络模型构建了一个使得最大加工变形和最大疲劳应力都尽可能小的多目标优化问题,使用遗传算法求解该多目标问题后取得的最优解为:3个腹板与零件底部距离分别为8.868 mm、27.992 mm、28.000 mm,此时零件的最大加工变形为0.088 mm,最小的随机疲劳载荷寿命为4.432×107次。

     

    Abstract: In the process of blank manufacturing, the non-uniformity of mechanical properties of materials leads to residual stress in an aluminum alloy thick plate, so that in the subsequent high-speed cutting process, with the removal of a large number of materials, the release of residual stress causes deformation of the whole structure, which seriously affects the dimensional stability of the whole structure. Therefore, it is very important to study the relationship between part deformation and part structure to realize the high efficiency and precision of machining process. Firstly, the release of residual stress in an aluminum plate is reasonably equivalent to the application of external loads, and the deflection equation of machining deformation in the thickness direction of the aluminum plate is established by using the bending deformation formula of material mechanics. According to the actual measurement, the formula analytic value and the finite element simulation value of the machining deformation are in a good agreement with the actual measured value. In order to further analyze the relationship between part structure and its fatigue life, the nominal stress method is used to simplify the analysis by equating the minimum fatigue life of the part with the maximum stress of the part under fatigue loading. After static analysis of some typical structures, the neural network model with three web positions as input, and the maximum stress of the part and the maximum machining deformation as output is obtained. Finally, the neural network model is used to construct a multi-objective optimization problem that minimizes the maximum machining deformation and maximum fatigue stress, and the optimal solution obtained by solving the multi-objective problem with genetic algorithm is that the distance between the bottom of the three webs and the bottom of the part is 8.868 mm, 27.992 mm, 28.000 mm, respectively. At this moment, the maximum machining deformation of the part is 0.088 mm, the minimum random fatigue load life is 4.432×107.

     

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