A novel method for optimizing the topography parameters of mechanical mating surfaces focus on performance and cost requirements
A novel method for optimizing the topography parameters of mechanical mating surfaces focus on performance and cost requirements
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DOI：
10.1063/5.0055024
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发表时间：
2021-06
期刊：
影响因子：
1.6
通讯作者：
Yunlong Wang;Xiaokai Mu;Cong Yue;Wei Sun;Chong Liu;Qingchao Sun
中科院分区：
文献类型：
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作者：
Yunlong Wang;Xiaokai Mu;Cong Yue;Wei Sun;Chong Liu;Qingchao Sun
零件的表面加工精度与装配体配合面之间的接触性能密切相关，过度提高零件的加工精度会造成资源浪费，以保证系统性能。为了在低成本和低制造精度的基础上保证系统的高性能，本研究提出了在设计阶段通过调整表面形貌参数来实现这一目标的方法。首先用不同的参数表征被测零件的表面形貌信息，实现表面形貌的参数化表达;其次，通过数值分析和实验方法获得不同表面形貌的配合面的力学性能;第三，建立了不同表面形貌参数与接触性能的函数关系模型，使用拟合算法;最后，以配合面接触刚度为目标，以表面加工精度为约束条件，对表面形貌参数进行了优化。结果表明，优化后两种试样表面形貌的平均方差σ分别比优化前提高了0.98%和2.71%，表明表面加工难度和成本相对降低。该研究可为提高表面形貌参数的优化设计和整机性能提供有效途径。
The surface machining precision of parts is closely related to the contact performance between the mating surfaces of the assembly, and it will create a waste of resources to ensure the system performance by excessively improving the machining accuracy of parts. In order to ensure the high performance of the system on the basis of low cost and low manufacturing precision, this study proposes a method to achieve the goal by adjusting the surface topography parameters in the design phase. First, the surface topography information of the measured parts was characterized by different parameters to realize the parametric expression of the surface topography; second, the mechanical properties of the mating surface with different surface topographies were obtained by numerical analysis and experimental methods; third, the functional relationship models between different surface topography parameters and the contact performance of the mating surface were obtained by using the fitting algorithm; finally, taking the contact stiffness of the mating surface as the objective and the surface machining accuracy as the constraint condition, the surface topography parameters are optimized. The results show that the average variance σ of the surface topography of the two different specimens after optimization increases by 0.98% and 2.71%, respectively, compared with that before optimization, which indicates the relative reduction in the difficulty and cost of surface processing. This study can provide an effective way to improve the optimization design of surface topography parameters and the performance of the whole machine.