A novel method for optimizing the topography parameters of mechanical mating surfaces focus on performance and cost requirements
Source abstract
Abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Adhesion, Friction, and Surface Interactions · Tribology and Lubrication Engineering · Advanced Measurement and Metrology Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Dalian University of Technology 1 , Dalian 116024, China
Logistics Engineering College, Shanghai Maritime University 2 , Shanghai 201306, China
AECC Shanghai Commercial Aircraft Engine Manufacturing Co., Ltd. 3 , Shanghai 201306, China
Funding
National Natural Science Foundation of China · Ministry of Industry and Information Technology of the People’s Republic of China · Shanghai Sailing Program
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