The prediction of surface roughness of PCBN turning GH4169 based on adaptive genetic algorithm

ABSTRACT

Super alloy is widely used in aerospace, ships, petrochemical, etc. Processed surface quality of super alloy plays a key role in the performances in poor working conditions. Surface roughness is significant in evaluating surface quality, so it is important to establish the prediction model of surface roughness. An adaptive genetic algorithm is proposed for the prediction model of GH4169 surface roughness. According to the theoretical analysis, the prediction model established with adaptive genetic algorithm could effectively predict the surface roughness of turning process of GH4169. Moreover, the prediction model could optimize the turning parameters and to improve the surface quality.

KEYWORDS:

• super alloy
• surface roughness
• the prediction model
• adaptive genetic algorithm

Funding

This project is supported by National Natural Science Foundation of China (Grant No. 51475128).