Applicability of artificial neural network for modeling and prediction of the laser polished surface quality

被引：0
|
作者：
Wu, Honghe [1 ]
Bordatchev, Evgueni, V [1 ]
机构：
[1] Natl Res Council Canada, 800 Collip Circle, London, ON N6G 4X8, Canada
来源：
2021 CONFERENCE ON LASERS AND ELECTRO-OPTICS (CLEO) | 2021年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Surface quality improvement by a laser polishing (LP) process is a new innovative technology enabling value- adding functionalities, such as improving visual appearance, wettability, friction, and others through the control and reconfiguration of the surface topography. However, the resultant surface is dependent upon many process parameters which makes selecting optimal process parameters to achieve desired surface topography difficult and unrepeatable. It was proposed and demonstrated that artificial neural network (ANN) can reliably model the LP of H13 tool steel and predict the laser polished surface topography parameters, such as areal waviness and roughness, with a probability of 80%. (C) 2020 Her Majesty the Queen in Right of Canada, as represented by the National Research Council of Canada; equal contribution of co-authors (C) 2021 The Author(s)
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页数：2
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