Journal
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
Volume 26, Issue 10, Pages 3037-3046Publisher
KOREAN SOC MECHANICAL ENGINEERS
DOI: 10.1007/s12206-012-0813-9
Keywords
Artificial neural network; Drilling machine; Learning algorithm; Vibration analyses
Categories
Ask authors/readers for more resources
Small tolerances are very important factors for drilling machines. Due to the mechanical friction on their moving parts, it is necessary to predict vibration effects. This investigation is focused on design of robust neural network predictors for analyzing vibration effects on moving parts of drilling machines. The research is divided into two parts; the first part is experimental investigation, the second part is simulation analysis with neural networks. Therefore, a real time drilling machine is used for vibrations under working conditions. The measured real vibration parameters are analyzed with neural network. As a result, simulation approaches show that radial basis neural network has superior performance to adapt real time parameters of drilling machines.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available