Open AccessResearch on the peak prediction and intelligent computing of reversal error for the tilt feed system installed on the precision machine tools
Author(s) -
Feng Bao,
Manzhi Yang,
Meng Dang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2083/4/042023
Subject(s) - tilt (camera) , control theory (sociology) , kinematics , torque , trajectory , machining , computer science , mean squared prediction error , simulation , algorithm , mathematics , engineering , physics , mechanical engineering , artificial intelligence , geometry , classical mechanics , control (management) , astronomy , thermodynamics
To effectively predict the peak of reversal error of tilt feed system and reduce reversal error caused by friction and gravity components, a peak prediction method of reversal error for tilt feed system on the precision NC machine tool is proposed. According to the load, tilt angle, motion trajectory, maximum static friction torque and relevant dynamic characteristic information, the peak prediction formula of the reversal error for the tilt feed system is established by mathematical derivation based on the kinematics, dynamics and torque balance during the process of reversal. Thus, the peak of reversal error for the tilt feed system can be obtained. The experimental results show that this method can achieve a good prediction effect, and can predict the peak of reversal error before the machining. It provides a theoretical basis for the reversal error suppression.