A position independent geometric errors identification and correction method for five-axis serial machines based on screw theory. (August 2015)

• Record Type: Journal Article
• Authors: Yang, Jixiang; Mayer, J.R.R.; Altintas, Yusuf
• Is Part Of: International journal of machine tools & manufacture. Volume 95(2015:Aug.)
• Page Start: 52
• Page End: 66
• Publication Date: 2015-08
• Subjects: Five-axis -- Position independent geometric errors -- Screw theory -- CNC; Machine-tools -- Periodicals; Manufacturing processes -- Periodicals; Machines-outils -- Périodiques; Fabrication -- Périodiques; Electronic journals; 621.902
• DOI: 10.1016/j.ijmachtools.2015.04.011
• Languages: English
• ISSNs: 0890-6955

Abstract

Abstract: Position independent geometric errors (PIGEs), which are caused by imperfect assembly of five-axis machine tools, need to be identified and compensated to improve the accuracy of machined parts. This paper presents the identification and correction of serial five-axis machine tools based on screw theory. The proposed identification model is based on a generalized Jacobian function for a variety of five-axis machine configurations as opposed to the models based on homogeneous transformation matrices (HTMs). The screw theory allows a global description of rigid body motion without constructing the local frames on each drive module as required by the HTMs method. An explicit inverse kinematics model is proposed to compensate the geometric errors directly as opposed to the existing approximate linearized or iterative methods. The proposed identification and correction of PIGEs methods are verified through simulations and experiments with ball-bar tests on a five-axis machine tool. Highlights: A generalized five-axis Jacobian function for PIGEs identification is derived based on the screw theory. A generalized identification model based on the proposed Jacobian function is adopted to process data from ball-bar tests. An explicit inverse kinematics model is proposed to directly compensate the PIGEs. The proposed identification and compensation of PIGEs methods are verified through simulations and experiments with ball-bar tests on a five-axis machine tool.