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Research on Thermal Errors Compensation Techniques of Screw in On-line Inspection Software

Author: YueHongXin
Tutor: ZhangQing
School: Tianjin University
Course: Mechanical and Electronic Engineering
Keywords: Many-body theory Error compensation Neural Networks Parameter Identification
CLC: TH161
Type: Master's thesis
Year: 2005
Downloads: 249
Quote: 7
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Abstract


The positioning accuracy of CNC machine tools is an important indicator to reflect the performance of the machine , which is an important factor to affect the accuracy of the workpiece . The relative movement of the heat generated by the screw and nut elongation seriously affect the positioning accuracy, due to the varied machining conditions when its thermal deformation of the position of the screw is not very consistent . In this paper, the the screw heat distortion characteristics RBF neural network method to establish the screw thermal error model , the thermal deformation of the screw identification error parameter , using the theory of multi-body system build with screw thermal errors calculated compensation function generic model . The online detection and compensation software development using Visual Basic 6.0 and Access database on a Windows 2000 platform . The main work of this paper is summarized as the following aspects : a systematic exposition of the feed rate , preload , processing conditions , and bearing a fixed form of the thermal deformation of the screw . Second, based on the theory of multi-body system (MBS) , the establishment of containing the probe error , machine tool geometric error , the screw spindle thermal error error compensation model . To introduce structure and algorithm of neural network theory and RBF network , RBF neural network method screw thermal error identification model . Fourth, the development of the online testing software meter and screw hot deformation processing center ; the software total of six functional modules , focusing on the development of the screw thermal error compensation module . XHFA2420 large profiling beam gantry machining center and MAKNIO vertical machining center , model and software experimental verification . The experiments show that the identification model established by RBF learning fast , high approximation accuracy , especially suited to deal with the changes of complex systems . Detected by the standard test pieces and compensation experiment : the error compensation accuracy is greatly improved overall accuracy improved by an average of 74.6% , and to verify the feasibility and effectiveness of the error compensation method proposed in this paper .

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CLC: > Industrial Technology > Machinery and Instrument Industry > Machinery Manufacturing Technology > Theory of machining accuracy
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