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contributor authorLiu, Kuo
contributor authorLiu, Haibo
contributor authorLi, Te
contributor authorWang, Yongqing
contributor authorSun, Mingjia
contributor authorWu, Yuliang
date accessioned2019-02-28T11:02:33Z
date available2019-02-28T11:02:33Z
date copyright12/18/2017 12:00:00 AM
date issued2018
identifier issn1087-1357
identifier othermanu_140_02_021004.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4252020
description abstractThe conception of the comprehensive thermal error of servo axes is given. Thermal characteristics of a preloaded ball screw on a gantry milling machine is investigated, and the error and temperature data are obtained. The comprehensive thermal error is divided into two parts: thermal expansion error ((TEE) in the stroke range) and thermal drift error ((TDE) of origin). The thermal mechanism and thermal error variation of preloaded ball screw are expounded. Based on the generation, conduction, and convection theory of heat, the thermal field models of screw caused by friction of screw-nut pairs and bearing blocks are derived. The prediction for TEE is presented based on thermal fields of multiheat sources. Besides, the factors influencing TDE are analyzed, and the model of TDE is established based on the least square method. The predicted thermal field of the screw is analyzed. The simulation and experimental results indicate that high accuracy stability can be obtained using the proposed model. Moreover, high accuracy stability can still be achieved even if the moving state of servo axis changes randomly, the screw is preloaded, and the thermal deformation process is complex. Strong robustness of the model is verified.
publisherThe American Society of Mechanical Engineers (ASME)
titlePrediction of Comprehensive Thermal Error of a Preloaded Ball Screw on a Gantry Milling Machine
typeJournal Paper
journal volume140
journal issue2
journal titleJournal of Manufacturing Science and Engineering
identifier doi10.1115/1.4037236
journal fristpage21004
journal lastpage021004-9
treeJournal of Manufacturing Science and Engineering:;2018:;volume( 140 ):;issue: 002
contenttypeFulltext


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