Robustness of thermal error compensation model of CNC machine tool

Lang, Xianli; Miao, Enming; Gong, Ya-Yun; Niu, Pengcheng; Xu, Zhishang

doi:10.1117/12.2014436

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“…The development of modern industrial manufacturing technology of machine tools needs increasingly high requirements of accuracy and reliability. Numerous studies show that: in precision machining, machine tool components heat up and this heating is caused by thermal distortion which comes up by error in data of about 40% -70% [1][2][3] .…”

Section: Introductionmentioning

confidence: 99%

Application of Optimized GM (1,1) in the Machine Tool Thermal Error Modeling

2012

AMR

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Considering the prediction of thermal machine tool error data this paper proposes using GM (1,1) model of gray system to predict machine tool thermal error data. Through comparing with the calculated result between traditional GM(1,1) model and the optimized GM(1,1) model, more satisfactory results can be achieved, and indicating that this model can predict the distribution of machine tool thermal error data more accurately. So the optimized GM (1,1) model can be used to provide a more reliable methodology in controlling the digital machine tool.

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Section: Introductionmentioning

confidence: 99%

Application of Optimized GM (1,1) in the Machine Tool Thermal Error Modeling

2012

AMR

View full text Add to dashboard Cite

show abstract

Robustness of thermal error compensation model of CNC machine tool

Cited by 1 publication

References 0 publications

Application of Optimized GM (1,1) in the Machine Tool Thermal Error Modeling

Application of Optimized GM (1,1) in the Machine Tool Thermal Error Modeling

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