On the selection and assessment of input variables for the characteristic diagram based correction of thermo-elastic deformations in machine tools

• Autorzy: Ihlenfeldt S. , Naumann C. , Putz M.

Identyfikatory

DOI

10.5604/01.3001.0012.7630

• Języki publikacji: EN

Abstrakty

EN

It is a well-known problem of milling machines, that waste heat from motors, friction effects on guides and most importantly the milling process itself greatly affect positioning accuracy and thus production quality. An economic and energy-efficient method of correcting this thermo-elastic positioning error is to gather sensor data from the machine tool and the process and to use that information to predict and correct the resulting tool center point displacement using high dimensional characteristic diagrams. On the one hand, the selection of which and how many input variables to use in the characteristic diagrams is critical to their performance. On the other hand, however, there are often a great number of possible variable combinations available and testing them all is practically impossible. This paper will discuss the suitability of many different input variable types and present a new method of input variable selection which will be compared to existing methods and demonstrated on measurements performed on a machine tool.

Słowa kluczowe

EN

thermal effects; algorithm; machine tool; measurement

• Wydawca: Wydawnictwo Wrocławskiej Rady FSNT NOT
• Czasopismo: Journal of Machine Engineering
• Rocznik: 2018
• Tom: Vol. 18, No. 4
• Strony: 25--38
• Opis fizyczny: Bibliogr. 27 poz., rys.

Twórcy

autor

Ihlenfeldt S.

• Fraunhofer Institute for Machine Tools and Forming Technology IWU, Chemnitz, Germany
• Dresden University of Technology, Institute of Machine Tools and Control Engineering, Dresden, Germany

autor

Naumann C.

• Fraunhofer Institute for Machine Tools and Forming Technology IWU, Chemnitz, Germany

autor

Putz M.

• Fraunhofer Institute for Machine Tools and Forming Technology IWU, Chemnitz, Germany

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).