Thermal error compensation of a 5-axis machine tool using indigenous temperature sensors and CNC integrated Python code validated with a machined test piece
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F20%3A00341767" target="_blank" >RIV/68407700:21220/20:00341767 - isvavai.cz</a>
Result on the web
<a href="http://hdl.handle.net/10467/89305" target="_blank" >http://hdl.handle.net/10467/89305</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.precisioneng.2020.06.010" target="_blank" >10.1016/j.precisioneng.2020.06.010</a>
Alternative languages
Result language
angličtina
Original language name
Thermal error compensation of a 5-axis machine tool using indigenous temperature sensors and CNC integrated Python code validated with a machined test piece
Original language description
Achieving high workpiece accuracy is the long-term goal of machine tool designers. There are many causes for workpiece inaccuracy, with thermal errors being the most common. Indirect compensation (using prediction models for thermal errors) is a promising strategy to reduce thermal errors without increasing machine tool costs. The modelling approach uses transfer functions to deal with this issue; it is an established dynamic method with a physical basis, and its modelling and calculation speed are suitable for real-time applications. This research presents compensation for the main internal and external heat sources affecting the 5-axis machine tool structure including spindle rotation, three linear axes movements, rotary C axis and time-varying environmental temperature influence, save for the cutting process. A mathematical model using transfer functions is implemented directly into the control system of a milling centre to compensate for thermal errors in real time using Python programming language. The inputs of the compensation algorithm are indigenous temperature sensors used primarily for diagnostic purposes in the machine. Therefore, no additional temperature sensors are necessary. This achieved a significant reduction in thermal errors in three machine directions X, Y and Z during verification testing lasting over 60 hours. Moreover, a thermal test piece was machined to verify the industrial applicability of the introduced approach. The results of the transfer function model compared with the machine tool’s multiple linear regression compensation model are discussed.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20302 - Applied mechanics
Result continuities
Project
<a href="/en/project/EF16_026%2F0008404" target="_blank" >EF16_026/0008404: Machine Tools and Precision Engineering</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Precision Engineering
ISSN
0141-6359
e-ISSN
1873-2372
Volume of the periodical
66
Issue of the periodical within the volume
November
Country of publishing house
US - UNITED STATES
Number of pages
10
Pages from-to
21-30
UT code for WoS article
000583295900003
EID of the result in the Scopus database
2-s2.0-85087938331