Matches in SemOpenAlex for { <https://semopenalex.org/work/W3196585668> ?p ?o ?g. }
- W3196585668 endingPage "184" @default.
- W3196585668 startingPage "184" @default.
- W3196585668 abstract "Thermal error is one of the main sources of machining error of machine tools. Being a key component of the machine tool, the spindle will generate a lot of heat in the machining process and thereby result in a thermal error of itself. Real-time measurement of thermal error will interrupt the machining process. Therefore, this paper presents a machine learning model to estimate the thermal error of the spindle from its feature temperature points. The authors adopt random forests and Gaussian process regression to model the thermal error of the spindle and Pearson correlation coefficients to select the feature temperature points. The result shows that random forests collocating with Pearson correlation coefficients is an efficient and accurate method for the thermal error modeling of the spindle. Its accuracy reaches to 90.49% based on only four feature temperature points—two points at the bearings and two points at the inner housing—and the spindle speed. If the accuracy requirement is not very onerous, one can select just the temperature points of the bearings, because the installation of temperature sensors at these positions is acceptable for the spindle or machine tool manufacture, while the other positions may interfere with the cooling pipeline of the spindle." @default.
- W3196585668 created "2021-09-13" @default.
- W3196585668 creator A5053463916 @default.
- W3196585668 creator A5072540494 @default.
- W3196585668 creator A5091679175 @default.
- W3196585668 date "2021-08-30" @default.
- W3196585668 modified "2023-10-10" @default.
- W3196585668 title "The Thermal Error Estimation of the Machine Tool Spindle Based on Machine Learning" @default.
- W3196585668 cites W1502922572 @default.
- W3196585668 cites W1977930671 @default.
- W3196585668 cites W1977998559 @default.
- W3196585668 cites W1979910723 @default.
- W3196585668 cites W1985846166 @default.
- W3196585668 cites W1988729822 @default.
- W3196585668 cites W1990480859 @default.
- W3196585668 cites W1998481880 @default.
- W3196585668 cites W2002425998 @default.
- W3196585668 cites W2007653356 @default.
- W3196585668 cites W2011388760 @default.
- W3196585668 cites W2023933093 @default.
- W3196585668 cites W2036429389 @default.
- W3196585668 cites W2042005770 @default.
- W3196585668 cites W2045982469 @default.
- W3196585668 cites W2048050120 @default.
- W3196585668 cites W2050236706 @default.
- W3196585668 cites W2072544990 @default.
- W3196585668 cites W2078351548 @default.
- W3196585668 cites W2084308970 @default.
- W3196585668 cites W2086179689 @default.
- W3196585668 cites W2087999507 @default.
- W3196585668 cites W2090784252 @default.
- W3196585668 cites W2162514941 @default.
- W3196585668 cites W2167835364 @default.
- W3196585668 cites W2216946510 @default.
- W3196585668 cites W2576629868 @default.
- W3196585668 cites W2617992479 @default.
- W3196585668 cites W2791740441 @default.
- W3196585668 cites W2895892446 @default.
- W3196585668 cites W2911964244 @default.
- W3196585668 cites W2921780980 @default.
- W3196585668 cites W3036202367 @default.
- W3196585668 cites W3121469503 @default.
- W3196585668 cites W3172776540 @default.
- W3196585668 doi "https://doi.org/10.3390/machines9090184" @default.
- W3196585668 hasPublicationYear "2021" @default.
- W3196585668 type Work @default.
- W3196585668 sameAs 3196585668 @default.
- W3196585668 citedByCount "8" @default.
- W3196585668 countsByYear W31965856682021 @default.
- W3196585668 countsByYear W31965856682022 @default.
- W3196585668 countsByYear W31965856682023 @default.
- W3196585668 crossrefType "journal-article" @default.
- W3196585668 hasAuthorship W3196585668A5053463916 @default.
- W3196585668 hasAuthorship W3196585668A5072540494 @default.
- W3196585668 hasAuthorship W3196585668A5091679175 @default.
- W3196585668 hasBestOaLocation W31965856681 @default.
- W3196585668 hasConcept C111919701 @default.
- W3196585668 hasConcept C11413529 @default.
- W3196585668 hasConcept C121332964 @default.
- W3196585668 hasConcept C127413603 @default.
- W3196585668 hasConcept C138885662 @default.
- W3196585668 hasConcept C153294291 @default.
- W3196585668 hasConcept C154945302 @default.
- W3196585668 hasConcept C204530211 @default.
- W3196585668 hasConcept C2776401178 @default.
- W3196585668 hasConcept C41008148 @default.
- W3196585668 hasConcept C41895202 @default.
- W3196585668 hasConcept C43521106 @default.
- W3196585668 hasConcept C523214423 @default.
- W3196585668 hasConcept C5941749 @default.
- W3196585668 hasConcept C78519656 @default.
- W3196585668 hasConcept C98045186 @default.
- W3196585668 hasConceptScore W3196585668C111919701 @default.
- W3196585668 hasConceptScore W3196585668C11413529 @default.
- W3196585668 hasConceptScore W3196585668C121332964 @default.
- W3196585668 hasConceptScore W3196585668C127413603 @default.
- W3196585668 hasConceptScore W3196585668C138885662 @default.
- W3196585668 hasConceptScore W3196585668C153294291 @default.
- W3196585668 hasConceptScore W3196585668C154945302 @default.
- W3196585668 hasConceptScore W3196585668C204530211 @default.
- W3196585668 hasConceptScore W3196585668C2776401178 @default.
- W3196585668 hasConceptScore W3196585668C41008148 @default.
- W3196585668 hasConceptScore W3196585668C41895202 @default.
- W3196585668 hasConceptScore W3196585668C43521106 @default.
- W3196585668 hasConceptScore W3196585668C523214423 @default.
- W3196585668 hasConceptScore W3196585668C5941749 @default.
- W3196585668 hasConceptScore W3196585668C78519656 @default.
- W3196585668 hasConceptScore W3196585668C98045186 @default.
- W3196585668 hasFunder F4320322795 @default.
- W3196585668 hasIssue "9" @default.
- W3196585668 hasLocation W31965856681 @default.
- W3196585668 hasLocation W31965856682 @default.
- W3196585668 hasOpenAccess W3196585668 @default.
- W3196585668 hasPrimaryLocation W31965856681 @default.
- W3196585668 hasRelatedWork W2010575535 @default.
- W3196585668 hasRelatedWork W2063110400 @default.
- W3196585668 hasRelatedWork W2322509432 @default.
- W3196585668 hasRelatedWork W2393634774 @default.