2023
DOI: 10.1177/09544054221150662
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Core temperature measurement using ultrasound for high precision manufacturing processes

Abstract: During machining processes, the temperature of the workpiece may vary due to different factors. One of such factors is the heat generated due to tool/workpiece friction. Temperature may also vary due to environmental conditions. These temperature variations can affect the dimensional accuracy of the manufactured workpiece. It is known that the expansion of a part is related to a change in its average temperature, which is influenced more by the internal, core temperature than the surface temperature. The surfa… Show more

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Cited by 2 publications
(2 citation statements)
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“…To ensure the generalization and accuracy of the model, it was necessary to collect machine tool temperature data and thermal error data under different working conditions [ 35 ]. During the experiment, the machine tool data at three speeds were collected, that is, three sets of thermal error experiments were carried out in total.…”
Section: Experimental Processmentioning
confidence: 99%
“…To ensure the generalization and accuracy of the model, it was necessary to collect machine tool temperature data and thermal error data under different working conditions [ 35 ]. During the experiment, the machine tool data at three speeds were collected, that is, three sets of thermal error experiments were carried out in total.…”
Section: Experimental Processmentioning
confidence: 99%
“…The traditional thermal error modeling method often uses the critical temperature at the current time as the input to predict the thermal error. However, the thermal error not only depends on the temperature characteristics of the current time but also has an inseparable relationship with the temperature characteristics of the past continuous time (Olabode et al, 2023;Hans and Ghosh, 2020). This leads to the low prediction accuracy and robustness of the thermal error model established by the traditional method due to the inability to consider the time series characteristics.…”
Section: Introductionmentioning
confidence: 99%