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Title
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Surface roughness measurements of turned parts through a vision-based measurement system : uncertainty analysis and performance comparison with state-of-the-art instruments
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Author
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Abstract
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| The focus of this study is to design a vision-based measurement instrument capable of measuring surface roughness and to discuss its metrological performance compared to more traditional measurement instruments. The instrument is a non-contact measurement system characterized by short inspection time which allows for in-line implementation. The aim of the work was to combine the use of the Modulation Transfer Function to estimate the resolution and of an Electrically Tunable Lens to obtain an optimally focused image. A set of turned steel samples with different roughness in the range Ra 2.38 mu m to 15.07 mu m was prepared and the layout of the instrument is presented, including a discussion on how optimal imaging conditions were obtained. The paper describes the comparison performed on the measurements collected with different instruments. In particular, it reports a comparison of roughness measurements performed by the vision-based system designed in this work and state-of-the-art instruments on a set of turned samples. In particular, the reference instrument is a stylus-based measurement system. The data acquired and the results showed that all of the instruments' performances are compatible with each other, including the vision-based instrument developed in this work. |
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Language
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English
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Source (journal)
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Proceedings of 2022 IEEE International Workshop on Metrology for Industry 4.0 & IOT (IEEE METROIND4.0&IOT)
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Source (book)
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IEEE International Workshop on Metrology for Industry 4.0 and IoT, (MetroInd4.0 and IoT), JUN 07-09, 2022, Univ Trento, Univ Trento, Trento, ITALY
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Publication
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New york
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Ieee
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2022
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ISBN
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978-1-6654-1093-9
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DOI
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10.1109/METROIND4.0IOT54413.2022.9831674
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Volume/pages
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(2022)
, p. 17-22
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ISI
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000855570300004
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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