Adalto Farias, Vanessa Seriacopi, Marcelo Otávio dos Santos, Ed Claudio Bordinassi
{"title":"3-axis computer numerical control machine positioning error dataset for thermal error compensation","authors":"Adalto Farias, Vanessa Seriacopi, Marcelo Otávio dos Santos, Ed Claudio Bordinassi","doi":"10.1016/j.dib.2024.110942","DOIUrl":null,"url":null,"abstract":"<div><div>This article reports on a comprehensive dataset detailing positioning errors in a 3-axis milling center machine (MCM) with computer numerical control (CNC) specifically curated for thermal error compensation. The data, which includes separate datasets for the X, Y, and Z axes, was collected through systematic measurements using an interferometric laser (IL) system under monitored thermal conditions. Each axis's acquisition was recorded with a resolution to capture dynamic variations influenced by thermal fluctuations. Temperature measurements were obtained using resistance temperature detectors (RTD) installed in the bearing housings of each axis for monitoring of thermal conditions throughout the data collection process in each axis. The dataset comprises raw positional and error data for each axis alongside metadata describing parameters such as bearing temperature, heating cycle, and machine operating conditions. This dataset can potentially be a valuable resource for researchers, enabling them to develop and validate real-time thermal error compensation algorithms, thereby enhancing CNC machining precision for each axis independently and collectively. Furthermore, the dataset's structured format facilitates comparative studies across different machine configurations and operational contexts, contributing to advancements in manufacturing technology and improvements in process parameter design and optimization.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352340924009053/pdfft?md5=3080bb58ed3bb682b8da6a21fd4b2f2d&pid=1-s2.0-S2352340924009053-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340924009053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This article reports on a comprehensive dataset detailing positioning errors in a 3-axis milling center machine (MCM) with computer numerical control (CNC) specifically curated for thermal error compensation. The data, which includes separate datasets for the X, Y, and Z axes, was collected through systematic measurements using an interferometric laser (IL) system under monitored thermal conditions. Each axis's acquisition was recorded with a resolution to capture dynamic variations influenced by thermal fluctuations. Temperature measurements were obtained using resistance temperature detectors (RTD) installed in the bearing housings of each axis for monitoring of thermal conditions throughout the data collection process in each axis. The dataset comprises raw positional and error data for each axis alongside metadata describing parameters such as bearing temperature, heating cycle, and machine operating conditions. This dataset can potentially be a valuable resource for researchers, enabling them to develop and validate real-time thermal error compensation algorithms, thereby enhancing CNC machining precision for each axis independently and collectively. Furthermore, the dataset's structured format facilitates comparative studies across different machine configurations and operational contexts, contributing to advancements in manufacturing technology and improvements in process parameter design and optimization.
期刊介绍:
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