{"title":"Structure of digital metrological twins as software for uncertainty estimation","authors":"I. Poroskun, C. Rothleitner, D. Heißelmann","doi":"10.5194/jsss-11-75-2022","DOIUrl":null,"url":null,"abstract":"Abstract. Ongoing digitalization in metrology and the ever-growing complexity of measurement systems have increased the effort required to create complex software for uncertainty estimation. To address this issue, a general structure for uncertainty estimation software will be presented in this work. The structure was derived from the Virtual Coordinate Measuring Machine (VCMM), which is a well-established tool for uncertainty estimation in the field of coordinate metrology. To make it easy to apply the software structure to specific projects, a supporting software library was created. The library is written in a portable and extensible way using the C++ programming language. The software structure and library proposed can be used in different domains of metrology. The library provides all the components necessary for uncertainty estimation (i.e., random number generators and GUM S1-compliant routines). Only the project-specific parts of the software must be developed by potential users. To verify the usability of the software structure and the library, a Virtual Planck-Balance, which is the digital metrological twin of a Kibble balance, is currently being developed.\n","PeriodicalId":17167,"journal":{"name":"Journal of Sensors and Sensor Systems","volume":" ","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Sensors and Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/jsss-11-75-2022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract. Ongoing digitalization in metrology and the ever-growing complexity of measurement systems have increased the effort required to create complex software for uncertainty estimation. To address this issue, a general structure for uncertainty estimation software will be presented in this work. The structure was derived from the Virtual Coordinate Measuring Machine (VCMM), which is a well-established tool for uncertainty estimation in the field of coordinate metrology. To make it easy to apply the software structure to specific projects, a supporting software library was created. The library is written in a portable and extensible way using the C++ programming language. The software structure and library proposed can be used in different domains of metrology. The library provides all the components necessary for uncertainty estimation (i.e., random number generators and GUM S1-compliant routines). Only the project-specific parts of the software must be developed by potential users. To verify the usability of the software structure and the library, a Virtual Planck-Balance, which is the digital metrological twin of a Kibble balance, is currently being developed.
期刊介绍:
Journal of Sensors and Sensor Systems (JSSS) is an international open-access journal dedicated to science, application, and advancement of sensors and sensors as part of measurement systems. The emphasis is on sensor principles and phenomena, measuring systems, sensor technologies, and applications. The goal of JSSS is to provide a platform for scientists and professionals in academia – as well as for developers, engineers, and users – to discuss new developments and advancements in sensors and sensor systems.