I. Velkavrh, Katharina Dimovski, F. Kafexhiu, Thomas Wright
{"title":"Enhanced Efficiency in Coefficient of Friction Evaluation through Automated Data Processing","authors":"I. Velkavrh, Katharina Dimovski, F. Kafexhiu, Thomas Wright","doi":"10.24053/tus-2023-0014","DOIUrl":null,"url":null,"abstract":"In this work, an approach towards automated extraction and evaluation of static and kinematic coefficients of friction is presented. By replacing manual evaluation with an automated process, this approach yields promising results, simplifies data handling, and saves significant time. The methodology shows potential for application to a wide range of experimental data and provides advanced processing capabilities using the extracted and mathematically evaluated data points. However, for data with high signal- to-noise ratios, automatic detection still requires further optimization to improve accuracy.","PeriodicalId":53690,"journal":{"name":"Tribologie und Schmierungstechnik","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tribologie und Schmierungstechnik","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24053/tus-2023-0014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Materials Science","Score":null,"Total":0}
引用次数: 0
Abstract
In this work, an approach towards automated extraction and evaluation of static and kinematic coefficients of friction is presented. By replacing manual evaluation with an automated process, this approach yields promising results, simplifies data handling, and saves significant time. The methodology shows potential for application to a wide range of experimental data and provides advanced processing capabilities using the extracted and mathematically evaluated data points. However, for data with high signal- to-noise ratios, automatic detection still requires further optimization to improve accuracy.