{"title":"An on-line tool wear monitoring method based on cutting power","authors":"Teng Wan, Xingzheng Chen, C. Li, Ying Tang","doi":"10.1109/COASE.2018.8560412","DOIUrl":null,"url":null,"abstract":"In a CNC batch process, excessive tool wear will lead to a bad surface quality of the final product. On-line tool wear monitoring is recognized as an effective method to reduce the impact of the tool wear on surface quality. In this paper, a cutting power model is firstly established with the consideration of tool wear and cutting parameters. A novel on-line tool wear monitoring approach for CNC batch processing is then proposed and a monitoring system is developed. Result of the case study shows that the proposed approach is effective in tool wear on-line monitoring.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"211 1","pages":"205-210"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2018.8560412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In a CNC batch process, excessive tool wear will lead to a bad surface quality of the final product. On-line tool wear monitoring is recognized as an effective method to reduce the impact of the tool wear on surface quality. In this paper, a cutting power model is firstly established with the consideration of tool wear and cutting parameters. A novel on-line tool wear monitoring approach for CNC batch processing is then proposed and a monitoring system is developed. Result of the case study shows that the proposed approach is effective in tool wear on-line monitoring.