Ekta Sharma, Shivali, Jyotsna, P. Mahapatra, Amit Doegar
{"title":"刀具状态监测采用链码技术、像素匹配和形态运算","authors":"Ekta Sharma, Shivali, Jyotsna, P. Mahapatra, Amit Doegar","doi":"10.1109/CIACT.2017.7977270","DOIUrl":null,"url":null,"abstract":"Tool condition in various machining processes directly affects the quality of machined surfaces. Tool condition needs to be monitored with the purpose of evaluating the tool life and timely replacing it, if it is not in favourable condition. The present work focuses on monitoring of tool condition through image processing. The images of the single point lathe tool have been captured before and after machining by a machine vision system. These images are processed using MATLAB image processing toolbox software and tool condition has been evaluated. Different methods, i.e. Chain code, pixel matching and morphological operations have been successfully implemented for extracting the shape of the tool. Depending upon the shape of the tool, it has been classified as ‘Normal’ or ‘Worn’.","PeriodicalId":218079,"journal":{"name":"2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Tool condition monitoring using the chain code technique, pixel matching and morphological operations\",\"authors\":\"Ekta Sharma, Shivali, Jyotsna, P. Mahapatra, Amit Doegar\",\"doi\":\"10.1109/CIACT.2017.7977270\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tool condition in various machining processes directly affects the quality of machined surfaces. Tool condition needs to be monitored with the purpose of evaluating the tool life and timely replacing it, if it is not in favourable condition. The present work focuses on monitoring of tool condition through image processing. The images of the single point lathe tool have been captured before and after machining by a machine vision system. These images are processed using MATLAB image processing toolbox software and tool condition has been evaluated. Different methods, i.e. Chain code, pixel matching and morphological operations have been successfully implemented for extracting the shape of the tool. Depending upon the shape of the tool, it has been classified as ‘Normal’ or ‘Worn’.\",\"PeriodicalId\":218079,\"journal\":{\"name\":\"2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIACT.2017.7977270\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIACT.2017.7977270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tool condition monitoring using the chain code technique, pixel matching and morphological operations
Tool condition in various machining processes directly affects the quality of machined surfaces. Tool condition needs to be monitored with the purpose of evaluating the tool life and timely replacing it, if it is not in favourable condition. The present work focuses on monitoring of tool condition through image processing. The images of the single point lathe tool have been captured before and after machining by a machine vision system. These images are processed using MATLAB image processing toolbox software and tool condition has been evaluated. Different methods, i.e. Chain code, pixel matching and morphological operations have been successfully implemented for extracting the shape of the tool. Depending upon the shape of the tool, it has been classified as ‘Normal’ or ‘Worn’.