{"title":"铜表面粗糙度分析的数学形态学算法插入损耗验证","authors":"Li-Chi Chang, Yu-Sen Yang, Yu-Tian Lee, Shao-Wei Hsu, Chieh-Sen Lee, Ming-Chuan Chang","doi":"10.1109/IMPACT56280.2022.9966669","DOIUrl":null,"url":null,"abstract":"Insertion loss of a testing vehicle is widely referred for the material estimation, the differential pair and single-end striplines are generally employed for the high-speed digital applications. In addition to the matte side, the shiny side with the surface treatment of the inner layer is the critical issue for the insertion-loss improvement. In general, the inner-layer roughness is determined by the cross-section scanning electron or optical microscope photo with the manual defining of the average line. Therefore, the tolerance is produced from personal operation or gage repeatability and reproducibility (Gage R and R). In this study, a mathematical morphology algorithm is proposed for automatically detecting the roughness of the striplines. Basing on the algorithm and operating flow, the detected Rz and Rq values of the copper-foil roughness are applied in 3D simulation tool for the insertion-loss validation and comparison.","PeriodicalId":13517,"journal":{"name":"Impact","volume":"7 1","pages":"1-3"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Copper Surface Roughness Analysis in Mathematical Morphology Algorithm for the Insertion-Loss Validation\",\"authors\":\"Li-Chi Chang, Yu-Sen Yang, Yu-Tian Lee, Shao-Wei Hsu, Chieh-Sen Lee, Ming-Chuan Chang\",\"doi\":\"10.1109/IMPACT56280.2022.9966669\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Insertion loss of a testing vehicle is widely referred for the material estimation, the differential pair and single-end striplines are generally employed for the high-speed digital applications. In addition to the matte side, the shiny side with the surface treatment of the inner layer is the critical issue for the insertion-loss improvement. In general, the inner-layer roughness is determined by the cross-section scanning electron or optical microscope photo with the manual defining of the average line. Therefore, the tolerance is produced from personal operation or gage repeatability and reproducibility (Gage R and R). In this study, a mathematical morphology algorithm is proposed for automatically detecting the roughness of the striplines. Basing on the algorithm and operating flow, the detected Rz and Rq values of the copper-foil roughness are applied in 3D simulation tool for the insertion-loss validation and comparison.\",\"PeriodicalId\":13517,\"journal\":{\"name\":\"Impact\",\"volume\":\"7 1\",\"pages\":\"1-3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Impact\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMPACT56280.2022.9966669\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Impact","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMPACT56280.2022.9966669","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Copper Surface Roughness Analysis in Mathematical Morphology Algorithm for the Insertion-Loss Validation
Insertion loss of a testing vehicle is widely referred for the material estimation, the differential pair and single-end striplines are generally employed for the high-speed digital applications. In addition to the matte side, the shiny side with the surface treatment of the inner layer is the critical issue for the insertion-loss improvement. In general, the inner-layer roughness is determined by the cross-section scanning electron or optical microscope photo with the manual defining of the average line. Therefore, the tolerance is produced from personal operation or gage repeatability and reproducibility (Gage R and R). In this study, a mathematical morphology algorithm is proposed for automatically detecting the roughness of the striplines. Basing on the algorithm and operating flow, the detected Rz and Rq values of the copper-foil roughness are applied in 3D simulation tool for the insertion-loss validation and comparison.