P. Kalansuriya, R. Bhattacharyya, S. Sarma, N. Karmakar
{"title":"Towards chipless RFID-based sensing for pervasive surface crack detection","authors":"P. Kalansuriya, R. Bhattacharyya, S. Sarma, N. Karmakar","doi":"10.1109/RFID-TA.2012.6404565","DOIUrl":null,"url":null,"abstract":"We present Surface Crack Antenna Reflectometric Sensing or SCARS: a chipless RFID sensor that enables pervasive, wireless surface crack detection in structural materials. We outline the sensor design and demonstrate how crack length and orientation can be related to the backscatter signal signature of the SCARS sensor. In doing so, design techniques that improve sensor sensitivity and signal fidelity are presented. Proof of concept is then demonstrated via numerical simulation and the implementation of a laboratory prototype. Finally, an envisioned pervasive health monitoring and data extraction strategy using these sensors is also discussed.","PeriodicalId":232862,"journal":{"name":"2012 IEEE International Conference on RFID-Technologies and Applications (RFID-TA)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on RFID-Technologies and Applications (RFID-TA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RFID-TA.2012.6404565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 34
Abstract
We present Surface Crack Antenna Reflectometric Sensing or SCARS: a chipless RFID sensor that enables pervasive, wireless surface crack detection in structural materials. We outline the sensor design and demonstrate how crack length and orientation can be related to the backscatter signal signature of the SCARS sensor. In doing so, design techniques that improve sensor sensitivity and signal fidelity are presented. Proof of concept is then demonstrated via numerical simulation and the implementation of a laboratory prototype. Finally, an envisioned pervasive health monitoring and data extraction strategy using these sensors is also discussed.