L. Schenato, M. Camporese, S. Bersan, S. Cola, A. Galtarossa, A. Pasuto, P. Simonini, P. Salandin, L. Palmieri
{"title":"High density distributed strain sensing of landslide in large scale physical model","authors":"L. Schenato, M. Camporese, S. Bersan, S. Cola, A. Galtarossa, A. Pasuto, P. Simonini, P. Salandin, L. Palmieri","doi":"10.1117/12.2263284","DOIUrl":null,"url":null,"abstract":"This paper describes the application of a commercial distributed optical fiber sensing system to a large scale physical model of landslide. An optical fiber cable, deployed inside the landslide body, is interrogated by means of optical frequency domain reflectometry with very high spatial density. A shallow landslide is triggered in the physical model by artificial rainfall and the evolution of the strain is measured up to the slope failure. Precursory signs of failure are detected well before the collapse, providing insights to the failure dynamic.","PeriodicalId":198716,"journal":{"name":"2017 25th Optical Fiber Sensors Conference (OFS)","volume":"650 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 25th Optical Fiber Sensors Conference (OFS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2263284","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
This paper describes the application of a commercial distributed optical fiber sensing system to a large scale physical model of landslide. An optical fiber cable, deployed inside the landslide body, is interrogated by means of optical frequency domain reflectometry with very high spatial density. A shallow landslide is triggered in the physical model by artificial rainfall and the evolution of the strain is measured up to the slope failure. Precursory signs of failure are detected well before the collapse, providing insights to the failure dynamic.