William Xerri, G. Saracco, G. Gassier, Laurent Zomero, P. Picon
{"title":"Preliminary Acoustic Study of 3D Localization of Buried Polyethylene Pipe","authors":"William Xerri, G. Saracco, G. Gassier, Laurent Zomero, P. Picon","doi":"10.1115/qnde2021-74945","DOIUrl":null,"url":null,"abstract":"\n Acoustic waves are commonly used to locate buried polyethylene pipes. In this preliminary study we are particularly interested in pipes depth. To obtain depth information we are moving towards a multi-sensor solution. Several estimators are implemented and tested on real data. A depth estimator according to the relative delays between sensors is proposed. We compare two relative delays estimators : the method using the cross-correlation and the one using the coherence function. We will verify on real measurements that the second method is much more efficient than the first one. Before discussing the results we will present another approach which consists in adapting the MUSIC (MUltiple SIgnals Classification) algorithm to our problem.","PeriodicalId":189764,"journal":{"name":"2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/qnde2021-74945","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Acoustic waves are commonly used to locate buried polyethylene pipes. In this preliminary study we are particularly interested in pipes depth. To obtain depth information we are moving towards a multi-sensor solution. Several estimators are implemented and tested on real data. A depth estimator according to the relative delays between sensors is proposed. We compare two relative delays estimators : the method using the cross-correlation and the one using the coherence function. We will verify on real measurements that the second method is much more efficient than the first one. Before discussing the results we will present another approach which consists in adapting the MUSIC (MUltiple SIgnals Classification) algorithm to our problem.