{"title":"利用δ t映射进行近场地震定位","authors":"SHI Peng-Cheng, WANG Yuan, YOU Qing-Yu","doi":"10.1002/cjg2.30061","DOIUrl":null,"url":null,"abstract":"<p>Near-field seismic localization has important significance and wide applications in the real world, for instance, locating explosions or tracking traffic movements. The traditional methods designed for far-field scenarios are limited here due to the unknown velocity structures and high accuracy demands. This paper, for the first time, applied the Delta T Mapping (DTM) technique from acoustic emission detection in near-field seismic localization. DTM first needs to construct a mapping of the difference of first arrivals on which the following locating is based. There are two approaches for establishing such model: (1) grid search method: using linear scattered point interpolation to obtain new DTM of higher resolution; (2) statistical locating method: using Gaussian Process Regression to build the mapping from Delta T to positions. The experiment was conducted in an area of 140 m×90 m in the suburb of Beijing. The locating error was 0.5∼5.1 m. The results showed that DTM is reliable, highly accurate and suitable for real-time use for near-field seismic localization. The cost of learning DTM and analyzing data could be further decreased while obtaining highly accurate DTM by switching the sources and receivers. Furthermore, combining source-scan algorithm has certain potential to locate multi-sources.</p>","PeriodicalId":100242,"journal":{"name":"Chinese Journal of Geophysics","volume":"60 5","pages":"465-479"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cjg2.30061","citationCount":"0","resultStr":"{\"title\":\"NEAR-FIELD SEISMIC LOCALIZATION USING DELTA T MAPPING\",\"authors\":\"SHI Peng-Cheng, WANG Yuan, YOU Qing-Yu\",\"doi\":\"10.1002/cjg2.30061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Near-field seismic localization has important significance and wide applications in the real world, for instance, locating explosions or tracking traffic movements. The traditional methods designed for far-field scenarios are limited here due to the unknown velocity structures and high accuracy demands. This paper, for the first time, applied the Delta T Mapping (DTM) technique from acoustic emission detection in near-field seismic localization. DTM first needs to construct a mapping of the difference of first arrivals on which the following locating is based. There are two approaches for establishing such model: (1) grid search method: using linear scattered point interpolation to obtain new DTM of higher resolution; (2) statistical locating method: using Gaussian Process Regression to build the mapping from Delta T to positions. The experiment was conducted in an area of 140 m×90 m in the suburb of Beijing. The locating error was 0.5∼5.1 m. The results showed that DTM is reliable, highly accurate and suitable for real-time use for near-field seismic localization. The cost of learning DTM and analyzing data could be further decreased while obtaining highly accurate DTM by switching the sources and receivers. Furthermore, combining source-scan algorithm has certain potential to locate multi-sources.</p>\",\"PeriodicalId\":100242,\"journal\":{\"name\":\"Chinese Journal of Geophysics\",\"volume\":\"60 5\",\"pages\":\"465-479\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/cjg2.30061\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chinese Journal of Geophysics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cjg2.30061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chinese Journal of Geophysics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cjg2.30061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
近场地震定位在现实世界中有着重要的意义和广泛的应用,例如定位爆炸或跟踪交通运动。由于速度结构未知和精度要求高,传统的远场方法在此受到限制。本文首次将声发射探测中的Delta T Mapping (DTM)技术应用于近场地震定位。DTM首先需要构造一个首到差的映射,以此为基础进行后续定位。建立该模型的方法有两种:(1)网格搜索法:利用线性散点插值获得更高分辨率的新DTM;(2)统计定位法:利用高斯过程回归建立从T到位置的映射。实验在北京郊区140 m×90 m的范围内进行。定位误差为0.5 ~ 5.1 m。结果表明,DTM方法可靠、精度高,适合实时应用于近场地震定位。通过源和接收机的切换,可以在获得高精度DTM的同时,进一步降低学习DTM和分析数据的成本。此外,结合源扫描算法在多源定位方面具有一定的潜力。
NEAR-FIELD SEISMIC LOCALIZATION USING DELTA T MAPPING
Near-field seismic localization has important significance and wide applications in the real world, for instance, locating explosions or tracking traffic movements. The traditional methods designed for far-field scenarios are limited here due to the unknown velocity structures and high accuracy demands. This paper, for the first time, applied the Delta T Mapping (DTM) technique from acoustic emission detection in near-field seismic localization. DTM first needs to construct a mapping of the difference of first arrivals on which the following locating is based. There are two approaches for establishing such model: (1) grid search method: using linear scattered point interpolation to obtain new DTM of higher resolution; (2) statistical locating method: using Gaussian Process Regression to build the mapping from Delta T to positions. The experiment was conducted in an area of 140 m×90 m in the suburb of Beijing. The locating error was 0.5∼5.1 m. The results showed that DTM is reliable, highly accurate and suitable for real-time use for near-field seismic localization. The cost of learning DTM and analyzing data could be further decreased while obtaining highly accurate DTM by switching the sources and receivers. Furthermore, combining source-scan algorithm has certain potential to locate multi-sources.