用于海底沉积物原位声速测量的时差自动提取方法

IF 1.8 3区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS
Qingfeng Hua, Jingqiang Wang, Guanbao Li, Linqing Zhang, Lei Sun, Wuwen Dong
{"title":"用于海底沉积物原位声速测量的时差自动提取方法","authors":"Qingfeng Hua,&nbsp;Jingqiang Wang,&nbsp;Guanbao Li,&nbsp;Linqing Zhang,&nbsp;Lei Sun,&nbsp;Wuwen Dong","doi":"10.1111/1365-2478.13514","DOIUrl":null,"url":null,"abstract":"<p>The in situ acoustic measurement of seafloor sediment is an important technical means to obtain the acoustic parameters of seafloor. The time-of-flight method is commonly used to calculate the sound speed in seafloor sediment. Accurate identification of signal feature points is essential for determining travel time or travel time difference of acoustic signals. However, the precise identification of feature points, such as the take-off point of the first wave of a sound wave signal, is challenging. The conventional manual identification method is inefficient and prone to errors. The development of a feature point auto-identification method is imperative for accurately calculating the travel time of acoustic signals. In this study, we employed the cross-correlation method, the level threshold method and the short window-long window energy ratio method to extract the acoustic travel time differences and calculate the sound speeds in seawater and in seafloor sediment. We then analysed the effectiveness of these calculated results. The sound speeds in seawater obtained through the aforementioned methods were compared with the sound speeds measured using a sound velocity profiler. The comparison revealed that these processing methods exhibit a high level of accuracy. The sound speed results in sediments show that the programme-based auto-identification methods significantly reduce the standard deviation compared to the manual identification method. This study successfully assessed the processing accuracy of different methods and expanded the processing methods for in situ acoustic signals of seafloor sediments.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 6","pages":"2261-2273"},"PeriodicalIF":1.8000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time difference auto-extraction methods for in situ sound speed measurements in seafloor sediments\",\"authors\":\"Qingfeng Hua,&nbsp;Jingqiang Wang,&nbsp;Guanbao Li,&nbsp;Linqing Zhang,&nbsp;Lei Sun,&nbsp;Wuwen Dong\",\"doi\":\"10.1111/1365-2478.13514\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The in situ acoustic measurement of seafloor sediment is an important technical means to obtain the acoustic parameters of seafloor. The time-of-flight method is commonly used to calculate the sound speed in seafloor sediment. Accurate identification of signal feature points is essential for determining travel time or travel time difference of acoustic signals. However, the precise identification of feature points, such as the take-off point of the first wave of a sound wave signal, is challenging. The conventional manual identification method is inefficient and prone to errors. The development of a feature point auto-identification method is imperative for accurately calculating the travel time of acoustic signals. In this study, we employed the cross-correlation method, the level threshold method and the short window-long window energy ratio method to extract the acoustic travel time differences and calculate the sound speeds in seawater and in seafloor sediment. We then analysed the effectiveness of these calculated results. The sound speeds in seawater obtained through the aforementioned methods were compared with the sound speeds measured using a sound velocity profiler. The comparison revealed that these processing methods exhibit a high level of accuracy. The sound speed results in sediments show that the programme-based auto-identification methods significantly reduce the standard deviation compared to the manual identification method. This study successfully assessed the processing accuracy of different methods and expanded the processing methods for in situ acoustic signals of seafloor sediments.</p>\",\"PeriodicalId\":12793,\"journal\":{\"name\":\"Geophysical Prospecting\",\"volume\":\"72 6\",\"pages\":\"2261-2273\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geophysical Prospecting\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/1365-2478.13514\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geophysical Prospecting","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1365-2478.13514","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 0

摘要

海底沉积物原位声学测量是获取海底声学参数的重要技术手段。飞行时间法通常用于计算海底沉积物中的声速。准确识别信号特征点对于确定声信号的传播时间或传播时差至关重要。然而,精确识别特征点(如声波信号第一波的起飞点)是一项挑战。传统的人工识别方法效率低且容易出错。为了准确计算声波信号的传播时间,开发一种特征点自动识别方法势在必行。在本研究中,我们采用了交叉相关法、电平阈值法和短窗口-长窗口能量比法提取声波旅行时间差,并计算出海水和海底沉积物中的声速。然后,我们分析了这些计算结果的有效性。我们将通过上述方法获得的海水声速与使用声速剖面仪测量的声速进行了比较。比较结果表明,这些处理方法具有很高的准确性。沉积物中的声速结果表明,与人工识别方法相比,基于程序的自动识别方法大大降低了标准偏差。这项研究成功评估了不同方法的处理精度,拓展了海底沉积物原位声学信号的处理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time difference auto-extraction methods for in situ sound speed measurements in seafloor sediments

The in situ acoustic measurement of seafloor sediment is an important technical means to obtain the acoustic parameters of seafloor. The time-of-flight method is commonly used to calculate the sound speed in seafloor sediment. Accurate identification of signal feature points is essential for determining travel time or travel time difference of acoustic signals. However, the precise identification of feature points, such as the take-off point of the first wave of a sound wave signal, is challenging. The conventional manual identification method is inefficient and prone to errors. The development of a feature point auto-identification method is imperative for accurately calculating the travel time of acoustic signals. In this study, we employed the cross-correlation method, the level threshold method and the short window-long window energy ratio method to extract the acoustic travel time differences and calculate the sound speeds in seawater and in seafloor sediment. We then analysed the effectiveness of these calculated results. The sound speeds in seawater obtained through the aforementioned methods were compared with the sound speeds measured using a sound velocity profiler. The comparison revealed that these processing methods exhibit a high level of accuracy. The sound speed results in sediments show that the programme-based auto-identification methods significantly reduce the standard deviation compared to the manual identification method. This study successfully assessed the processing accuracy of different methods and expanded the processing methods for in situ acoustic signals of seafloor sediments.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Geophysical Prospecting
Geophysical Prospecting 地学-地球化学与地球物理
CiteScore
4.90
自引率
11.50%
发文量
118
审稿时长
4.5 months
期刊介绍: Geophysical Prospecting publishes the best in primary research on the science of geophysics as it applies to the exploration, evaluation and extraction of earth resources. Drawing heavily on contributions from researchers in the oil and mineral exploration industries, the journal has a very practical slant. Although the journal provides a valuable forum for communication among workers in these fields, it is also ideally suited to researchers in academic geophysics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信