Acoustic-based approach for micro-leakage detection and localization in water supply pipelines

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-05-13 DOI:10.1039/D3EW00686G
Cuimin Feng, Jiancong Zhao, Qiangsan Ran, Mengchao Qu and Zixiao Guo
{"title":"Acoustic-based approach for micro-leakage detection and localization in water supply pipelines","authors":"Cuimin Feng, Jiancong Zhao, Qiangsan Ran, Mengchao Qu and Zixiao Guo","doi":"10.1039/D3EW00686G","DOIUrl":null,"url":null,"abstract":"<p >Acoustic detection is a widely used method for investigating leaks in water supply pipelines. However, improving the accuracy of acoustic detection techniques is crucial, especially in scenarios with low pipeline pressures (≤0.2 MPa) and small leak apertures (≤2 mm), where micro-leakage detection poses challenges. In this study, a pipeline model is constructed based on acoustic leak detection principles, and numerical simulations are performed using FLUENT software. The occurrence and propagation of sound are simulated using the Foutz-Williams–Hawkins (FW–H) equation, to generate sound signals by micro-leakage in pipe sections with adjacent tee pipe fittings. The results indicate that the average sound pressure amplitude caused by pipeline vibration varies with changes in pressure. In particular, upstream locations exhibit a higher degree of variability compared to downstream locations. An increase in both pipeline pressure and leak aperture leads to an amplified power spectrum across different frequency bands at various detection points. However, the energy generated by water leaks and vibrations in tee pipe fittings is relatively low and heavily distorted by ambient signals. To mitigate these challenges, a combination of the empirical mode decomposition (EMD) method is utilized to extract leak sound signals and eliminate interference information. Additionally, the cross-correlation time delay estimation method is used to determine the time difference between upstream and downstream sensors when receiving leak sound signals. This approach successfully identifies and localizes leakage points in pipe segments with tee pipe fittings. This study provides evidence of the effectiveness of this approach in detecting and localizing micro-leakage points in water supply pipelines, achieving a remarkable localization result with a relative error of only 1%.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"93","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/ew/d3ew00686g","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

Acoustic detection is a widely used method for investigating leaks in water supply pipelines. However, improving the accuracy of acoustic detection techniques is crucial, especially in scenarios with low pipeline pressures (≤0.2 MPa) and small leak apertures (≤2 mm), where micro-leakage detection poses challenges. In this study, a pipeline model is constructed based on acoustic leak detection principles, and numerical simulations are performed using FLUENT software. The occurrence and propagation of sound are simulated using the Foutz-Williams–Hawkins (FW–H) equation, to generate sound signals by micro-leakage in pipe sections with adjacent tee pipe fittings. The results indicate that the average sound pressure amplitude caused by pipeline vibration varies with changes in pressure. In particular, upstream locations exhibit a higher degree of variability compared to downstream locations. An increase in both pipeline pressure and leak aperture leads to an amplified power spectrum across different frequency bands at various detection points. However, the energy generated by water leaks and vibrations in tee pipe fittings is relatively low and heavily distorted by ambient signals. To mitigate these challenges, a combination of the empirical mode decomposition (EMD) method is utilized to extract leak sound signals and eliminate interference information. Additionally, the cross-correlation time delay estimation method is used to determine the time difference between upstream and downstream sensors when receiving leak sound signals. This approach successfully identifies and localizes leakage points in pipe segments with tee pipe fittings. This study provides evidence of the effectiveness of this approach in detecting and localizing micro-leakage points in water supply pipelines, achieving a remarkable localization result with a relative error of only 1%.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于声学的供水管道微渗漏检测和定位方法
声学检测是一种广泛应用于调查供水管道泄漏的方法。然而,提高声学检测技术的准确性至关重要,尤其是在管道压力较低(≤0.2 兆帕)、泄漏孔径较小(≤2 毫米)的情况下,微泄漏检测面临挑战。本研究根据声学泄漏检测原理构建了管道模型,并使用 FLUENT 软件进行了数值模拟。利用 Foutz-Williams-Hawkins (FW-H) 方程模拟了声音的发生和传播,以产生带有相邻三通管件的管段中微泄漏的声音信号。结果表明,管道振动引起的平均声压振幅随压力变化而变化。特别是,与下游位置相比,上游位置的变化程度更高。管道压力和泄漏孔径的增加会导致不同检测点不同频段的功率谱放大。然而,漏水和三通管件振动产生的能量相对较低,且被环境信号严重扭曲。为了减轻这些挑战,我们结合使用了经验模式分解(EMD)方法来提取漏水声音信号并消除干扰信息。此外,在接收泄漏声音信号时,使用交叉相关时间延迟估计法来确定上下游传感器之间的时间差。这种方法成功地识别并定位了带有三通管件的管段中的泄漏点。这项研究证明了这种方法在检测和定位供水管道微渗漏点方面的有效性,并取得了显著的定位效果,相对误差仅为 1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
期刊最新文献
Vitamin B12: prevention of human beings from lethal diseases and its food application. Current status and obstacles of narrowing yield gaps of four major crops. Cold shock treatment alleviates pitting in sweet cherry fruit by enhancing antioxidant enzymes activity and regulating membrane lipid metabolism. Removal of proteins and lipids affects structure, in vitro digestion and physicochemical properties of rice flour modified by heat-moisture treatment. Investigating the impact of climate variables on the organic honey yield in Turkey using XGBoost machine learning.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1