Non-invasive leakage detection & localisation technique in noisy industrial environment

Author:

Efstathiadis Theofilos,Kalfas Anestis,Kousiopoulos Georgios P.,Papastavrou Georgios N.,Nikolaidis Spiros

Abstract

An innovative non-invasive method for pipe leak detection and localization in noisy environment is presented in this paper. Nowadays, it is well known that complex pipeline networks are used for operational purposes and fluid transportation in every high-end-technology heavy industry such as refineries, combined heat and power cycles, cement and steel industries, etc. In all these cases, safety is the key parameter in order to ensure the efficient plant operation and to avoid any possible accident with devastating consequences that may lead to a turn down of the production process. For this reason, it is mandatory to develop reliable enough methods for detection of fluid leakages which represent the most common threaten in pipeline networks. Towards to this direction an integrated experimental setup was built in order to validate the results of the algorithm which was also developed for the purposes of the present study and aims to detect and locate the artificial leakages through the attenuation of the acoustic signal propagating in a pipeline. This experimental setup consists of pipelines that installed into an anechoic chamber and uses pure water as working medium. Apart from the high-efficient accuracy of the developed algorithm in the leakage detection and localization, the proposed method was designed with extra focus on the reduced CAPEX and OPEX costs. Finally, according to the results the proposed system gives sufficiently low false alarm regarding the leakage detection, while the mean percentage error of the leakage localization is around 6% which is considered as an acceptable value.

Publisher

EDP Sciences

Subject

General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3