Hydroinformatics based technique for leak identification purpose – An experimental analysis

Author:

Hanafi M Y,Ghazali M F,Azmi W H,Yusof M F M,PiRemli M A

Abstract

Abstract Analysis of single point pressure transient signal has the potential of providing information on the pipeline system. The technique uses the frequency response and experiments are satisfactory for low-frequency bandwidth. The concept behind this approach is that reflections are detected by leak-induced disturbances. Such reflections are often very difficult to identify, particularly because of excessive noise. The common approach to boost the analysis is to use a data denoising approach. The wavelet transforms for leak detection in water pipelines are proposed in this article. The wavelet filter is optimally calibrated using maximal kurtosis values and is chosen for leakage detection. The suggested approach is tested using high-noise laboratory test signals. The findings show that the method is superior to current signal processing methods for the conditions used. The system permits not only the detection of leakage but also the location and evaluation of its magnitude with errors of less than 7%.

Publisher

IOP Publishing

Subject

General Medicine

Reference19 articles.

1. Improvement of Cepstrum Analysis for the Purpose to Detect Leak, Feature and Its Location in Water Distribution System based on Pressure Transient Analysis;Yusop;J. Mech. Eng.,2017

2. Does non-revenue water affect Malaysia’s water services industry productivity?;See;Utilities Policy,2018

3. Applying minimum night flow to estimate water loss using statistical modeling: a case study in Kinta Valley, Malaysia;Alkasseh;Water resources management,2013

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