An FBG Strain Sensor-Based NPW Method for Natural Gas Pipeline Leakage Detection

Author:

Hou Qingmin1ORCID

Affiliation:

1. School of Energy and Building Engineering, Harbin University of Commerce, Harbin 150028, China

Abstract

Natural gas pipeline leaks can lead to serious and dangerous accidents that can cause great losses of life and property. Therefore, detecting natural gas pipeline leaks has always been an important subject. The negative pressure wave (NPW) method is currently the most widely used leakage detection method. Generally, this method uses pressure sensors to detect NPW signals to assess the leak and determine the location of the leakage point. However, the installation of a pressure sensor requires penetrating the pipeline structure, so the sensor intervals are often distant, leading to large signal attenuations and the ineffective detection of small leaks. An NPW method based on fiber Bragg grating (FBG) strain sensors is proposed in this paper which detects NPWs by monitoring the annular strain of the pipeline. Moreover, due to the advantages of nondestructive installation FBG strain sensors can be arranged closer along the distance of the pipeline, the attenuation of the NPW is small and the detection of leaks is improved. This method is tested through experiments and compared with a pressure sensor-based method; the experimental results verify that the proposed method is more effective in detecting natural gas pipeline leaks.

Funder

Harbin University of Commerce

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference27 articles.

1. A Framework for Smart Production-Logistics Systems Based on CPS and Industrial IoT

2. A self-learning approach for optimal detailed scheduling of multi-product pipeline;H. R. Zhang;Journal of Computational and Applied Mathematics,2018

3. A MILP model based on flowrate database for detailed scheduling of a multi-product pipeline with multiple pump stations;Q. Liao;Computers & Chemical. Engineering.,2018

4. New batch-centric model for detailed scheduling and inventory management of mesh pipeline networks

5. A leakage risk assessment method for hazardous liquid pipeline based on Markov chain Monte Carlo

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