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

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