Study on leak-acoustics generation mechanism for natural gas pipelines

被引:44
作者
Liu, Cuiwei [1 ]
Li, Yuxing [1 ]
Meng, Lingya [2 ]
Wang, Wuchang [1 ]
Zhang, Fan [1 ]
机构
[1] China Univ Petr East China, Coll Pipeline & Civil Engn, Qjngdao 266555, Peoples R China
[2] China Univ Petr East China, Coll Informat & Control Engn, Qingdao 266555, Peoples R China
基金
美国国家科学基金会;
关键词
Natural gas pipelines; Leak-acoustics; Generation mechanism; Pressure perturbations; LOCATION; PIPE; SOUND;
D O I
10.1016/j.jlp.2014.08.010
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In order to figure out the principles of acoustic leak detection for natural gas pipelines, a study on the leak-acoustics generation mechanism is carried out. The aero-acoustics generation mechanism is analyzed and when leakage occurs the wave equations of sonic sources are developed. The leak-acoustics generated by the quadrupole and dipole sonic sources are then simulated to obtain the laws of the acoustic characteristics. The simulation data are compared with the experimental data to verify the simulation accuracy under variable operating conditions. The results show that the quadrupoles and the dipoles generated by turbulent fluctuations cause leak-acoustics; the main component of pressure perturbations acquired by the dynamic pressure sensor is acoustic perturbations: both the simulation method and the experimental method can be applied to study the leak-acoustics generation mechanism of natural gas pipelines. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:174 / 181
页数:8
相关论文
共 50 条
  • [41] Dynamic Response of Buried Natural Gas Pipelines under Horizontal Directional Drilling Loads
    Zhang, Kai
    Chen, Liqiong
    He, Ting
    Xu, Duo
    Huang, Weihe
    Yang, Song
    Zeng, Zhiqiang
    [J]. INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS, 2025, 25 (01)
  • [42] Leakage monitoring research and design for natural gas pipelines based on dynamic pressure waves
    Liu, Cuiwei
    Li, Yuxing
    Fang, Liping
    Han, Jinke
    Xu, Minghai
    [J]. JOURNAL OF PROCESS CONTROL, 2017, 50 : 66 - 76
  • [43] Failure analysis of carbon dioxide corrosion through wet natural gas gathering pipelines
    Abd, Ammar Ali
    Naji, Samah Zaki
    Hashim, Atheer Saad
    [J]. ENGINEERING FAILURE ANALYSIS, 2019, 105 : 638 - 646
  • [44] Likelihood, causes, and consequences of focused leakage and rupture of US natural gas transmission pipelines
    Wang, Hui
    Duncan, Ian J.
    [J]. JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2014, 30 : 177 - 187
  • [45] Natural gas pipeline leak detection based on acoustic signal analysis and feature reconstruction
    Yao, Lizhong
    Zhang, Yu
    He, Tiantian
    Luo, Haijun
    [J]. APPLIED ENERGY, 2023, 352
  • [46] Seismic fragility of buried steel natural gas pipelines due to axial compression at geotechnical discontinuities
    Grigorios Tsinidis
    Luigi Di Sarno
    Anastasios Sextos
    Peter Furtner
    [J]. Bulletin of Earthquake Engineering, 2020, 18 : 837 - 906
  • [47] Leak aperture recognition of natural gas pipeline based on variational mode decomposition and mutual information
    Ni, Lei
    Gu, Wei
    Zhou, Tao
    Hao, Peiqing
    Jiang, Juncheng
    [J]. MEASUREMENT, 2025, 242
  • [48] High-throughput sequencing approach in analysis of microbial communities colonizing natural gas pipelines
    Staniszewska, Agnieszka
    Kunicka-Styczynska, Alina
    Otlewska, Anna
    Gawor, Jan
    Gromadka, Robert
    Zuchniewicz, Karolina
    Zieminski, Krzysztof
    [J]. MICROBIOLOGYOPEN, 2019, 8 (08):
  • [49] Seismic fragility of buried steel natural gas pipelines due to axial compression at geotechnical discontinuities
    Tsinidis, Grigorios
    Di Sarno, Luigi
    Sextos, Anastasios
    Furtner, Peter
    [J]. BULLETIN OF EARTHQUAKE ENGINEERING, 2020, 18 (03) : 837 - 906
  • [50] A hybrid machine learning model for predicting crater width formed by explosions of natural gas pipelines
    Qin, Guojin
    Xia, Ailin
    Lu, Hongfang
    Wang, Yihuan
    Li, Ruiling
    Wang, Chengtao
    [J]. JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2023, 82