Leakage Detection in Underground Gas Pipeline

2019 ◽  
Vol 7 (6) ◽  
pp. 732-736
Author(s):  
Renuka Kishor Kale ◽  
S. L. Nalbalwar ◽  
S. B. Deosarkar ◽  
Sachin Singh
2014 ◽  
Vol 51 (11) ◽  
pp. 110602 ◽  
Author(s):  
黄悦 Huang Yue ◽  
王强 Wang Qiang ◽  
杨其华 Yang Qihua ◽  
章仁杰 Zhang Renjie

2021 ◽  
Vol 2076 (1) ◽  
pp. 012004
Author(s):  
Jianfeng Gao ◽  
Yu Zheng ◽  
Kai Ni ◽  
Huaizhi Zhang ◽  
Bin Hao ◽  
...  

Abstract In order to solve the problem of low accuracy in oil-gas pipeline leak detection, a pipeline leak detection method based on Particle Swarm Optimization (PSO) algorithm optimized Support Vector Machine (SVM) is introduced. This method uses PSO to solve the penalty factor ‘c’ and kernel function parameter ‘g’, and constructs the pipeline leakage detection model of SVM. We set up an experimental platform to collect negative pressure wave signals under different working conditions. After wavelet domain denoising and data preprocessing, four eigenvalues of Mean, Standard Deviation, Kurtosis and Skewness are extracted from the signals to form the eigenvector samples, which are taken as input of SVM, and four working conditions of normal, leakage, rise and fall are taken as output. Through experimental verification, the comprehensive performance of PSO-SVM algorithm is better than that of traditional SVM, Genetic Algorithm optimized SVM and grid search algorithm optimized SVM. The POS-SVM algorithm can be applied to the leak detection of oil-gas pipeline.


2013 ◽  
Vol 31 ◽  
pp. 1-7 ◽  
Author(s):  
Wei Liang ◽  
Laibin Zhang ◽  
Qingqing Xu ◽  
Chunying Yan

2012 ◽  
Vol 49 (7) ◽  
pp. 070602
Author(s):  
胡正松 Hu Zhengsong ◽  
杨其华 Yang Qihua ◽  
乔波 Qiao Bo

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