An Integrated Model-Driven and Data-Driven Method Based on CFD-PSO-RBF: Applications to Leakage Detection of Natural Gas Pipelines
Author:
Affiliation:
1. Artificial Intelligence Energy Research Institute (of NEPU),Electrical Information Engineering(of NEPU),Daqing,China
Funder
Natural Science Foundation of Heilongjiang Province
Northeast Petroleum University
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10598401/10598402/10598640.pdf?arnumber=10598640
Reference22 articles.
1. A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples
2. Matched-field processing for leak localization in a viscoelastic pipe: An experimental study
3. Study of Multisource Leakage Diffusion and Explosion Risk of Underground Natural Gas Pipelines
4. Pipeline signal feature extraction method based on multi-feature entropy fusion and local linear embedding
5. Numerical simulation study of infrasound signal characteristics and attenuation law of pipeline leakage;Zhong;Safety & Security,2022
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