Natural-Gas Transmission Pipeline-Leak Detection Model Based on Acoustic Emission and Machine Learning-Reference-Cited by-同舟云学术

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Natural-Gas Transmission Pipeline-Leak Detection Model Based on Acoustic Emission and Machine Learning

Published:2024-11 Issue:4 Volume:15 Page:
ISSN:1949-1190
Container-title:Journal of Pipeline Systems Engineering and Practice
language:en
Short-container-title:J. Pipeline Syst. Eng. Pract.

Author:

Wang Xinying¹^ORCID,Li Anqi²^ORCID,Lin Zhenyuan³,Li Shimin²^ORCID,Yang Yang²^ORCID

Affiliation:

1. Associate Professor, School of Safety and Engineering, Changzhou Univ., Changzhou, Jiangsu 213164, China (corresponding author). ORCID: .

2. School of Safety and Engineering, Changzhou Univ., Changzhou, Jiangsu 213164, China. ORCID:

3. School of Safety and Engineering, Changzhou Univ., Changzhou, Jiangsu 213164, China; College of Civil Engineering and Mechanics, Lanzhou Univ., Lanzhou, Gansu 730000, China.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JPSEA2.PSENG-1558

Reference22 articles.

1. A Method for Pipeline Leak Detection Based on Acoustic Imaging and Deep Learning

2. Evaluating prediction model performance;Cabot J. H.;Surgery,2023

3. Fault detection and diagnostic method of diesel engine by combining rule-based algorithm and BNS/BPNNS;Cai B.;J. Manuf. Syst.,2020

4. A fast and elitist multiobjective genetic algorithm: NSGA-II

5. Data-driven algorithm for real-time fatigue life prediction of structures with stochastic parameters;Feng S.;Comput. Methods Appl. Mech. Eng.,2020

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