Review on automated condition assessment of pipelines with machine learning

Y Liu, Y Bao - Advanced Engineering Informatics, 2022 - Elsevier
Pipelines carrying energy products play vital roles in economic wealth and public safety, but
incidents continue occurring. Condition assessment of pipelines is essential to identify …

A novel pipeline leak detection approach independent of prior failure information

A Rai, JM Kim - Measurement, 2021 - Elsevier
Condition monitoring of pipelines is of importance to detect fluids leakage and associated
financial losses and accidents. Artificial intelligence (AI) techniques have been widely used …

Pipeline leak diagnosis based on leak-augmented scalograms and deep learning

MF Siddique, Z Ahmad, JM Kim - Engineering Applications of …, 2023 - Taylor & Francis
This paper proposes a new framework for leak diagnosis in pipelines using leak-augmented
scalograms and deep learning. Acoustic emission (AE) scalogram images obtained from the …

[HTML][HTML] Prediction of oil and gas pipeline failures through machine learning approaches: A systematic review

AM Al-Sabaeei, H Alhussian, SJ Abdulkadir… - Energy Reports, 2023 - Elsevier
Pipelines are vital for transporting oil and gas, but leaks can have serious consequences
such as fires, injuries, pollution, and property damage. Therefore, preserving pipeline …

An anomaly detection model for oil and gas pipelines using machine learning

SS Aljameel, DM Alomari, S Alismail, F Khawaher… - Computation, 2022 - mdpi.com
Detection of minor leaks in oil or gas pipelines is a critical and persistent problem in the oil
and gas industry. Many organisations have long relied on fixed hardware or manual …

Intelligent system for condition monitoring of underground pipelines

SK Sinha, MA Knight - Computer‐Aided Civil and Infrastructure …, 2004 - Wiley Online Library
Pipeline infrastructure is decaying at an accelerating rate due to reduced funding,
insufficient quality control resulting in poor installation, little or no inspection and …

Deeppipe: A semi-supervised learning for operating condition recognition of multi-product pipelines

J Zheng, J Du, Y Liang, Q Liao, Z Li, H Zhang… - Process Safety and …, 2021 - Elsevier
Intelligent operating monitoring of pipelines helps to detect anomalies in time to ensure
pipeline safe, reducing potential risk. However, the operating conditions of the multi-product …

Applications of machine learning in pipeline integrity management: A state-of-the-art review

A Rachman, T Zhang, RMC Ratnayake - International journal of pressure …, 2021 - Elsevier
Despite being considered the safest means to transport oil and gas, pipelines are
susceptible to degradation. Pipeline integrity management (PIM) is implemented to lower the …

Deeppipe: A deep-learning method for anomaly detection of multi-product pipelines

J Zheng, C Wang, Y Liang, Q Liao, Z Li, B Wang - Energy, 2022 - Elsevier
The multi-product pipeline is the main way of refined oil transportation to ensure the safety of
the energy supply. Considering that abnormal conditions of the pipeline will cause huge …

A review on pipeline integrity management utilizing in-line inspection data

M Xie, Z Tian - Engineering Failure Analysis, 2018 - Elsevier
Pipelines are widely used in transporting large quantities of oil and gas products over long
distances due to their safety, efficiency and low cost. Integrity is essential for reliable pipeline …