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 …

Adoption of big data analytics for energy pipeline condition assessment

M Hussain, T Zhang, M Seema - … Journal of Pressure Vessels and Piping, 2023 - Elsevier
Due to complexity, the oil and gas industry employs various sensors to collect data for
analysis to maintain the safety and integrity of pipelines and associated infrastructure. There …

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 …

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 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 …

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 …