Detection of the pipeline elbow erosion by percussion and deep learning

J Chen, L Cao, G Song - Mechanical Systems and Signal Processing, 2023 - Elsevier
Elbows are commonly used in pipelines to change the direction of flow, and the pipeline
elbows are prone to erosion caused by the transported medium. Detection of the pipeline …

One-dimensional residual convolutional neural network and percussion-based method for pipeline leakage and water deposit detection

L Peng, J Zhang, S Lu, Y Li, G Du - Process Safety and Environmental …, 2023 - Elsevier
Pipeline leakage and water deposits can cause serious consequences, such as
environmental pollution, safety accidents, and economic losses. Therefore, effective …

A CNN-based transfer learning method for leakage detection of pipeline under multiple working conditions with AE signals

P Liu, C Xu, J Xie, M Fu, Y Chen, Z Liu… - Process Safety and …, 2023 - Elsevier
Pipeline leakage detection is a crucial part of pipeline integrity management. Acoustic
emission (AE) based leakage detection is widely used in this field. The latest detection …

Leakage detection in water pipelines using supervised classification of acceleration signals

H Shukla, K Piratla - Automation in Construction, 2020 - Elsevier
Loss of treated water through buried pipeline leakage is one of the pressing challenges
faced by water utilities across the world. Many current pipeline inspection techniques are ad …

An exploration on the machine learning approaches to determine the erosion rates for liquid hydrocarbon transmission pipelines towards safer and cleaner …

G Liu, F Ayello, J Vera, R Eckert, P Bhat - Journal of Cleaner Production, 2021 - Elsevier
Erosion is commonly found in pipelines with existence of interactions between solid
particles, fluid product transported and the surrounding materials. Erosion may lead to …

Solid particle erosion prediction in elbows based on machine learning and swarm intelligence algorithm

Z Wang, H Chen, M Wang, X Zhang, Y Dou - Journal of Petroleum Science …, 2022 - Elsevier
Continuous impact of solid particles causes severe pipeline wear, and may result in leakage
in directional change areas such as elbows. Accurate prediction of erosion is essential in the …

Time-frequency distribution map-based convolutional neural network (CNN) model for underwater pipeline leakage detection using acoustic signals

Y Xie, Y Xiao, X Liu, G Liu, W Jiang, J Qin - Sensors, 2020 - mdpi.com
Detection technology of underwater pipeline leakage plays an important role in the subsea
production system. In this paper, a new method based on the acoustic leak signal collected …

Performance prediction of erosion in elbows for slurry flow under high internal pressure

S Yang, J Fan, L Zhang, B Sun - Tribology International, 2021 - Elsevier
Slurry erosion is an important cause of material failure in the oil and gas industry.
Particularly, during hydraulic fracturing, the fracturing pipelines under high internal pressure …

A Hybrid Deep Learning Approach: Integrating Short-Time Fourier Transform and Continuous Wavelet Transform for Improved Pipeline Leak Detection

MF Siddique, Z Ahmad, N Ullah, J Kim - Sensors, 2023 - mdpi.com
A hybrid deep learning approach was designed that combines deep learning with enhanced
short-time Fourier transform (STFT) spectrograms and continuous wavelet transform (CWT) …

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 …