Pipeline leakage detection using acoustic emission and machine learning algorithms

N Ullah, Z Ahmed, JM Kim - Sensors, 2023 - mdpi.com
Pipelines play a significant role in liquid and gas resource distribution. Pipeline leaks,
however, result in severe consequences, such as wasted resources, risks to community …

Fatigue condition diagnosis of rolling bearing based on normalized balanced multiscale sample entropy

H Tan, S Xie, R Liu, J Cheng, K Jing - International Journal of Fatigue, 2023 - Elsevier
Rolling bearing is a key component of machinery, its fatigue failure will affect the reliability of
machinery. The bearing vibration signal has strong nonlinearity, resulting in weak fault …

Acoustic emission-based structural health prediction and monitoring: A comprehensive review

V Kumar, V Kumar, E Kalyan Kumar… - … Journal of Applied …, 2023 - World Scientific
In this paper, we report a detailed overview of non-destructive techniques, specifically
Acoustic emission, for structural health monitoring in engineering applications. The review …

Machine learning‐based approach for fatigue crack growth prediction using acoustic emission technique

M Chai, P Liu, Y He, Z Han, Q Duan… - Fatigue & Fracture of …, 2023 - Wiley Online Library
In this study, a general machine learning‐based approach is proposed for fatigue crack
growth rate (FCGR) prediction using multivariate acoustic emission (AE) online monitoring …

Study on crack classification criterion and failure evaluation index of red sandstone based on acoustic emission parameter analysis

J Li, S Lian, Y Huang, C Wang - Sustainability, 2022 - mdpi.com
The acoustic emission (AE) characteristics of rock during loading can reflect the law of crack
propagation and evolution in the rock. In order to study the fracture mode in the process of …

[HTML][HTML] Effect of grain structure on fatigue crack propagation behavior of 2024 aluminum alloy under different stress ratios

H Chen, S Liu, P Wang, X Wang, Z Liu, F Aldakheel - Materials & Design, 2024 - Elsevier
The fatigue load that a material experiences and its microstructure are important factors
influencing fatigue crack propagation behavior. This study employed laser scanning …

In situ monitoring of high-temperature creep damage in CrMoV high-strength structural steel using acoustic emission

M Chai, H Li, Z Tang, C Lai, Y Song, Z Zhang… - … and Building Materials, 2024 - Elsevier
The accurate detection and evaluation of creep damage in structural steel is essential for
ensuring the safety and reliability of high-temperature structures. In this work, the in situ …

Acoustic emission technology-based multifractal and unsupervised clustering on crack damage monitoring for low-carbon steel

J Huang, Z Zhang, B Zheng, R Qin, G Wen, W Cheng… - Measurement, 2023 - Elsevier
Structural crack damage caused by high-stress concentration and external alternating load
is characterized by imperceptible and low damage load, which makes online monitoring …

Fatigue crack growth prediction method based on machine learning model correction

X Fang, G Liu, H Wang, Y Xie, X Tian, D Leng, W Mu… - Ocean …, 2022 - Elsevier
At present, ML has become an effective method to solve the prediction problem of fatigue
crack growth. To reduce the inaccurate prediction caused by uncertain factors in crack …

Cyber–physical systems for high-performance machining of difficult to cut materials in I5. 0 era—A review

H Gohari, M Hassan, B Shi, A Sadek… - Sensors (Basel …, 2024 - pmc.ncbi.nlm.nih.gov
The fifth Industrial revolution (I5. 0) prioritizes resilience and sustainability, integrating
cognitive cyber-physical systems and advanced technologies to enhance machining …