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 …

Recognition of shear and tension signals based on acoustic emission parameters and waveform using machine learning methods

F Ren, C Zhu, Z Yuan, M Karakus, S Tang… - International Journal of …, 2023 - Elsevier
Acoustic emission (AE) technology is widely used to monitor the damage evolution of rock.
Identifying AE signals is crucial to reveal the rock cracking mechanism. The current tension …

Review on acoustic emission source location, damage recognition and lifetime prediction of fiber-reinforced composites

W Zhou, Z Pan, J Wang, S Qiao, L Ma, J Liu… - Journal of Materials …, 2023 - Springer
Acoustic emission technology is an effective nondestructive testing method for fiber-
reinforced composites, which can monitor the damage process in real time. The main …

Feature extraction, recognition, and classification of acoustic emission waveform signal of coal rock sample under uniaxial compression

ZW Ding, XF Li, X Huang, MB Wang, QB Tang… - International Journal of …, 2022 - Elsevier
In this study, based on Mel frequency cepstrum coefficient (MFCC) method, the AE signal
characteristics of coal and rock samples were extracted, and the stress state criterion based …

A new qualitative acoustic emission parameter based on Shannon's entropy for damage monitoring

M Chai, Z Zhang, Q Duan - Mechanical Systems and Signal Processing, 2018 - Elsevier
An important objective of acoustic emission (AE) non-destructive monitoring is to accurately
identify approaching critical damage and to avoid premature failure by means of the …

Achieving robust damage mode identification of adhesive composite joints for wind turbine blade using acoustic emission and machine learning

D Xu, PF Liu, ZP Chen, JX Leng, L Jiao - Composite Structures, 2020 - Elsevier
Interest in damage mode classification of composite structures by Acoustic Emission (AE)
inspection technique and clustering analysis by machine learning has been increasingly …

A new method for detecting fatigue crack initiation in aluminum alloy using acoustic emission waveform information entropy

SF Karimian, M Modarres, HA Bruck - Engineering fracture mechanics, 2020 - Elsevier
Sensitive structures, such as airframes, need careful inspection and maintenance to avoid
fatigue failures. These activities are expensive, discrete and imperfect, since catastrophic …

Damage mode identification of adhesive composite joints under hygrothermal environment using acoustic emission and machine learning

D Xu, PF Liu, JG Li, ZP Chen - Composite structures, 2019 - Elsevier
This paper studies the hygrothermal aging effect on the damage behaviors of adhesive
composite joints by acoustic emission (AE) technique. Tensile tests and AE tests are …

A Kaiser window-based S-transform for time-frequency analysis of power quality signals

C Liang, Z Teng, J Li, W Yao, S Hu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The accurate time-frequency (TF) positioning of power quality (PQ) disturbances is the basis
of dealing with PQ problems in power systems. To accurately detect PQ disturbances, this …

Structural health evaluation of the prestressed concrete using advanced acoustic emission (AE) parameters

G Ma, Q Du - Construction and Building Materials, 2020 - Elsevier
Acoustic emission (AE) is a promising technology for structural health monitoring to reduce
costs and improve performance but hard to interpret. This paper puts forward an advanced …