State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass ﬁber reinforced polyester composite (GFRP) using acoustic emission

QR Code

State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass ﬁber reinforced polyester composite (GFRP) using acoustic emission

Fatigue strength is one of the most important properties of composite materials because it directly relates to their lifespan. Acoustic emission (AE) is a passive structural health monitoring (SHM) technique that provides real-time damage detection based on stress waves generated by cracks in the st...

Full description

Bibliographic Details
Main Authors:	Gholizadeh, S., Leman, Z., Baharudin, B.T.H.T.
Format:	Article
Published:	Elsevier 2023
Online Access:	http://psasir.upm.edu.my/id/eprint/109502/

Similar Items

Glass fiber-reinforced polyester composite fatigue crack monitoring using acoustic emission
by: Gholizadeh, Samira
Published: (2015)

Acoustic Emission Study Of Fatigue Crack Growth In Rail Track Material
by: Mohd Yusof, Taib
Published: (2010)

A review of the application of acoustic emission technique in engineering
by: Gholizadeh, Somayyeh, et al.
Published: (2015)

Effect of fabric biaxial prestress on the fatigue of woven E-glass/polyester composites
by: Haider, Nawras Haidar Mostafa Meir Al-Said, et al.
Published: (2016)

Unsupervised learning of facial expression components
by: Egede, Joy Onyekachukwu
Published: (2013)

Acoustic emission behavior during fatigue crack of API5LX70 gas pipeline steel
by: Mohd Fadhlan, Mohd Yusof, et al.
Published: (2011)

Unsupervised ensemble Kalman filtering with an uncertain constraint for land hydrological data assimilation
by: Khaki, Mehdi, et al.
Published: (2018)

Effect of ply lay-up and curing pressure on void content in GFRP laminates of unsaturated polyester resin-reinforced woven E-glass fibers
by: Yeo, Kiam Beng, et al.
Published: (2017)

Challenges in supervised and unsupervised learning: a comprehensive overview
by: Almuqati, Mohammed Tuays, et al.
Published: (2024)

Ensemble-based machine learning models for vehicle drivers’ fatigue state detection utilizing EEG signals
by: Hasan, Md Mahmudul, et al.
Published: (2024)

Fatigue Crack Growth Analysis of Semielliptical Surface Crack
by: M. R. M., Akramin, et al.
Published: (2014)

Crack detection of ceramic tile using acoustic emission
by: Sarkawi, Buang.
Published: (2005)

Comparison of supervised and unsupervised learning classifiers for human posture recognition
by: Htike, Kyaw Kyaw, et al.
Published: (2010)

Unsupervised process monitoring and fault diagnoses with machine learning methods
by: Aldrich, Chris, et al.
Published: (2013)

Unsupervised Fertigation and Machine Learning for Crop Vegetation Parameter Analysis
by: Mohd Izzat, Mohd Rahman, et al.
Published: (2023)

Modelling kernel methods for unsupervised learning of micro array data
by: Md. Sap, Mohd. Noor
Published: (2008)

Ensemble learning for multidimensional poverty classification
by: Azuraliza Abu Bakar,, et al.
Published: (2020)

Ensemble deep learning for tuberculosis detection
by: Ahmad Hijazi, Mohd Hanafi, et al.
Published: (2020)

Bending behaviour of timber beams strengthened with glass fibre reinforced polymer (GFRP)
by: Erma Suryati Sabariah, Md Ali
Published: (2014)

Effect of various conditions on adhesively bonded glass fiber reinforced plastic (GFRP)
by: Lim, Anthony Wee Liang.
Published: (2008)

Acoustic emission assessment of interface cracking in thermal barrier coatings
by: Yang, L., et al.
Published: (2016)

Fatigue cracking of bituminous paving mixtures
by: Read, John
Published: (1996)

Trajectory Ensembles and Machine Learning: From reinforcement learning for rare event sampling to training of neural network ensembles
by: Mair, Jamie
Published: (2023)

Exploring Accounting Research Topic Evolution: An Unsupervised Machine Learning Approach
by: Cao, June, et al.
Published: (2023)

Unsupervised learning algorithm for adaptive group formation: Collaborative learning support in remotely accessible laboratories
by: Mujkanovic, A., et al.
Published: (2012)

Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms
by: Agrawal, Utkarsh, et al.
Published: (2018)

Degradation of glass fibre reinforced polymer (GFRP) composite subjected to different environmental conditions
by: Mousay, Mohammed Mousay
Published: (2022)

Degradation of glass fiber reinforced polymer (GFRP) material exposed to tropical atmospheric condition
by: Mousay, Mohammed, et al.
Published: (2021)

Fatigue Failure Assessment of Metallic Specimens using the Acoustic Emission Technique.
by: Inayatullah, Othman, et al.
Published: (2013)

Cracking behaviour of coal ash concrete based on acoustic emission technique
by: Abdul Muiz, Hasim
Published: (2023)

Ensemble learning of colorectal cancer survival rates
by: Roadknight, Chris, et al.
Published: (2013)

Micro mechanism of fatigue cracking in asphalt concrete
by: Chen, An-Qi
Published: (2022)

Fatigue Crack Propagation in Aluminium 6063 Tubes
by: Oshkour, Azim Ataollahi
Published: (2009)

Unsupervised online constructed-response tests: Maximising student learning and results integrity
by: Johnson, Genevieve, et al.
Published: (2012)

Investigation On The Mechanical Properties Of Glass Fiber Reinforced Polymer (Gfrp) Hybrid Composite With Eggshell Powder
by: Lee, Jie Shin
Published: (2019)

Effects Of Plastering And Glass Fibre Reinforced Polymer (Gfrp) On Concrete Masonry Prism Strength Capacity
by: Ismail, Mohammad Fikri
Published: (2017)

Investigation On The Mechanical Properties Of Glass Fiber Reinforced Polymer (Gfrp) Hybrid Composite With Eggshell Powder
by: Lee, Jie Shin
Published: (2019)

Quantitative relationship between strain and acoustic emission response in monitoring fatigue damage
by: Mohammad, Mazian, et al.
Published: (2014)

Identifying the Crack Nature Using b-Value Acoustic Emission Signal Analysis
by: Saiful Bahari, Miera, et al.
Published: (2020)

Finite element based fatigue crack growth of cracked plates under axial loading
by: Mohamad Abiddullah, Mohd Lasim
Published: (2010)