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

• 主要な著者: Gholizadeh, S., Leman, Z., Baharudin, B.T.H.T.
• フォーマット: 論文
• 出版事項: Elsevier 2023
• オンライン･アクセス: http://psasir.upm.edu.my/id/eprint/109502/; https://linkinghub.elsevier.com/retrieve/pii/S0041624X23000744

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...