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Acoustic emission detection of fatigue damage in cruciform welded joints
Abstract Weld seams are critical points for the initiation of fatigue cracks in steel structures subjected to cyclic loads. Semi-elliptical surface cracking at the toes of a fillet weld is not easily found when it is partially through the thickness and subcritical. In this study the acoustic emission (AE) method is used to detect crack propagation in cruciform fillet welded joints that are representative of typical fatigue sensitive details in steel bridge superstructures. The effect of geometry and fatigue load on the AE data is investigated by varying the width of the base plate and the stress ratio. AE data filtering based on load pattern, source location, and waveform feature analysis was implemented to minimize noise-induced AE signals and false indications due to wave reflections. AE time domain features such as amplitude (b-value), counts, signal strength, and absolute energy are employed to study the influence of geometry and fatigue load on the AE data.
Highlights A combined approach for acoustic emission (AE) data filtering is presented. AE of fatigue cracks in cruciform welded joints is characterized. The effect of geometry and fatigue load on the AE is investigated. Active fatigue cracks with higher load ratio lead to stronger AE. The AE intensity is not affected by the width of the welded joints.
Acoustic emission detection of fatigue damage in cruciform welded joints
Abstract Weld seams are critical points for the initiation of fatigue cracks in steel structures subjected to cyclic loads. Semi-elliptical surface cracking at the toes of a fillet weld is not easily found when it is partially through the thickness and subcritical. In this study the acoustic emission (AE) method is used to detect crack propagation in cruciform fillet welded joints that are representative of typical fatigue sensitive details in steel bridge superstructures. The effect of geometry and fatigue load on the AE data is investigated by varying the width of the base plate and the stress ratio. AE data filtering based on load pattern, source location, and waveform feature analysis was implemented to minimize noise-induced AE signals and false indications due to wave reflections. AE time domain features such as amplitude (b-value), counts, signal strength, and absolute energy are employed to study the influence of geometry and fatigue load on the AE data.
Highlights A combined approach for acoustic emission (AE) data filtering is presented. AE of fatigue cracks in cruciform welded joints is characterized. The effect of geometry and fatigue load on the AE is investigated. Active fatigue cracks with higher load ratio lead to stronger AE. The AE intensity is not affected by the width of the welded joints.
Acoustic emission detection of fatigue damage in cruciform welded joints
Yu, Jianguo (author) / Ziehl, Paul (author) / Matta, Fabio (author) / Pollock, Adrian (author)
Journal of Constructional Steel Research ; 86 ; 85-91
2013-03-28
7 pages
Article (Journal)
Electronic Resource
English
Acoustic emission detection of fatigue damage in cruciform welded joints
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