Metal parts have recently been substituted with composite in the transport industry due to their characteristics, which include increased strength, stiffness and reduced weight. Acoustoultrasonics is an inspection technique, which combines the acoustic emission methodology with ultrasonic simulation of stress waves to assess defect states in materials. Acousto-ultrasonics belong to the family of inspection tools, which emerge to identify and measure occurred damage or decay state of transportation modes and infrastructure. In this paper, we attempt to detect defects by performing initial experiments with composite specimens. Specifically, the attenuation of simulated acoustic emission events are measured aiming to further investigate the phenomenon of edge reflections from small composite specimens. Also, only two features from the signal can be used to detect two different types of faults. Finally, a new triangular-like larger specimen is introduced and assessed using the two sensors, in order to show the difference of the two aforementioned features when two different material and dimension specimens are used.
Recently, the transport industry has been substituting metal with composite parts due to their properties, such as increased strength, stiffness and lightweightness. Inspection and monitoring are very important tools that detect, identify and measure occurred damage or deterioration state of transport means and infrastructure. Acousto-ultrasonics is an non-destructive testing technique, which is essentially a combination of acoustic emission methodology with ultrasonic simulation of stress waves to assess defect states in certain materials. In this paper, we perform initial experiments with composite specimens, attempting to detect defects. In particular, the attenuation of simulated acoustic emission events are measured in order to further investigate the phenomenon of edge reflections from small composite specimens. Furthermore, the detection of two different types of defects is shown using only two features extracted from the signal.
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