Paper
14 November 2002 Early detection of local buckling in composite bars
Author Affiliations +
Proceedings Volume 4935, Smart Structures, Devices, and Systems; (2002) https://doi.org/10.1117/12.476126
Event: SPIE's International Symposium on Smart Materials, Nano-, and Micro- Smart Systems, 2002, Melbourne, Australia
Abstract
Most structural health monitoring analyses to date have focused on the determination of damage in the form of crack growth in metallic materials or delamination or other types of damage growth in composite materials. However, in many applications local instability in the form of buckling can be the precursor to more extensive damage and unstable failure of the structure. If buckling could be detected in the very early stages, there is a possibility of taking preventive measures to stabilize and save the structure. Relatively few investigations have addressed this type of damage initiation in structures. Recently, during the structural health monitoring of wind turbine blades, local buckling was identified as the cause of premature failure. Results from this investigation suggested that stress waves could be used for detecting the early signs of change in the local curvature that precedes buckling type of failure in this structure. These conditions have been replicated in the laboratory and detailed investigation on the ability of low frequency vibrations to detect the buckling displacement has been carried out. The experiment was performed on a composite bar. The results clearly show that low frequency vibrations could be used to detect the onset of buckling in which the local deflection is only of the order of 0.25 inches.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mannur J. Sundaresan, Bashir Ali, Frederick Ferguson, and Mark J. Schulz "Early detection of local buckling in composite bars", Proc. SPIE 4935, Smart Structures, Devices, and Systems, (14 November 2002); https://doi.org/10.1117/12.476126
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KEYWORDS
Composites

Wind turbine technology

Ferroelectric materials

Sensors

Structural health monitoring

Actuators

Receivers

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