Fingerprints of Fatigue Crack Generated Acoustic Emission Waveforms


Reference #: 01286

The University of South Carolina is offering licensing opportunities for identifying fatigue crack-generated acoustic emission waveforms.



Acoustic emissions (AE) waves are generated by a sudden redistribution of stress in a material or structure. AE techniques have many industrial applications, such as assessing structural integrity, detecting flaws, testing for leaks, or monitoring weld quality, and is used extensively as a research tool.


Invention Description:

The original fingerprints of the fatigue crack generated acoustic emission waveforms are identified. These fingerprints were used as a standard to distinguish the crack-generated and the non-crack generated acoustic AE signals. Each fingerprint had a particular time-domain signal pattern and unique frequency spectrum. It was found that the huge amount of fatigue crack generated AE hits can be sorted very nicely and efficiently into few groups based on these fingerprints, explaining the complex fatigue crack growth mechanisms which would enable proper fatigue damage monitoring solutions for the safety of public infrastructures.


Potential Applications:

Potential industrial applications are those which use nondestructive evaluation (NDE) and structural health monitoring (SHM) techniques for monitoring structural integrity using acoustic emissions. These include:

•       Mechanical engineering (progressive damage and fracture analysis of the mechanical components)

•       Aerospace industry (Unmanned aerial vehicle (UAV), aircraft structural monitoring)

•       Civil engineering (bridges, buildings, transportation systems, etc.)

•       Energy infrastructures (wind turbines, nuclear applications, pipelines, offshore, etc.)

•       National security (surveillance drone for anti-warfare, anti-terrorism, etc.)

•       Manufacturing quality control (acoustic emission monitoring during manufacturing)


Advantages and Benefits:

This invention is expected to be a highly efficient way of acoustic emission (AE) signal analysis than the existing methods. This is also expected to bring a significant improvement in the AE technology by distinguishing the unnecessary data from a huge amount of AE experimental data, providing a competitive advantage.


Patent Information:
For Information, Contact:
Technology Commercialization
University of South Carolina
Victor Giurgiutiu
Yeasin Bhuiyan
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