Methodology and GUI for NDE/SHM using Two-Stage Compressive Sensing


Reference #: 01579

The University of South Carolina is offering licensing opportunities for Methodology and GUI for NDE/SHM using Two-Stage Compressive Sensing


Compressive Sensing has been shown to greatly reduce data acquisition and processing burdens by providing mathematical guarantees for accurate signal recovery from far fewer samples than conventionally needed. NASA is developing new vehicles for human space flight. Many of these spacecraft are targeted for long-term use, which offers challenges for inspection and maintenance.

Invention Description:

The purpose of the innovation is to reduce data acquisition processes and data storage burdens for NDE/SHM systems while maintaining the ability to accurately detect, locate, and characterize structural damage. The methodology uses Compressive Sensing to reconstruct data at two stages in the data acquisition and analysis process to detect damage and generate a diagnostic image of the structure

Potential Applications:

It is anticipated that the first application of the technology will be the integration into NASA’s inspection tools for large complex space structures made with composites or thin metals.

Potential commercial customers include Boeing, Blue Origin, GE Aviation, and SpaceX. Other non-NASA applications and industries include aerospace (aircraft wings and fuselage), marine (ship hulls), wind energy (rotor blades), railways, civil infrastructure (buildings and bridges), oil and gas (pipelines), etc. Generally, any industry that uses large structures that require frequent inspection will benefit from the use of the Compressive Sensing technology.

Advantages and Benefits:

Novel features of the innovation include: (1) the ability to generate basis functions needed for Compressive Sensing, (2) the ability to reconstruct temporally under sampled sensor signals from different types of NDE/SHM techniques, (3) the ability to reconstruct parameters from spatially under sampled actuator-sensor paths and/or pixels from images, (4) the ability to generate diagnostic images from the reconstructed data in both time and space, (5) the ability to import and analyze sensor signals from various NDE/SHM techniques and in various data formats, and (6) the ability to quantify the signal/image reconstructions through the use of correlation coefficients and probability-of-detection curves. The advantages of the innovation are the reduction in data acquisition processes and storage, and the potential to reduce the number of required sensors and the total weight of NDE/SHM systems.


Patent Information:
For Information, Contact:
Technology Commercialization
University of South Carolina
Sourav Banerjee
Mustahseen Indaleeb
Shawn Beard
Ritubarna Banerjee
Compressive Sensing
Data Features
Data Reduction
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