Medical University of South Carolina

Intelligent Automation, Inc.

Banibrata Poddar

Victor Giurgiutiu

Jingjing Bao

Md Yeasin Bhuiyan

Mohammad Faisal Haider

The current disclosure determines if structural faults exist and extracts geometric features of the structural faults from acoustic emission waveforms, such as crack length and orientation, and can evaluate the structural faults online, during normal operation conditions.

Identifying structural defect geometric features from acoustic emission waveforms

Computationally efficient, highly accurate, and cost-effective approach for detection of damage in a structure is described. Methods include a combined analysis in both global and local regions of a structure to predict the received wave signals at a location due to scattering of Lamb waves at a damage site. Through comparison of an actual received wave signal with the predicted signals, identification of damage location and/or type can be provided. Methods can be particularly beneficial when considering damage assessment in a complex structure that includes plate-like structures that include an extension off of a base plate, e.g., a stiffened structure.

Growing community of inventors

Rockville, MD, United States of America

Banibrata Poddar