N.C. A&T grant of the month: Monitoring strucutral integrity of armor, weapons

U.S. Army logoThe Sponsored Funding Report for June:

N.C. A&T received 23 grants totaling $17.19 million in June.

The complete list of grants received in June.

One highlight was a grant worth $616,956 from the Army Research Office to Dr. Mannur Sundaresan of the Department of Mechanical Engineering.  Dr. Albert Esterline of the Department of Computer Science also will work on the project.

The project: Prognostic Health Management of DoD Assets

The issue: Acoustic emission-based structural health monitoring techniques have great potential for determining the current state of health of critical structures, such as Army vehicles and weapons systems, and predicting their future performance.  However, current technology relies mostly on empirical approaches for interpreting AE signals, a technique that has been plagued by ambiguity and false positives.

With a better understanding of the physics of acoustic emission (AE) signal propagation and the development of signal processing techniques, AE-based techniques can play a larger role in developing highly efficient, adaptive, and survivable vehicles, armor, and machinery and the assurance of their safety and integrity.

Abstract:  This research will develop numerical models, experiments, algorithms, web architectures, and other tools applicable to prognostic health management. The research will address identification of critical damage states in composite structural elements and strategies for sensing such states with multiple sensors.

The mechanics aspect of this proposal will focus on the basic understanding of stress wave generation and propagation in heterogeneous media, including composite materials; developing signal processing techniques to extract features related to the physics of the source mechanisms and propagation path; and developing an understanding of features related to false positives. The work also will examine embedded PZT and fiber optic sensors for monitoring static strain as well as acoustic emission signals. Computer science topics such as data fusion, multiagent systems, and sensor web will be developed for prognostic health management.  The Structural Health Monitoring Laboratory N.C. A&T will be upgraded with fiber optic strain and acoustic emission measurement instrumentation.

This work will build on results previously obtained by this group, mostly under the support of a prior Army grant, that have paved the way for more reliable structural health monitoring techniques grounded in physics-based quantitative interpretation of AE signals. Advances have been made in key areas including calibrating and quantifying AE sensor performance in the context of the different types of damage-related AE signals; identification of a key component of AE signals unrecognized in past AE literature; development of novel sensors with increased sensitivity; quantitative understanding of AE signals generated by frictional process, a key source of false positives in AE signals; development of a physics-based procedure for classifying and quantifying AE signals; and life prediction and life extension of impact-damaged composite specimens.

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