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Proceedings Paper

Integrated material state awareness system with self-learning symbiotic diagnostic algorithms and models
Author(s): Sourav Banerjee; Lie Liu; S. T. Liu; Fuh-Gwo Yuan; Shawn Beard
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Paper Abstract

Materials State Awareness (MSA) goes beyond traditional NDE and SHM in its challenge to characterize the current state of material damage before the onset of macro-damage such as cracks. A highly reliable, minimally invasive system for MSA of Aerospace Structures, Naval structures as well as next generation space systems is critically needed. Development of such a system will require a reliable SHM system that can detect the onset of damage well before the flaw grows to a critical size. Therefore, it is important to develop an integrated SHM system that not only detects macroscale damages in the structures but also provides an early indication of flaw precursors and microdamages. The early warning for flaw precursors and their evolution provided by an SHM system can then be used to define remedial strategies before the structural damage leads to failure, and significantly improve the safety and reliability of the structures. Thus, in this article a preliminary concept of developing the Hybrid Distributed Sensor Network Integrated with Self-learning Symbiotic Diagnostic Algorithms and Models to accurately and reliably detect the precursors to damages that occur to the structure are discussed. Experiments conducted in a laboratory environment shows potential of the proposed technique.

Paper Details

Date Published: 1 April 2011
PDF: 12 pages
Proc. SPIE 7984, Health Monitoring of Structural and Biological Systems 2011, 79840M (1 April 2011); doi: 10.1117/12.880511
Show Author Affiliations
Sourav Banerjee, Acellent Technologies, Inc. (United States)
Lie Liu, North Carolina State Univ. (United States)
S. T. Liu, North Carolina State Univ. (United States)
Fuh-Gwo Yuan, North Carolina State Univ. (United States)
Shawn Beard, Acellent Technologies, Inc. (United States)


Published in SPIE Proceedings Vol. 7984:
Health Monitoring of Structural and Biological Systems 2011
Tribikram Kundu, Editor(s)

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