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Bio-inspired neuro-symbolic approach to diagnostics of structures

  • Shoureshi, Rahmat A. (Intelligent Systems Lab, School of Engineering & Computer Science, University of Denver) ;
  • Schantz, Tracy (Intelligent Systems Lab, School of Engineering & Computer Science, University of Denver) ;
  • Lim, Sun W. (Intelligent Systems Lab, School of Engineering & Computer Science, University of Denver)
  • Received : 2010.11.22
  • Accepted : 2010.11.26
  • Published : 2011.03.25

Abstract

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

Keywords

References

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