Health error prediction and sensor topology optimization on a smart pressure vessel

John G. Michopoulos; Phillip W. Mast; Robert Badaliance; Lee W. Gause; Henry H. Chaskelis

doi:10.1117/12.209329

12 May 1995 Health error prediction and sensor topology optimization on a smart pressure vessel

John G. Michopoulos, Phillip W. Mast, Robert Badaliance, Lee W. Gause, Henry H. Chaskelis

Proceedings Volume 2447, Smart Structures and Materials 1995: Industrial and Commercial Applications of Smart Structures Technologies; (1995) https://doi.org/10.1117/12.209329
Event: Smart Structures and Materials '95, 1995, San Diego, CA, United States

Abstract

NRL's Mechanics of Materials Branch has developed a technology that facilitates sensor selection and placement within a composite structure. The Embedded Sensors for Smart Structures Simulator (ES⁴) is a tool that relates the output of a finite number of sensors to strain induced structural and material damage. This tool is based on the use of the dissipative part of the bulk nonlinear material behavior. The methodology used to identify this behavior will be briefly described in the present paper. This paper describes the role of strain measurements and their relation to sensor type and location, the conceptual framework of dissipated energy density as the metric employed for assessing material/structural performance. Emphasis is given on the utilization of dissipated energy density for estimating the error between the health of the structure as 'seen' by the sensors and the actual health of the structure. Useful applications of this difference are sensor placement optimization in the case of the design phase and confidence level measure for the case of an on board simulating capability.

Citation Download Citation

John G. Michopoulos, Phillip W. Mast, Robert Badaliance, Lee W. Gause, and Henry H. Chaskelis "Health error prediction and sensor topology optimization on a smart pressure vessel", Proc. SPIE 2447, Smart Structures and Materials 1995: Industrial and Commercial Applications of Smart Structures Technologies, (12 May 1995); https://doi.org/10.1117/12.209329

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