A theoretical framework for sensor placement, structural identification and damage detection in tensegrity structures

Abstract

Tensegrity structures are systems composed of elements in compression and tension in a stable self-equilibrium state that provides stability and stiffness to the structure. Tensegrity finds its root in contemporary art with Kenneth Snelson's sculptures, yet it quickly evolved into a structural paradigm employed in a wide spectrum of science and engineering applications. Tensegrity structures being lightweight, and capable of combining sensors and actuators with structural elements, they are advantageous for active applications. However, in most active applications, sensor placement is based on engineering judgement and not a systematic approach based on the analysis of tensegrity structures. This paper addresses sensor placement for structural identification and damage detection in tensegrity structures using cellular decomposition. By decomposing tensegrity structures into the minimum number of constitutive unicellular sub-structures (cells and stable sub-structures resulting from their interaction), the minimum number of sensors required for their self-stress identification can be defined along with a set of edge solutions for sensor placement. Moreover, under the assumptions of a known deformed geometry and loading, it is shown that the resulting sensor configurations can be extended for structural identification as well as damage detection providing a theoretical framework for active and sensory tensegrity structures based on their cellular composition.