Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 160, Issue -, Pages -Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2021.107824
Keywords
Tensegrity; Structural health monitoring; Interacting filtering; Particle filter; Ensemble Kalman Filter
Categories
Funding
- Science & Engineering Research Board (SERB) , New Delhi, India [ECR/2018/001464]
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Tensegrities are a special type of truss structure where compression members float within a network of tension members. Over time, cables may lose their pre-stress and bars may buckle or corrode, affecting structural stiffness. Tensegrity structures can change their form and stiffness by altering member pre-stress upon loading, potentially masking the effect of damage.
Tensegrities form a special case of truss, wherein compression members (struts/bars) float within a network of tension members (cables). Tensegrities are characterized by the pres-ence of at least one infinitesimal mechanism stabilized with member pre-stress to ensure equilibrium. Over prolonged usage, the cables may lose their pre-stress while the bars may buckle, get damaged, or corrode, affecting the structural stiffness leading to change in the measured dynamic properties. Upon loading, a tensegrity structure may change its form through altering its member pre-stress affecting its global stiffness, even in the absence of damage. This can potentially mask the effect of damage leading to a false impression of tensegrity health. This poses the major challenge in tensegrity health monitoring espe-cially when the load is stochastic and unknown. Present study proposes an output-only time-domain method that makes use of tenseg-rity vibrational responses within a Bayesian filtering-based approach to monitor the tensegrity health in the presence of uncertainties due to ambient force, model inaccuracy, and measurement noise. For this, an interacting strategy combining Particle Filter (PF) and Ensemble Kalman Filter (EnKF) has been adopted (Interacting Particle-Ensemble Kalman Filter, IP-EnKF) in which the EnKF estimates the response states as ensembles while run-ning within a PF envelop that estimates a set of location-based health parameters as par-ticles. Furthermore, for a cheaper damage detection procedure, strain responses are used as measurements. The efficiency of the proposed methodology in terms of accuracy, compu-tational cost, and robustness against noise contamination has been demonstrated using numerical experiments performed on two tensegrity modules: a simplex tensegrity and an extended-octahedron tensegrity. (c) 2021 Elsevier Ltd. All rights reserved.
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