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Structural Condition Monitoring with the Use of the Derivative-Free Nonlinear Kalman Filter

Structural Condition Monitoring with the Use of the Derivative-Free Nonlinear Kalman Filter
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Author(s): Gerasimos Rigatos (Unit of Industrial Automation, Industrial Systems Institute, Greece)and Argyris Soldatos (National Technical University of Athens, Greece)
Copyright: 2015
Pages: 31
Source title: Handbook of Research on Advancements in Robotics and Mechatronics
Source Author(s)/Editor(s): Maki K. Habib (The American University in Cairo, Egypt)
DOI: 10.4018/978-1-4666-7387-8.ch013

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Abstract

The chapter proposes structural condition monitoring for buildings and mechanical structures using a new nonlinear filtering method under the name Derivative-Free Nonlinear Kalman Filtering. The filter makes use of exact linearization of the structure's dynamical model in accordance to differential flatness theory and of an inverse transformation that enables one to obtain estimates for the state vector elements of the initial model. The response of the structure is compared to the response generated by the filter under the assumption of a damage-free model. Moreover, the filter provides estimates of the state vector elements of the structure, which cannot be directly measured, while it can also give estimates of unknown excitation inputs. By comparing the two signals, residuals sequences are generated. The statistical processing of the residuals provides an indication about the existence of parametric changes (damages) in the structure that otherwise could not have been detected.

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