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21 July 2004 Use of fiber optic sensors and recurrence quantification analysis in detecting and localizing damage in a thin steel plate
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Abstract
A new algorithm is presented for detecting damage in structures subject to ambient or applied excitation. The approach is derived from an attractor-based technique for detecting nonstationarity in time series data and is referred to as recurrence quantification analysis (RQA). Time series data collected from the structure are used to reconstruct the system's dynamical attractor in phase space. The practitioner then quantifies the probabilities that a given trajectory will visit local regions in this phase space. This is accomplished by forming a binary matrix consisting of all points that fall within some predefined radius of each point on the attractor. The resulting recurrence plot reflects correlations in the time series across all available time scales in a probabilistic fashion. Based on the structure found in recurrence plots a variety of metrics are extracted including: percentage of recurrence points, a measure reflecting determinism, and entropy. These "features" are then used to detect and track damage-induced changes to the structure's vibrational response. The approach is demonstrated experimentally in diagnosing the length of a crack in a thin steel plate. Structural response data are recorded from multiple locations on the plate using a novel fiber-based sensing system.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jonathan M. Nichols, Stephen T. Trickey, and Mark Seaver "Use of fiber optic sensors and recurrence quantification analysis in detecting and localizing damage in a thin steel plate", Proc. SPIE 5394, Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems III, (21 July 2004); https://doi.org/10.1117/12.539954
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