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Abstract
This paper describes the formulation of a maximum-likelihood estimate of damage location for guided-wave structural health monitoring (GWSHM) using a minimally informed, Rayleigh-based statistical model of scattered wave measurements. Also introduced are two statistics-based methods for evaluating localization performance: the localization probability density function estimate and the localizer operating characteristic curve. Using an ensemble of measurements from an instrumented plate with stiffening stringers, the statistical performance of the so-called Rayleigh maximum-likelihood estimate (RMLE) is compared with that of seven previously reported localization methods. The RMLE proves superior in all test cases, and is particularly effective in localizing damage using very sparse arrays consisting of as few as three transducers. The probabilistic basis used for modelling the complicated wave scattering behaviour makes the algorithm especially suited for localizing damage in complicated structures, with the potential for improved performance with increasing structure complexity.
Original language | English |
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Pages (from-to) | 2575-2596 |
Number of pages | 22 |
Journal | Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences |
Volume | 467 |
Issue number | 2133 |
DOIs | |
Publication status | Published - 8 Sept 2011 |
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Dive into the research topics of 'Maximum-likelihood estimation of damage location in guided-wave structural health monitoring'. Together they form a unique fingerprint.Projects
- 1 Finished
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EFFICIENT STRUCTURAL HEALTH MONITORING USING SPARSE DISTRIBUTED SENSOR ARRAYS
1/01/06 → 1/07/09
Project: Research