Proceedings Article10.1117/12.396393
Sensor validation for smart structures
Michael I. Friswell,Daniel J. Inman +1 more
- 24 Aug 2000
- Vol. 4073, pp 150-161
TL;DR: This paper considers possible approaches to sensor validation, based on the assumption that a model of the structure is available, and makes use of the natural data redundancy since there will more sensors than modes in the data.
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Abstract: Structures with a large number of embedded sensors are becoming more common, and this refined spatial information can be used to advantage in damage location and model validation. These sensors could be accelerometers, strain gauges, piezoceramic patches, PVDF film sensors, or optical fibre sensors. This approach requires that the sensors are functioning correctly, which on a smart structure operating in the field should be continuous and automatically monitored. This paper considers possible approaches to sensor validation, based on the assumption that a model of the structure is available. The aim is to make use of the natural data redundancy since there will more sensors than modes in the data. The validation approaches considered are based on hypothesis testing based on a number of techniques, such as modal filtering. The methods are demonstrated on simple examples that exercise their strengths and weaknesses.
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Citations
The Method of Proper Orthogonal Decomposition for Dynamical Characterization and Order Reduction of Mechanical Systems: An Overview
Gaëtan Kerschen,Gaëtan Kerschen,Gaëtan Kerschen,Jean Claude Golinval,Alexander F. Vakakis,Alexander F. Vakakis,Lawrence A. Bergman +6 more
TL;DR: In this article, a different approach is adopted, and proper orthogonal decomposition is considered, and modes extracted from the decomposition may serve two purposes, namely order reduction by projecting high-dimensional data into a lower-dimensional space and feature extraction by revealing relevant but unexpected structure hidden in the data.
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Structural damage diagnosis under varying environmental conditions—Part I: A linear analysis
TL;DR: In this paper, a damage detection method based on principal component analysis (PCA) applied to vibration features identified during the monitoring of the structure is proposed for structural health monitoring under varying environmental and operational conditions.
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Damage identification using inverse methods
TL;DR: A number of problems that exist with the use of inverse methods in damage detection and location, including modelling error, environmental effects, damage localization and regularization are discussed.
Sensor validation using principal component analysis
TL;DR: In this paper, the authors present a procedure based on principal component analysis which is able to perform detection, isolation and reconstruction of a faulty sensor, which is assessed using an experimental application.
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Null subspace-based damage detection of structures using vibration measurements
Ai-Min Yan,Jean-Claude Golinval +1 more
TL;DR: In this article, a damage detection method of mechanical system based on subspace identification concepts and statistical process techniques is presented, where measured time-responses of structures subjected to artificial or environmental vibrations are assembled to form the Hankel matrix, which is further factorised by performing singular value decomposition to obtain characteristic subspaces.
122
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