Journal Article10.1106/GVD2-EGPN-C5B1-DPNX
Sensor Validation for Smart Structures
101
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, because there will be 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 be 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, because there will be 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.
968
Mechanical systems and signal processing
ScienceDirect
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TL;DR: Vehicle system dynamics integration encompasses interdisciplinary challenges innovations in various aspects related to vehicle system/subsystems/components dynamic characteristics, modeling and validation, vehicle dynamics state measurement and estimation, vehicle/chassis control systems, coordination of power management and dynamics/stability control, etc.
925
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.
559
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.
Performance assessment and validation of piezoelectric active-sensors in structural health monitoring
TL;DR: A sensor diagnostics and validation process that performs in situ monitoring of the operational status of piezoelectric active-sensors in structural health monitoring (SHM) applications is presented in this article.
285
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