1,721,029 research outputs found
STRUCTURAL DAMAGE LOCALIZATION UNDER VARYING ENVIRONMENTAL CONDITIONS
No full textStructural condition assessment by means of structural health monitoring has in recent years evolved into an actionable practice. For diagnosing structural health, a number of damage detection methods have been proposed, relying on vibration response data, for extraction of features that are characteristic of the intact or unsound structure. In this context, environmental variation comprises a severe challenge, since it induces deviations in the measured structural vibration characteristics, often masking the changes induced by damage. This work offers a remedy to this issue by adoption a Principal Component Analysis (PCA) based approach to account for variations induced from environmental condition variation and separate these from contributions corresponding to damage. Beyond mere detection, the proposed framework offers the possibility for localizing damage
On the use of mode shape curvatures for damage localization under varying environmental conditions
Full text linkA novel damage localization method is introduced in this study, which exploits mode shape curvatures as damage features, while accounting for operational variability. The developed framework operates in an output-only regime,that is, it does not assume availability of records from the influencing environmental/operational quantities but rather from response quantities alone. The introduced tool comprises 3 stages pertaining to training, validation, and diagnostics. During the training stage, a representation of the healthy, or baseline, structural state is acquired over varying operational conditions. A data matrix is formulated, whose individual columns correspond to mode shape curvatures at distinct operational conditions, and principal component analysis (PCA) is applied for extraction of the imprints of separate operational sources on these curvatures. To this end, a residual matrix between the original and the PCA mapped data is formed serving for statistical characterization of each mode. Subsequently, during the validation and diagnostics stages, the mode shape curvature matrices for the currently inspected structural state are assembled and the same PCA mapping is enforced. A typical hypothesis test and a corresponding damage index are then adopted in order to firstly detect damage, and to secondly localize damage, should this exist. The implementation of the proposed method in 2 numerical case studies confirms its effectiveness and the encouraging results suggest further investigation on operating structural systems
A Model-Based Bayesian Inference Approach for On-Board Monitoring of Rail Roughness Profiles: Application on Field Measurement Data of the Swiss Federal Railways Network
Full text linkISSN:1545-2255ISSN:1545-2263ISSN:1545-226
Locally Resonant Metasurfaces for Shear Waves in Granular Media
No full textIn this paper, the physics of horizontally polarized shear waves traveling across a locally resonant
metasurface in an unconsolidated granular medium is experimentally and numerically explored. The metasurface
is comprised of an arrangement of subwavelength horizontal mechanical resonators embedded in
a granular layer made of silica microbeads. The metasurface supports a frequency-tailorable attenuation
zone induced by the translational mode of the resonators. The experimental and numerical findings reveal
that the metasurface not only backscatters part of the energy but also redirects the wave front underneath
the resonators, leading to a considerable amplitude attenuation at the surface level, when all the resonators
have similar resonant frequency. A more complex picture emerges when using resonators arranged in a
so-called graded design, e.g., with a resonant frequency increasing or decreasing throughout the metasurface.
Unlike the mechanism observed in a bilayered medium, shear waves localized at the surface of the
granular material are not converted into bulk waves. Although a detachment from the surface occurs, the
depth-dependent velocity profile of the granular medium prevents the mode conversion and the horizontally
polarized shear wave front returns to the surface. The outcomes of our experimental and numerical
studies allow for understanding the dynamics of wave propagation in resonant metamaterials embedded
in vertically inhomogeneous soils and, therefore, may be valuable for improving the design of engineered
devices for ground-vibration and seismic wave containment
Output-error state-space identification of vibrating structures using evolution strategies: A benchmark study
No full textIn this study, four widely accepted and used variants of Evolution Strategies (ES) are adapted and applied to the output-error state- spaceidentification problem. The selection of ES is justified by prior strong indication of superior performance to similar problems, over alternatives like Genetic Algorithms (GA) or Evolutionary Programming (EP). The ES variants that are being tested are (i) the (1+1)-ES, (ii) the (μ/δ+λ;)-SA-ES, (iii) the (μδ,λ)-SA-ES, and (iv) the (μw,λ)-CMA-ES. The study is based on asix-degree-of-freedom (DOF) structural model of a shear building that is characterized by light damping (up to 5%). The envisaged analysis is taking place through Monte Carlo experiments under two different excitation types (stationary / non-stationary) and the applied ES are assessed in terms of (i) accurate modal parameters extraction, (ii) statistical consistency, (iii) performance under noise-corrupted data, and (iv) performance under non-stationary data. The results of this suggest that ES are indeed competitive alternatives in the non-linear state-spaceestimation problem and deserve further attention
Sensor Networks in Structural Health Monitoring: From Theory to Practice
No full textThe intense development of novel data-driven and hybrid methods for structural health monitoring (SHM) has been demonstrated by field deployments on large-scale systems, including transport, wind energy, and building infrastructure. The actionability of SHM as an essential resource for life-cycle and resilience management is heavily dependent on the advent of low-cost and easily deployable sensors Nonetheless, in optimizing these deployments, a number of open issues remain with respect to the sensing side. These are associated with the type, configuration, and eventual processing of the information acquired from these sensors to deliver continuous behavioral signatures of the monitored structures. This book discusses the latest advances in the field of sensor networks for SHM. The focus lies both in active research on the theoretical foundations of optimally deploying and operating sensor networks and in those technological developments that might designate the next generation of sensing solutions targeted for SHM. The included contributions span the complete SHM information chain, from sensor design to configuration, data interpretation, and triggering of reactive action. The featured papers published in this Special Issue offer an overview of the state of the art and further proceed to introduce novel methods and tools. Particular attention is given to the treatment of uncertainty, which inherently describes the sensed information and the behavior of monitored systems
On the use of dispersion analysis for model assessment in structural identification
No full textOne of the most important issues faced in parametric time-domain identification and subsequent experimental/operational modal analysis is the correct estimation of model order, which in turn determines the number of structural vibration modes. The aim of this study is to provide a quantitative and physically meaningful framework for model order assessment that is characterized by global applicability, in the sense of implementation in both state-space and transfer function model representations. To this end and under the assumption of stationary wideband excitation, a novel dispersion analysis scheme is proposed for the quantification of every mode's relative importance to the total stochastic response, which is based on a modal decomposition of the covariance matrix. Subsequently, after defining the modal dispersion matrix, a corresponding metric is introduced and used either as a stand alone tool for model order assessment, or as an extension of existing tools, such as stabilization diagrams. The method is validated through both simulated (NASA Mini-Mast truss) and experimental (suspended steel subframe flexible structure) identification problems, for which a subspace and a prediction-error estimation method are utilized and compared under the proposed quantitative indices. Moreover, performance comparisons with other energy-based metrics are also reported. The results indicate that the proposed method can be effectively used in parametric time-domain structural identification, for both order assessment and comparison of diverse model-based estimation methods
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Hybridization of Guided Surface Acoustic Modes in Unconsolidated Granular Media by a Resonant Metasurface
Full text linkWe investigate the interaction of guided surface acoustic modes (GSAMs) in unconsolidated granular media with a metasurface, consisting of an array of vertical oscillators. We experimentally observe the hybridization of the lowest-order GSAM at the metasurface resonance, and note the absence of mode delocalization found in homogeneous media. Our numerical studies reveal how the stiffness gradient induced by gravity in granular media causes a down-conversion of all the higher-order GSAMs, which preserves the acoustic energy confinement. We anticipate these findings to have implications in the design of seismic-wave protection devices in stratified soils
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