000004583 001__ 4583
000004583 005__ 20141118192708.0
000004583 0177_ $$2doi$$a10.3850/978-981-07-2219-7_P379

000004583 0247_ $$210.3850/978-981-07-2219-7_P379
$$adoi
000004583 04107 $$aeng
000004583 046__ $$k2012-05-23
000004583 100__ $$aYan, Wang-Ji
000004583 24500 $$aA Two-Stage Bayesian Approach for Ambient Modal Analysis using Wireless Sensor: Case of Separated Modes

000004583 24630 $$n5.$$pProceedings of the 5th Asian-Pacific Symposium on Structural Reliability and its Applications
000004583 260__ $$bResearch Publishing, No:83 Genting Lane, #08-01, Genting Building, 349568 SINGAPORE
000004583 506__ $$arestricted
000004583 520__ $$2eng$$aAs a promising alternative to the traditional wired sensors, wireless sensors are attracting recently widespread attention in the field of structural health monitoring (SHM). In this study, a two-stage Bayesian approach is proposed for ambient modal analysis employing wireless sensor networks (WSN). Herein we consider the case of a system with well-separated modes. During the first stage of the approach, spectral variables (i.e., eigen-frequencies, damping ratios as well as the spectral intensities of modal excitation and prediction error) and their associated uncertainties are identified by a so-called 'Fast Bayesian Spectrum Trace Approach' (FBSTA). Next, during the second stage of the approach and given the modal parameters identified in the first stage, the spatial variables (i.e., mode shapes) as well as their uncertainties are extracted instantaneously through a so-called 'Fast Bayesian Spectrum Density Approach' (FBSDA). A distributed computing strategy that improves the computational efficiency and reduces the required data transmission as well as the required memory space is also proposed to realize the proposed algorithm in the environment of WSN. A numerical example is presented to illustrate the efficiency of the proposed method.

000004583 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000004583 653__ $$aStructural health monitoring, Wireless sensors, ambient modal analysis, Bayesian approach, Distributed computing strategy, Uncertainty estimation.

000004583 7112_ $$a5th Asian-Pacific Symposium on Structural Reliability and its Applications$$cSingapore (SG)$$d2012-05-23 / 2012-05-25$$gAPSSRA2012
000004583 720__ $$aYan, Wang-Ji$$iKatafygiotis, Lambros S.
000004583 8560_ $$ffischerc@itam.cas.cz
000004583 8564_ $$s190175$$uhttps://invenio.itam.cas.cz/record/4583/files/P379.pdf$$yOriginal version of the author's contribution as presented on CD, .
000004583 962__ $$r4180
000004583 980__ $$aPAPER