Abstract

Recently, a number of authors have been focusing on drive-by monitoring methods, exploiting sensors mounted on the vehicle rather than on the bridge to be monitored, with clear advantages in terms of cost and flexibility. This work aims at further exploring the feasibility and effectiveness of novel tools for indirect health monitoring of railway structures, by introducing a higher level of accuracy in damage modelling, achieve more close-to-reality results. A numerical study is carried out by means of a FE 3D model of a short span Warren truss bridge, simulating the dynamic interaction of the bridge/track/train structure. Two kinds of defects are simulated, the first one affecting the connection between the lower chord and the side diagonal member, the second one involving the joint between the cross-girder and the lower chord. Accelerations gathered from the train bogie in different working conditions and for different intensities of the damage level are analyzed through two time-frequency algorithms, namely Continuous Wavelet and Huang-Hilbert transforms, to evaluate their robustness to disturbing factors. Compared to previous studies, a complete 3D model of the rail vehicle, together with a 3D structural scheme of the bridge in place of the 2D equivalent scheme widely adopted in the literature, allow a more detailed and realistic representation of the effects of the bridge damage on the vehicle dynamics. Good numerical results are obtained from both the two algorithms in the case of the time-invariant track profile, whereas the Continuous Wavelet Transform is found to be more robust when a deterioration of track irregularity is simulated.

Highlights

  • Railway bridges represent a widely spread key component [1] within the railway infrastructure system

  • Accelerations gathered from the train bogie in different working conditions and for different intensities of the damage level are analyzed through two time-frequency algorithms, namely Continuous Wavelet and Huang-Hilbert transforms, to evaluate their robustness to disturbing factors

  • The maxima of the index revealing the presence of the damage can identify the damaged region, the Huang-Hilbert Transform (HHT) instantaneous energy peak falls at the right margin of the affected region

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Summary

Introduction

Railway bridges represent a widely spread key component [1] within the railway infrastructure system. A major concern about the practical validity of drive-by approach consists in the fact that the train response might be influenced by the bridge status, and by other factors not related to the damage, like the level of track irregularities, a different dynamic response of the vehicle due to different passenger loads, or other uncertainties related the train speed variation and accuracy of its positioning with respect to the bridge. They can be divided in two main categories 1: modal parameter-based and non-modal parameter-based methods. 2.42. .T4.raTirnaiMn oMdeoldel gaesmandieokcycartjahteeeodacicfeoonTwo[jeea2nnfifsrwnc3easfmTTcgte]ino,kowghunctowcenaudoertoetcraohgirictoib[fdatfeisr2fainlotaieetoce3rifhdsnrioofbn]n,teeeinenohtewnsrrosfcdeesotfswgishnois.(rwpteeiettirTrlthstenaeehthhheeeriaee(eatenadttcsheCrchihcshnltehiwS.aeseyseiArwtTcpciryibCttaahnsehhdportSrserbheydebttAaheahcosanoyilarevedndaastearieemryryrrbnmeatcavosddioi((ncocnedttyhnohbghdraynasntomeeeeniiavascgdldm8T)ieoTnaied.0eSdldSgvirA,e–cRefeReerl1brdalaoersa4)tottnd,mtc.rm0eigrhadcr,raeieakiAeeraeingtselmnmlrh,p,fseismrlapocyee/macavmceapthohmoteecowdae,ifetrvdevmricetatvaaerheeolhli)el,emnrlercay)ltyrdayvi,opteeacan,weftfrasawnfdeeoprelovtrad,alahosbeatllmtt,uaenrnyrbmunttardedyiertisoicotwiinrnheanrnttsagsroialorghglo,slre,iaa,llnsearpttanrmorodssrtoesao.teletdrtolaibtrap,htnntaoernpoiebselddogdi,roptrnaiitrachgeseeorosrhseadidr.dlrertllaebe,seittonpnedwpwfbpdtoiorwhotoeerercy-et-trefhbwtbearaeeheodwotraneei--gfnneoiidnnger conTdhietitornai.ns speed is in the range 80 km/h–140 km/h, corresponding to the real operating condition

Numerical Algorithms for Signal Processing
Influence of Damage Position
Conclusions

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