Combined use of sensor data and structural knowledge processed by Bayesian network: Application to a railway diagnosis aid scheme

Oukhellou, Latifa; Côme, Étienne; Bouillaut, Laurent; Aknin, Patrice

doi:10.1016/j.trc.2008.04.001

Cited by 33 publications

(16 citation statements)

References 21 publications

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“…2 R is equal to 1 minus the ratio of residual variability. When the variability of the residual values around the regression surface with regards to the overall variability is small, the predictions from the proposed regression equation are judged to be good.…”

Section: Damage Detection Based On Response Surface Modellingmentioning

confidence: 99%

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Damage identification in beams by a response surface based technique

Teidj

Driouach

Khamlichi

2014

MATEC Web of Conferences

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Abstract. In this work, identification of damage in uniform homogeneous metallic beams was considered through the propagation of non dispersive elastic torsional waves. The proposed damage detection procedure consisted of the following sequence. Giving a localized torque excitation, having the form of a short half-sine pulse, the first step was calculating the transient solution of the resulting torsional wave. This torque could be generated in practice by means of asymmetric laser irradiation of the beam surface. Then, a localized defect assumed to be characterized by an abrupt reduction of beam section area with a given height and extent was placed at a known location of the beam. Next, the response in terms of transverse section rotation rate was obtained for a point situated afterwards the defect, where the sensor was positioned. This last could utilize in practice the concept of laser vibrometry. A parametric study has been conducted after that by using a full factorial design of experiments table and numerical simulations based on a finite difference characteristic scheme. This has enabled the derivation of a response surface model that was shown to represent adequately the response of the system in terms of the following factors: defect extent and severity. The final step was performing the inverse problem solution in order to identify the defect characteristics by using measurement.

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Section: Damage Detection Based On Response Surface Modellingmentioning

confidence: 99%

“…Thus, singular points are also detected. To correct the obtained predictions by eddy current based technique, a Bayesian based method which uses two sources of information in order to distinguish between actual broken sections and ordinary singular points was proposed [2].…”

Section: Introductionmentioning

confidence: 99%

Damage identification in beams by a response surface based technique

Teidj

Driouach

Khamlichi

2014

MATEC Web of Conferences

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“…For example, in [9], the Sobol variance-based method was employed to determine sound design solutions for railway system. Similar issue was addressed in detection and diagnosis of broken rail for railway infrastructure, where Bayesian networks was adopted to analyse the sensor data [10]. In [11], by using the simulation of railway environments, the dependability and safety of satellite technique application in ERTMS system was assessed.…”

Section: Introductionmentioning

confidence: 99%

Safety monitor for train‐centric CBTC system

Wang

Zhao

Ning

et al. 2018

IET Intelligent Transport Systems

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Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. When citing, please reference the published version. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.

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“…Visual inspections are supplemented with eddy current [28] and ultrasound measurements [1] for detection of cracks. However, some conditions of IRJs can still not be detected by these three methods.…”

Section: Introductionmentioning

confidence: 99%

Health condition monitoring of insulated joints based on axle box acceleration measurements

Molodova

Oregui

Núñez

et al. 2016

Engineering Structures

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a b s t r a c tThis paper presents a health condition monitoring system for insulated rail joints (IRJs) based on axle box acceleration (ABA) measurements. The ABA signals from all the wheels of the measuring train are processed to extract those characteristics that better represent the quality of the IRJ. Then, different indicators are used for damage assessment, the most relevant being a set of frequency bands in the ABA power spectrum. A detection algorithm is proposed based on the derived frequency characteristics of the ABA signal. We compared the responses of IRJs in good condition with those in poor condition. Track inspections were performed to validate the health condition monitoring methodology in different IRJs of the Dutch railway network. The hit rate of IRJs detection was 84% for two validated tracks. The damage assessment procedure allowed to prioritize the IRJs that require maintenance. This information is useful for the railway inframanagers as it allows to predict where safety compromises will be faced.

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Combined use of sensor data and structural knowledge processed by Bayesian network: Application to a railway diagnosis aid scheme

Cited by 33 publications

References 21 publications

Damage identification in beams by a response surface based technique

Damage identification in beams by a response surface based technique

Safety monitor for train‐centric CBTC system

Health condition monitoring of insulated joints based on axle box acceleration measurements

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