References of "Rutten, Christophe"
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See detailDamage Detection on the Champangshiehl Bridge using Blind Source Separation
Nguyen, Viet Ha; Rutten, Christophe; Golinval, Jean-Claude ULg et al

in Strauss, Alfred; Frangopol, Dan M.; Bergmeister, Konrad (Eds.) Life-Cycle and Sustainability of Civil Infrastructure Systems (2012)

This paper addresses the problem of damage detection in civil engineering structures using characteristic subspaces obtained from principal component analysis (PCA) of output-only measurements. Damage ... [more ▼]

This paper addresses the problem of damage detection in civil engineering structures using characteristic subspaces obtained from principal component analysis (PCA) of output-only measurements. Damage detection is performed by comparing subspace features between a reference (healthy) state and a current (possibly damaged) state. The damage indicator used in this study is the angular coherence between sub-spaces. The considered damage detection procedure is illustrated on the Champangshiehl Bridge which is a two span concrete box girder bridge located in Luxembourg. Before its destruction, multiple damage levels were inten-tionally created by cutting a growing number of prestressed tendons. Vibration data were acquired by the University of Luxembourg for each damaged state at many locations on the bridge. As previous studies dem-onstrated the large importance of environmental factors on modal identification, special care was taken to evaluate this influence during the test campaign. [less ▲]

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See detailFault Diagnosis in Industrial Systems Based on Blind Source Separation Techniques Using One Single Vibration Sensor
Nguyen, Viet Ha; Rutten, Christophe; Golinval, Jean-Claude ULg

in Shock & Vibration (2012), 19(5), 795-801

In the field of structural health monitoring or machine condition monitoring, most vibration based methods reported in the literature require to measure responses at several locations on the structure. In ... [more ▼]

In the field of structural health monitoring or machine condition monitoring, most vibration based methods reported in the literature require to measure responses at several locations on the structure. In machine condition monitoring, the number of available vibration sensors is often small and it is not unusual that only one single sensor is used to monitor a machine. The aim of this paper is to propose an extension of fault detection techniques that may be used when a reduced set of sensors or even one single sensor is available. Fault detection techniques considered here are based on output-only methods coming from the Blind Source Separation (BSS) family, namely Principal Component Analysis (PCA) and Second Order Blind Identification (SOBI). The advantages of PCA or SOBI rely on their rapidity of use and their reliability. Based on these methods, subspace identification may be performed by using the concept of block Hankel matrices which make possible the use of only one single measurement signal. Thus, the problem of fault detection in mechanical systems can be solved by using subspaces built from active principal components or modal vectors. It consists in comparing subspace features between the reference (undamaged) state and a current state. The angular coherence between subspaces is a good indicator of a dynamic change in the system due to the occurrence of faults or damages. The robustness of the methods is illustrated on industrial examples. [less ▲]

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