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Analysis of natural frequencies of delaminated composite beams based on finite element method
Krawczuk, M.,Ostachowicz, W.,Zak, A. Techno-Press 1996 Structural Engineering and Mechanics, An Int'l Jou Vol.4 No.3
This paper presents a model of a layered, delaminated composite beam. The beam is modelled by beam finite elements, and the delamination is modelled by additional boundary conditions. In the present study, the laminated beam contains only one delaminated region through the thickness direction which extends to the full width of the beam. It is also assumed that the delamination is open. The influence of the delamination length and position upon changes in the bending natural frequencies of the composite laminated cantilever beam is investigated.
R.B. Bai,X.G. Song,M. Radzieński,W. Ostachowicz,S.S. Wang,M.S. Cao 국제구조공학회 2014 Smart Structures and Systems, An International Jou Vol.13 No.6
The objective of this study is to develop a reliable method for locating cracks in a beam usingdata fusion of fractal dimension features of operating deflection shapes. The Katz’s fractal dimension curveof an operating deflection shape is used as a basic feature of damage. Like most available damage features,the Katz’s fractal dimension curve has a notable limitation in characterizing damage: it is unresponsive todamage near the nodes of structural deformation responses, e.g., operating deflection shapes. To address thislimitation, data fusion of Katz’s fractal dimension curves of various operating deflection shapes is used tocreate a sophisticated fractal damage feature, the ‘overall Katz’s fractal dimension curve’. This overallKatz’s fractal dimension curve has the distinctive capability of overcoming the nodal effect of operatingdeflection shapes so that it maximizes responsiveness to damage and reliability of damage localization. Themethod is applied to the detection of damage in numerical and experimental cases of cantilever beams withsingle/multiple cracks, with high-resolution operating deflection shapes acquired by a scanning laservibrometer. Results show that the overall Katz’s fractal dimension curve can locate single/multiple cracks inbeams with significantly improved accuracy and reliability in comparison to the existing method. Datafusion of fractal dimension features of operating deflection shapes provides a viable strategy for identifyingdamage in beam-type structures, with robustness against node effects.
Bai, R.B.,Song, X.G.,Radzienski, M.,Cao, M.S.,Ostachowicz, W.,Wang, S.S. Techno-Press 2014 Smart Structures and Systems, An International Jou Vol.13 No.6
The objective of this study is to develop a reliable method for locating cracks in a beam using data fusion of fractal dimension features of operating deflection shapes. The Katz's fractal dimension curve of an operating deflection shape is used as a basic feature of damage. Like most available damage features, the Katz's fractal dimension curve has a notable limitation in characterizing damage: it is unresponsive to damage near the nodes of structural deformation responses, e.g., operating deflection shapes. To address this limitation, data fusion of Katz's fractal dimension curves of various operating deflection shapes is used to create a sophisticated fractal damage feature, the 'overall Katz's fractal dimension curve'. This overall Katz's fractal dimension curve has the distinctive capability of overcoming the nodal effect of operating deflection shapes so that it maximizes responsiveness to damage and reliability of damage localization. The method is applied to the detection of damage in numerical and experimental cases of cantilever beams with single/multiple cracks, with high-resolution operating deflection shapes acquired by a scanning laser vibrometer. Results show that the overall Katz's fractal dimension curve can locate single/multiple cracks in beams with significantly improved accuracy and reliability in comparison to the existing method. Data fusion of fractal dimension features of operating deflection shapes provides a viable strategy for identifying damage in beam-type structures, with robustness against node effects.
Vibration-based structural health monitoring using large sensor networks
Deraemaeker, A.,Preumont, A.,Reynders, E.,De Roeck, G.,Kullaa, J.,Lamsa, V.,Worden, K.,Manson, G.,Barthorpe, R.,Papatheou, E.,Kudela, P.,Malinowski, P.,Ostachowicz, W.,Wandowski, T. Techno-Press 2010 Smart Structures and Systems, An International Jou Vol.6 No.3
Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.
Vibration-based structural health monitoring using large sensor networks
A. Deraemaeker,A. Preumont,E. Reynders,G. De Roeck,J. Kullaa,V. Lämsä,K. Worden,G. Manson,R. Barthorpe,E. Papatheou,P. Kudela,P. Malinowski,W. Ostachowicz,T. Wandowski 국제구조공학회 2010 Smart Structures and Systems, An International Jou Vol.6 No.3
Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project Smart Sensing For Structural Health Monitoring(S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.