Frequency response function data of a composite plate under various damage identification scenarios

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Nathan Dwek , Dennis Janssens , Vasileios Dimopoulos , Matteo Kirchner , Elke Deckers , Frank Naets
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引用次数: 0

Abstract

This article presents data collected in support of research on damage identification in a composite plate, using low-frequency vibration measurements. The data consist of the Frequency Response Functions (FRFs) of a square plate, measured using an impact hammer and accelerometers, as an alternative to ultrasonic measurements. The plate is instrumented with 7 accelerometers, and a dense grid of candidate damage locations is defined. First, a set of baseline FRFs is collected by measuring the responses to hammer excitations at all grid points. Then, 6 damage identification scenarios are considered, and for each scenario, a set of FRFs is collected by measuring the responses to hammer excitations at the 7 accelerometer locations. Added masses are glued to the plate to reproduce the scattering effect of damage. This provides a convenient academic example for a wide range of topics in the field of structural dynamics and serves as a first proof-of-concept exercise for damage identification research. In addition, it allows to validate different approaches and benchmark their performance, thereby contributing a reference test case to adequately compare methods against one another.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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