Replication Data for: Structural health monitoring of jacket-type support structures in offshore wind turbines: a comprehensive dataset for bolt loosening detection through vibrational analysis

DOI

This dataset is a collection of vibrational data for structural health monitoring, with focus on the detection of bolt loosening in offshore wind turbine jacket foundations. The data set comprises 780 comma-separated values (CSV) files, each corresponding to specific experimental conditions, including various structural states of the wind turbine's support structure. These states are systematically varied considering three main aspects: the amplitude of a white noise (WN) signal, the type of bolt damage, and the level at which damage has occurred.

The data were meticulously collected using eight triaxial accelerometers (PCB R Piezotronic model 356A17), strategically placed at different locations on a scaled-down replica of an offshore jacket-type wind turbine. This setup facilitated the acquisition of detailed vibrational data through a National Instruments’ data acquisition (DAQ) system, comprising six input modules (NI 9234 model) housed in a chassis (cDAQ model). The white noise signal, simulating wind disturbance at the nacelle, was produced by a modal shaker and varied in three amplitudes (0.5, 1, and 2), directly proportional to the induced vibration in the wind turbine.

The conditions include a healthy state (bolts tightened to 12 Nm) and various degrees of loosening (bolts loosened to 9 Nm, 6 Nm, and completely absent), examined at four distinct levels of the turbine's base structure.

Identifier
DOI https://doi.org/10.34810/DATA1011
Metadata Access https://dataverse.csuc.cat/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34810/DATA1011
Provenance
Creator Valdez Yepez, Rhandall ORCID logo; Tutivén, Christian ORCID logo; Vidal Seguí, Yolanda ORCID logo
Publisher CORA.Repositori de Dades de Recerca
Contributor Vidal Seguí, Yolanda; Universitat Politècnica de Catalunya; 295(RA)
Publication Year 2024
Funding Reference https://ror.org/01bg62x04 2021-SGR-01044
Rights CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact Vidal Seguí, Yolanda (Universitat Politècnica de Catalunya)
Representation
Resource Type Experimental data; Dataset
Format text/tab-separated-values; text/csv; text/plain
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Version 3.0
Discipline Construction Engineering and Architecture; Engineering; Engineering Sciences