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Development of a vibration-based structural health monitoring system for wind turbines

  • In the context of national innovative project IMO-WIND, an integrated long term monitoring System was installed on a prototype of an offshore wind turbine System of 5 megawatt dass. The Federal Institute for Materials Research and Testing (BAM) was responsible for development of the SHM System. It consists of a signal acquisition System and a Signal processing and management System. The signal acquisition System is composed of 14 acceleration sensors, 110 strain gauges and 4 inclination sensors, installed at the tripod foundation and the tower. It began to work in August 2007. In order to investigate the structural dynamic properties, extract efficient damage index and manage huge amounts of Vibration Signals and analysis results, an automated signal processing and management Software System is developed in LabVIEW® environment. It includes functions such as automated Operational Modal Analysis (OMA) on the basis of Stochastic Subspace Identification (SSI) method and poly-referenceIn the context of national innovative project IMO-WIND, an integrated long term monitoring System was installed on a prototype of an offshore wind turbine System of 5 megawatt dass. The Federal Institute for Materials Research and Testing (BAM) was responsible for development of the SHM System. It consists of a signal acquisition System and a Signal processing and management System. The signal acquisition System is composed of 14 acceleration sensors, 110 strain gauges and 4 inclination sensors, installed at the tripod foundation and the tower. It began to work in August 2007. In order to investigate the structural dynamic properties, extract efficient damage index and manage huge amounts of Vibration Signals and analysis results, an automated signal processing and management Software System is developed in LabVIEW® environment. It includes functions such as automated Operational Modal Analysis (OMA) on the basis of Stochastic Subspace Identification (SSI) method and poly-reference Least-Squares Complex Frequency Domain (p-LSCF) approach, investigation of environmental/operational effects on structural dynamic properties under operational conditions, features extraction using Principal Component Regression (PCR) and Multiple Linear Regression (MLR) as well as data/result management and visualization. Besides, this paper also presents variations of structural modal parameters of a wind turbine system under complex environmental/operational conditions. Comparison of modal parameters automatically extracted by SSI method and poly-reference p-LSCF approach indicates that the latter method provides more stable modal identification results ffom the viewpoint of long term OMA. Subsequently, the influences of temperature, wind velocity, rotation speed and nacelle direction on modal parameters are generally discussed. Finally, variations of indentified modal parameters during two years are presented.zeige mehrzeige weniger

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Autor*innen:Wei-Hua Hu, Rolf Rohrmann, Samir Said, Werner Rücker
Persönliche Herausgeber*innen:Y. L. Xu, S. Zhu, Y. Xia, Y.Q. Ni, S.S. Law, J. H. Yin, Z.Q. Su
Dokumenttyp:Beitrag zu einem Tagungsband
Veröffentlichungsform:Verlagsliteratur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):SHMII-6 - 6th International conference on structural health monitoring of intelligent infrastructure (Proceedings)
Jahr der Erstveröffentlichung:2013
Herausgeber (Institution):International society for structural health monitoring of intelligent infrastructure
Erste Seite:1
Letzte Seite:10
Freie Schlagwörter:Automated operational modal analysis; Damage detection; Environmental and operational effects; Feature extraction; Vibration-based structural health monitoring system; Wind turbine
Veranstaltung:SHMII-6 - 6th International conference on structural health monitoring of intelligent infrastructure
Veranstaltungsort:Hong Kong, China
Beginndatum der Veranstaltung:09.12.2013
Enddatum der Veranstaltung:11.12.2013
ISBN:978-962-367-768-4
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:20.02.2016
Referierte Publikation:Ja
Datum der Eintragung als referierte Publikation:13.04.2015
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