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Diagnosis of vortex induced vibration of a gravity damper

Scappaticci L., Castellani F., Astolfi D., Garinei A.

Diagnostyka

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2018

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Vol. 19, No. 2

31--39

EN

A gravity damper is a one-way valve, employed for regulating the airflow rate in ducts, generally constituted by a series of rectangular panels (closure sections), connected to an articulated quadrilateral synchronizing the movements. If the device needs to process large masses of high speed air, as common in the case of energy conversion systems, disadvantageous dynamic effects can occur. In this study, vortexinduced vibration (VIV), occurring on a gravity damper for high values of the Reynolds number, is investigated. The analysis of this work couples numerical methods (Computational Fluid Dynamics with Large-Eddy Simulation turbulence model and Finite Element Method) to experiments: a full-scale accelerometric measurement campaign is actually performed at the wind tunnel facilities of the University of Perugia. VIVs are diagnosed and quantified through the experimental vibration analysis, which is interpreted through numerical simulations. The large amplitude of VIV is interpreted as due to a tendency towards lockin because of the approaching of the vortex shedding frequency to a natural vibration mode of the system. The integrated numerical and experimental framework finally inspires two different design solutions for mitigating the amplitude of VIV: these strategies are tested at the wind tunnel and they are indeed shown to be effective.

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Analysing wind turbine state dynamics for fault diagnosis

Bartolini N., Scappaticci L., Garinei A., Becchetti M., Terzi L.

Diagnostyka

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2016

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Vol. 17, No. 4

19--25

EN

Supervisory Control And Data Acquisition (SCADA) systems have recently become ubiquitous in wind energy technology. SCADA data analysis actually can provide considerable performance improvement at low cost. This also boosts wind energy exploitation, because it enlarges short and long term economic sustainability of investments. Nevertheless, SCADA data analysis poses several scientific and technological challenges, mostly related to the vastness of the data sets required for significant analysis. Separating the signal from the noise is therefore a complex task. In the present work, this issue is tackled by the point of view of state dynamics of wind turbines. SCADA control systems often record superabundant and ambiguous information. Therefore, in this work it is shown that hierarchical classification of information and time discretization of the continuous motion of states are powerful tools. The time-discretized state dynamics is processed in the formulation of several indices for performance evaluation and fault diagnosis. The method is tested on the data set of a wind farm owned by Renvico s.r.l. and sited in Italy.

3

A new data mining approach for power performance verification of an on-shore wind farm

Castellani F., Garinei A., Terzi L., Astolfi D., Moretti M., Lombardi A.

Diagnostyka

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2013

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Vol. 14, No. 4

35--42

EN

Monitoring wind energy production is fundamental to improve the performances of a wind farm during the operational phase. In order to perform reliable operational analysis, data mining of all available information spreading out from turbine control systems is required. In this work a SCADA (Supervisory Control And Data Acquisition) data analysis was performed on a small wind farm and new post-processing methods are proposed for condition monitoring of the aerogenerators. Indicators are defined to detect the malfunctioning of a wind turbine and to select meaningful data to investigate the causes of the anomalous behaviour of a turbine. The operating state database is used to collect information about the proper power production of a wind turbine and a number map has been codified for converting the performance analysis problem into a purely numerical one. Statistical analysis on the number map clearly helps in detecting operational anomalies, providing diagnosis for their reasons. The most operationally stressed turbines are systematically detected through the proposal of two Malfunctioning Indices. Results demonstrate that a proper selection of the SCADA data can be very useful to measure the real performances of a wind farm and thus to define optimal repair/replacement and preventive maintenance policies that play a major role in case of energy production.