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Comparison of methods for wind turbine condition monitoring with SCADA data

机译:用SCADA数据比较风力涡轮机状态的方法

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Wind turbine operational costs can be reduced by monitoring the condition of major components in the drivetrain. SCADA-based condition monitoring is attractive because the data are already collected, resulting in rapid deployment and modest set-up cost. Three SCADA-based monitoring methods were reviewed: signal trending; self-organising maps and physical model. The physical model was identified as being the most reliable at predicting impending component failures. A validation study on this method using five operational wind farms showed that it is possible to achieve a high detection rate and good detection accuracy. An advance detection period of between 1 month and 2 years was achieved by the method. The study has also highlighted limitations and areas for further development.
机译:通过监视传动系统中主要组件的状况,可以降低风力发电机的运营成本。基于SCADA的状态监视很有吸引力,因为已经收集了数据,从而导致了快速部署和适度的设置成本。审查了三种基于SCADA的监视方法:信号趋势;自组织图和物理模型。在预测即将发生的组件故障时,该物理模型被认为是最可靠的。使用五个运行中的风电场对该方法进行的验证研究表明,可以实现较高的检测率和良好的检测精度。通过该方法可以达到1个月至2年的提前检测期。该研究还强调了局限性和需要进一步发展的领域。

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