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Portable network analyzer and mobile app based small wind turbine condition monitoring

机译:基于便携式网络分析仪和移动应用的小型风力发电机状态监测

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Improved fault diagnostic techniques in wind turbines is a field of growing interest, given the negative impact that unexpected breakdowns have on the profitability of wind farms. Traditional and new diagnostic techniques mainly based, respectively, on vibration and generator current monitoring cannot be applied easily to small wind groups due to the very restrictive cost limitations. This paper proposes a fault diagnosis technique based on monitoring generator voltage, current and power suitable for small wind groups based on permanent magnet synchronous generators which aims to offer an affordable solution that provides easy to understand information even for users lacking technologic training, helping them decide when to ask for specialized assistance. This proposal is based on data provided by a commercial monitoring system installed between the generator and the regenerative inverter and processed and displayed in a mobile device (smartphone or tablet-PC) App running either Android or iOS, thus greatly contributing to a very cost-effective solution. The actual performance of an off-the-shelf small wind group has been measured both off-line and on-line (by the diagnosis App during the training stage) with good agreement and confirms the suitability of the method to detect demagnetization faults.
机译:鉴于意外故障会对风力发电场的盈利能力产生负面影响,因此在风力涡轮机中改进故障诊断技术已成为人们日益关注的领域。分别基于振动和发电机电流监控的传统诊断技术和新诊断技术由于成本限制非常有限,因此无法轻松应用于小型风团。本文提出了一种基于永磁同步发电机的,基于发电机电压,电流和功率监测的故障诊断技术,该技术适用于小型风力发电机组,旨在提供一种负担得起的解决方案,即使对于缺乏技术培训的用户,也能提供易于理解的信息,从而帮助他们确定何时寻求专业协助。该提案基于安装在发电机与再生逆变器之间的商业监控系统提供的数据,并在运行Android或iOS的移动设备(智能手机或平板电脑)应用中进行处理和显示,从而极大地降低了成本-有效的解决方案。现成的小型风力发电机组的实际性能已离线(在线)和在线(通过培训阶段的诊断App)进行了测量,并具有良好的一致性,并证实了该方法适用于检测退磁故障。

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