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Harmonic order tracking analysis: A novel method for the diagnosis of induction generators

机译:谐波阶次跟踪分析:感应发电机诊断的新方法

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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. New diagnostic techniques based on generator currents monitoring have recently been developed, but their use is still irrelevant despite the advantages that current monitoring presents versus monitoring vibrations. In part, this situation can be due to the needs of relatively high computing power not available in the wind-groups and also, to the use of signals that generate volumes of data difficult to transfer to control centers, where they could be processed. This paper introduces a methodology that aims to solve these problems. In this paper a novel diagnostic method based on monitoring the generator currents is proposed. This approach is based on the tracking analysis of the fault components using the harmonic order as independent variable. This approach can be implemented in low cost digital devices; the resultant patterns are very simple, since their shape is the same no matter the changes in the fundamental frequency and thus, are easily interpretable even by non-qualified persons. Moreover these patterns are characterized by a very low number of parameters, which make easy their transmission to remote control centers. This new approach is theoretically justified and validated by laboratory tests.
机译:鉴于意外故障对风电场盈利能力的负面影响,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。最近已经开发出了基于发电机电流监控的新诊断技术,但是尽管电流监控与监控振动相比具有优势,但它们的使用仍然无关紧要。在某种程度上,这种情况可能是由于需要风团中没有的相对较高的计算能力,还可能是由于使用了信号,这些信号产生的数据量很难传输到控制中心,在控制中心无法进行处理。本文介绍了旨在解决这些问题的方法。本文提出了一种基于监测发电机电流的新型诊断方法。该方法基于使用谐波阶数作为自变量的故障分量的跟踪分析。这种方法可以在低成本的数字设备中实现。所得到的图案非常简单,因为无论基本频率的变化如何,它们的形状都是相同的,因此即使是不合格的人也很容易解释。此外,这些模式的特点是参数数量非常少,这使得它们很容易传输到远程控制中心。从理论上讲,这种新方法是合理的,并通过实验室测试得到了验证。

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