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Application of Hilbert-Huang Transform Method on Fault Diagnosis for Wind Turbine Rotor

机译:Hilbert-Huang变换方法在风力发电机转子故障诊断中的应用

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摘要

Many signals of wind turbine faults are non-stationary and have highly complex time-frequency characteristics.Traditional time-frequency analysis method,such as Windowed Fourier Transform method,has no noticeable effect in handing non-stationary signals.Hilbert-Huang Transform (HHT) is a new signal processing method for analyzing the non-stationary mechanical signals.Based on Empirical Mode Decomposition (EMD),the Intrinsic Mode Function (IMF) in HHT can reflect the intrinsic physical characteristics of original data.Moreover,it is a good way to identify the faults involving a breakdown change.First,the principles and advantages of the HHT are presented in detail in this paper.Then,three typical faults of wind turbine rotor,such as rotor imbalance,aerodynamic asymmetry due to blade surface roughness and yaw misalignment are discussed by the HHT.Last,reasonable conclusions are drawn by the comparison between this method and the Wavelet Transform (WT) method with the help of simulation fault signals.The results show the effectiveness of HHT method for diagnosing those faults of wind turbine rotor.
机译:风力发电机故障的许多信号都是非平稳的,并且具有很高的时频特性。传统的时频分析方法,例如窗口傅立叶变换法,在处理非平稳信号方面没有明显的效果。希尔伯特-黄变换(HHT) )是一种用于分析非平稳机械信号的新信号处理方法。基于经验模态分解(EMD),HHT中的本征模函数(IMF)可以反映原始数据的固有物理特性。首先,详细介绍了HHT的原理和优点。然后,针对风力发电机转子的三个典型故障,如转子不平衡,叶片表面粗糙度引起的气动不对称以及HHT讨论了偏航角未对准问题。最后,通过仿真f将该方法与小波变换(WT)方法进行比较,得出了合理的结论。结果表明,HHT方法在诊断风力发电机转子故障时是有效的。

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