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Research on Fault Feature Extraction Method of the Wind Turbine Gearbox Based on SVD and Improved HHT

机译:基于SVD的风力涡轮机齿轮箱的故障特征提取方法研究及改进的HHT

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This paper researches fault feature extraction method based on singular value decomposition and the improved HHT method for non-stationary characteristics of wind turbine gearbox vibration signal. Firstly, through the signal phase space reconstruction, the singular value decomposition as a pre-filter, to preprocessing the signal, effectively weaken the random noise. Then using EEMD to improve the HHT method, decompose the denoising signal into a series of different time scales component of intrinsic mode functions. The fault characteristics of the signal are extracted by the Hilbert transform. Finally, simulating gearbox fault experiment to verify the effectively of the proposed method.
机译:本文研究了基于奇异值分解的故障特征提取方法及其改进的风力涡轮机振动信号的非静止特性HHT方法。首先,通过信号相位空间重建,奇异值分解作为预处理,以预处理信号,有效地削弱随机噪声。然后使用EEMD改进HHT方法,将去噪信号分解为内在模式功能的一系列不同时间尺度分量。信号的故障特性由Hilbert变换提取。最后,模拟变速箱故障实验,以有效地验证了所提出的方法。

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