Fault diagnosis of wind turbine planetary gear box based on EMD and resonance remodulation

Junshan Si, Yi Cao, Xianjiang Shi
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引用次数: 6

Abstract

Planetary gearbox of wind turbine works under changed load and speed and the vibration signal is nonlinear, non-stationary, this make it difficult to extract the weak fault characteristic frequency. In this paper, a new method of fault feature extraction and separation based on empirical mode decomposition (EMD) and resonance demodulation is proposed. The method uses EMD to decompose the vibration signal and gets the intrinsic mode function (IMF) which can represent different frequencies. Then, the IMF component of the structure resonance frequency which is caused by the fault gear impact is selected to demodulate and analyze, and the weak fault information is extracted. In order to verify the effectiveness of the proposed method, a simulation platform of the wind turbine is built based on the analysis of the structure and typical vibration characteristics of the planetary gear, we analyze the vibration signal of the planetary gear in normal and fault state. The experimental results show that it is feasible to denoise the fault information and extract the fault characteristic frequency components by using EMD and structural resonance demodulation technique.
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基于EMD和共振调制的风力发电机行星齿轮箱故障诊断
风力发电机行星齿轮箱在变负荷、变转速下工作,振动信号非线性、非平稳,这给微弱故障特征频率的提取带来了困难。提出了一种基于经验模态分解(EMD)和共振解调的故障特征提取与分离方法。该方法利用EMD对振动信号进行分解,得到能表示不同频率的内禀模态函数(IMF)。然后,选取故障齿轮撞击引起的结构共振频率的IMF分量进行解调分析,提取弱故障信息;为了验证所提方法的有效性,在分析行星齿轮结构和典型振动特性的基础上,搭建了风力机仿真平台,分析了行星齿轮在正常和故障状态下的振动信号。实验结果表明,采用EMD和结构共振解调技术对故障信息进行去噪和提取故障特征频率分量是可行的。
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