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Wind Turbine Gearbox Fault Diagnosis Based on Wavelet Theory and Hilbert Demodulation Spectrum

机译:基于小波理论和希尔伯特解调谱的风力涡轮机齿轮箱故障诊断

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Through the mechanism of the gearbox's vibration signal and establish the corresponding mathematical model, then establish a fault diagnosis method based on the wavelet theory and Hilbert demodulation spectrum. First, the wavelet threshold de-noising can be used to reducing noise of the gearbox's vibration signal. Then, use the wavelet packet decomposition to decomposing the de-noising signal into different frequency band. After that, use the Hilbert transform to demodulate the frequency band that focused power. Finally, extract the fault characteristic value for the fault diagnosis. Through a fault simulation vibration signal test the method, the results show that the method can effectively extract the fault information of the wind turbine gearbox.
机译:通过齿轮箱的振动信号的机制并建立相应的数学模型,然后基于小波理论和希尔伯特解调光谱建立故障诊断方法。 首先,小波阈值去噪可用于降低齿轮箱振动信号的噪音。 然后,使用小波分组分解将去噪信号分解成不同的频带。 之后,使用Hilbert变换来解调聚焦功率的频带。 最后,提取故障诊断的故障特征值。 通过故障仿真振动信号测试该方法,结果表明该方法可以有效地提取风力涡轮机齿轮箱的故障信息。

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