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Weak fault signal detection of rolling bearing

机译:滚动轴承的弱故障信号检测

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摘要

The characteristics of local singularity of vibration signal under the wavelet transform are studied, and quantitative analysis of the noise reduction features of wavelet transform methods is carried out. Based on that the modulus maxima of the local singularity of fault vibration signal and noise of rolling bearing under wavelet transform has different propagation characteristics in different scales, the wavelet decomposition and reconstruction algorithms are used to conduct decomposition, noise reduction, re-structure and spectral analysis on vibration signals of the bearing. Experiment show that the wavelet noise reduction method is very suitable for fault frequency detection of weak vibration signal of rolling bearing in low SNR cases.
机译:研究了小波变换下振动信号局部奇异性的特点,并对小波变换方法的降噪特征进行了定量分析。基于小波变换的故障振动信号局部奇异性模量最大值和滚动轴承噪声在不同尺度下具有不同的传播特性,采用小波分解重构算法进行分解,降噪,重构和频谱分析。分析轴承的振动信号。实验表明,在低信噪比的情况下,小波降噪方法非常适用于滚动轴承弱振动信号的故障频率检测。

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