连续小波变换在齿轮磨损估计中应用研究
Application Research of Continuous Wavelet Transform in Wear Estimation of Gears
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摘要: 通过对连续小波变换的分析研究,提出了一种提取信号在小波尺度上的能量谱的信号分析方法。该方法能有效地对不同磨损状况下的齿轮振动信号进行分析,分析结果说明信号在小波尺度上的能量谱与齿轮的磨损程度有密切的关系。求出不同磨损状况下齿轮振动信号的能量谱对尺度的积分值,并根据这些值拟合得到的曲线与齿轮磨损过程曲线非常相似,这说明可以用连续小波变换的能量谱估计齿轮磨损状况。最后提出了一种连续小波变换的齿轮磨损特征量提取方法,用于提取齿轮磨损程度的特征向量,特征量间的欧氏距离说明这些特征向量能很好地表征齿轮的磨损状况Abstract: On the basis of continuous wavelet transform, a signal analysis method based on extracting the energy spectrum of the signal on wavelet scale was proposed. This method was then applied to analyzing the gear vibration signal of different wearing conditions. The result shows that the energy spectrum of the signal on scale is closely related to the wearing condition of the gear. The accumulation values of the energy spectrum of the signal on scale are computed; then a curve much like that of the gear wear course is fitted according to these values. The curve shows that the energy spectrum of the continuous wavelet transform of the signal is sufficient to represent the wearing condition of the gear. A feature vector extraction method based on continuous wavelet transform is represented and applied in extracting the wearing feature of the gear. The distances between the vectors of different wearing condition proved that this feature extraction method is quite effective.