基于小波分形技术提取变速器轴承故障特征

Extraction of Gearbox Bearing Fault Characters Based on Wavelet Fractal Technology

利用小波技术对变速器轴承振动信号进行分解,对特定层的信号进行重构,并计算重构信号的分形维数,来实现变速器轴承不同技术状态下特征提取。实验结果表明,特定频率振动信号的分形维数能敏感反映变速器轴承技术状态,它可以作为诊断变速器轴承故障的一个重要特征量。

The wavelet transform technology was applied to analyze the bearing vibration signal, then the specifically vibration series of signal is reconstructed, and fractal dimension of them is computed to pick up the fault characteristic in different technology state of the gearbox bearing. The experiment result shows that the fractal dimension of the vibration signal of specifically frequency bands can reflect the technology state of the gearbox bearing, and can be as an important characteristic parameter to diagnose the gearbox bearing fault.