基于小波包预处理的神经网络故障模式识别的研究

The study of fault model identification based on wavelet packet and neural network

基于小波包对信号的高分辨率分解和重构能力 ,把信号在不同频段上进行分解 ,提取各分量故障信号的特征 ,应用BP神经网络进行故障模式识别 ,并将这种方法用于齿轮故障模式识别 。

In this paper,the signals between different frequencies were decomposed and reconstructed in order to draw the character of the fault signal based on the ability of wavelet packet decomposition and reconstruction.Use BP neural network to identity fault model.Take advantage of this approach to identify the gear fault model and get better result.