基于小波阈值的通风机故障特征提取应用研究

Research on fault feature extraction of fan based on wavelet threshold

为了对原始信号进行有效的降噪,从而获得的客观的煤矿主通风机的振动特征,确保通风机故障的诊断,采用小波阈值的方法,分析了小波阈值降噪的基本思路以及小波去噪阈值的选取原则;对小波降噪的特点进行分析,对比了小波分析和傅里叶变换分析2种方法下的去噪能力,研究为通风机故障的诊断提供了理论基础。

In order to effectively reduce the original signal,and obtain the objective vibration characteristics of the main coal mine fan,to ensure the diagnosis of the fan fault,the wavelet threshold method is used to analyze the basic idea of wavelet threshold denoising and the wavelet denoising threshold;the characteristics of wavelet denoising are analyzed,and the denoising ability under the two methods of wavelet analysis and fourier transform analysis is analyzed and compared,the research provides a theoretical basis for the diagnosis of ventilator faults.