摘要
应用了小波变换理论和小波降噪的原理,对齿轮箱的振动信号进行了小波降噪处理,有效的从含有噪声的齿轮箱振动信号中提取出该信号更加准确和真实的故障特征,从而为提高齿轮箱故障诊断的准确性以及检测齿轮箱的早期微弱故障信号提供了重要的参考价值。通过对仿真信号的降噪处理,然后进行FFT变换,并且和没经过信号降噪处理就进行FFT变换的对比,显示了小波降噪的优越性。最后通过对齿轮箱的实际振动信号的降噪处理,进一步表明了小波降噪在消除噪声干扰方面有效性。
The theory of wavelet transform and the principle of wavelet de-noising are used to carry out the wavelet de-noising for the vibration signals of gearbox and extract feature from noise signals,which is to improve the accuracy of fault diagnosis of gearbox and provide important reference value of early weak fault signal detection gearbox.Through FFT transform of the wavelet,de-noising for artificial signals is carried out and when compared with signals that with not de-noising wavelet and FFT transform,the superiority of the wavelet de-noising method is verified.Finally,through wavelet de-noised process for the actual signal,it is proved that de-noising study is effective on dispel noise.
出处
《机械设计与制造》
北大核心
2013年第3期81-83,共3页
Machinery Design & Manufacture
关键词
小波分析
小波降噪
傅里叶变换
故障诊断
Wavelet Analysis
Wavelet De-Noising
FFT Transform
Fault Diagnosis
