基于ITD与SSA的传动箱信号降噪及微弱特征提取

Signal De-noising and Weak Feature Extraction of Gearbox Based on ITD and SSA

试验采集的传动箱振动信号特征能量通常很小且易淹没在背景噪声之中,针对这一问题,提出了一种将固有时间尺度分解(Intrinsic Time-scale Decomposition,ITD)与奇异谱分析(Singular Spectrum Analysis,SSA)相结合的时频分析方法,并用于信号微弱特征的提取。通过仿真信号及试验采集的振动信号进行验证,结果表明:该方法能够有效地从混杂着能量较大的背景信号和噪声干扰中提取出微弱信号的特征频率成分,并达到了很好的降噪效果,提取出的信号更接近于原始无噪声信号。研究为设备运行状态信息的提取与状态识别提供了一种新方法。

Aiming at the problem that characteristic energy of gearbox vibration signal collected in test is usually low and easy to be drown in background noise,a time-frequency domain analysis method based on Intrinsic Time-scale Decomposition(ITD)and Singular Spectrum Analysis (SSA)is proposed to extract the weak characteristic of signals.The method is verified by using simulation signals and vibration signals collected in test.The results show that the method can effectively extract the frequency features from the weak signals mixed with large-energy-background signal and noise,and the noise is reduced effectively, the extracted signals are close to the original noise free signals.The proposed technique develops a novel method to extract status information and recognize the state of equipment in running state.