基于静电信号和短时傅里叶变换的齿轮故障监测方法

Gear fault monitoring method based on electrostatic signal and short-time Fourier transform

传统振动监测需依附被检对象,从而引起振动干扰源激励的增多,使得变工况下齿轮振动信号的故障特征被干扰信号湮没。为了解决这一问题,以啮合齿轮组为研究对象,分析了静电监测信号的优势,推导了信号时频分析理论,提出了一种基于静电信号和短时傅里叶变换(STFT)的齿轮故障监测方法。首先,研究了静电监测技术机理,设计了带阻滤波器去除工频干扰,完成了信号预处理工作;然后,推导了短时傅里叶加窗变换的原理,并结合齿轮振动和静电实验数据,分析了其时频域信号特征;最后,搭建了齿轮故障监测平台,进行了齿轮啮合磨损区域静电监测实验,验证了从静电信号中提取出齿轮故障特征的普适性。实验结果表明:静电信号提取的齿轮特征频率为309.6 Hz,与齿轮实际啮合频率一致,静电信号的三维功率谱密度与齿轮转速、载荷呈现正相关关系;与齿轮的振动信号相比,静电信号包含的干扰频带少,且利用时频功率谱可凸显不同的故障信息。研究结果表明:采用静电信号能较好地获取变工况下齿轮的状态信息,克服了振动监测的不足,该齿轮故障监测方法具有一定的应用价值。

Traditional vibration monitoring requires attachment to the tested object,which leads to an increase in vibration interference source excitation,causing the fault characteristics of gear vibration signals under variable operating conditions to be obscured by interference signals.In order to solve this problem,taking the meshing gear set as the research object,the advantages of electrostatic monitoring signal were analyzed,the theory of signal time-frequency analysis was deduced,and a gear fault monitoring method based on electrostatic signal and short time Fourier transform(STFT)was proposed.First of all,the mechanism of electrostatic monitoring technology was studied and a band-stop filter was designed to remove industrial frequency interference to achieve signal pre-processing work.And then,the principle of short-time Fourier plus window transformation was derived,and the time-frequency domain signal characteristics were analyzed by combining the gear vibration and electrostatic experimental data.Finally,a gear fault monitoring platform was set up and electrostatic monitoring experiments in the wear region were carried out by varying the gear revolutions and additional loads to verify the universality of electrostatic signal extraction for gear fault characteristics.The results of the experimental study show that the characteristic frequency of the gear extracted from the electrostatic signal is 309.6 Hz,which is consistent with the actual meshing frequency,and the three-dimensional power spectrum density is positively correlated with the gear speed and load.Compared with the vibration signal of gears,the electrostatic signal not only contains less interference frequency bands,but also highlight different fault information by using the time-frequency power spectrum.The results show that the electrostatic signal can better obtain the status information of gears under the variable working conditions,which overcomes the shortage of traditional vibration monitoring,and the gear fault monitoring method has certain application value.