摘要
在齿轮箱振动信号中,由于滚动轴承早期故障信号相对较弱,传统的齿轮箱滚动轴承故障诊断方法通常难以有效地提取轴承故障信息。为实现滚动轴承故障特征的准确提取,本文提出了一种基于同步平均和倒频谱编辑的齿轮箱滚动轴承故障分离诊断方法。所提方法首先利用时域同步平均实现齿轮成分增强,并通过倒频谱获得齿轮成分对应的倒频谱线准确位置,然后对原信号的倒频谱进行编辑实现对其中齿轮成分的或削弱以突出信号中的滚动轴承故障特征,提高齿轮箱滚动轴承故障诊断的准确性。仿真和试验结果验证了该方法的有效性。
In a gearbox,as rolling bearing fault signals are relatively weaker,the traditional rolling bearing fault diagnosis method is hard to extract bearing fault information from the gear-box vibration signals.In order to achieve the accurate extraction of bearing fault features,a method for bearing fault diagnosis based on cepstrum editing and time domain synchronous average was proposed here.With the proposed method,firstly the time domain synchronous average technology was used to enhance the gear-box vibration signals＇components.Then,the correct position of cepstrum line corresponding to each component was obtained using the cepstrum analysis.Finally,the vibration components in its original signals were weakened with the cepstrum editing to highlight rolling bearings＇fault features mixed in the original vibration signals and improve the correctness of gear-box rolling bearings＇fault diagnosis.Simulation and test results verified the effectiveness of this method.
出处
《振动与冲击》
EI
CSCD
北大核心
2015年第21期205-209,共5页
Journal of Vibration and Shock
基金
国家自然科学基金资助项目(51365023)
关键词
滚动轴承
故障诊断
倒频谱
时域同步平均
包络分析
rolling bearing
fault diagnosis
cepstrum
time domain synchronous average
envelope analysis
