摘要
为了更好地识别机车走形部滚动轴承的故障类型,提出了采用度量故障量值A_(dB)与轴承故障特征频率相结合,并通过虚拟仪器软件来进行诊断分析的方法。该方法首先对所提取的数据进行了二维Gabor带通滤波,然后对滤波数据进行倒谱分析,并提取倒谱分析后的特征信息。通过对特征信息的分析得出故障频率,并根据滚动轴承固有的特征频率给出故障范围,然后通过计算的A_(dB)值给出最终的故障所处的状态。该方法能够更加精确地给出具体的故障类型并提前给予安全预警提示,提高了机车的安全性。
In order to better identify the fault type of locomotive running of rolling bearings,through experiment and analysis,the measurement value of A_(dB) and fault bearing fault characteristic frequency combination,and through the virtual instrument software to analysis the diagnosis method.Firstly,the extracted data are filtered by band-pass filter,and then the cepstrum analysis is performed on the filtered data.Through the analysis of the characteristic information,the fault frequency is obtained,and the fault range is given according to the inherent characteristic frequency of the rolling bearing in this paper.
出处
《工业控制计算机》
2017年第9期48-49,共2页
Industrial Control Computer
关键词
滚动轴承
故障量值
特征频率
虚拟仪器
rolling bearing,fault value,characteristic frequency,virtual-instrument