摘要
采用数字仿真和数字检测技术,对轴承异常声检测特征量的选择进行了分析讨论。结果表明,现行异常声检测用特征量平均幅值、有效值、峰值、波峰因数、峭度系数、超门槛脉冲数、超门槛脉冲有效值中,波峰因数和超门槛脉冲数两个特征量相结合,能够对轴承异常声进行最为可靠和有效的检测。
Adopting the numeric simulation and the numeric detection technique,the analysis and discussion is made for the eigenvector selection in the measurement of abnormal sound of beatings. The results show that,of the eigenvectors ,such as average amplitude, virtual value, peak value, crest factor, kurtosis coeffcient, pulse number over threshold, virtual pulse value over threshold,which are presently used to detect abnormal sounds of bearings,the combination of the crest factor and pulse number over threshold can make the most reliable and effective detections for the abnormal sounds of beatings.
出处
《轴承》
北大核心
2005年第11期29-32,共4页
Bearing
关键词
滚动轴承
异常声
检测
波峰因数
超门槛脉冲数
峭度
wiling bearing
abnormal sound
detection
crest factor
pulse number over threshold
kurtosis
