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Using creative synchronous averaging for detecting defects of a belt-driven bevel gearbox
参考中译:创新同步平均法检测皮带传动圆锥齿轮箱缺陷
刊名：
Condition Monitor
作者：
S Ganeriwala
（SpectraQuest Inc）
刊号：
711C0068/E
ISSN：
0268-8050
出版年：
2023
年卷期：
2023
页码：
5-9
总页数：
5
分类号：
X92
语种：
eng
文摘：
Condition monitoring of gearboxes in industrial settings is often based on trending vibration levels at the gear mesh frequencies and sideband frequencies associated with the rotational speeds of mating shafts. However, the vibration levels for setting different alarms related to gearbox health are debated. Another issue of controversy is the question of what an indicator of fault severity is: is it the energy in the gear mesh frequencies or the energies in the sidebands? In this work, we analysed the vibration signature caused by gear tooth seeded faults of different levels. The data was analysed in both the time and frequency domains. The experimental study was conducted on a Machinery Fault Simulator (MFS). The pinion gear in the gearbox was intentionally faulted with increasing severities and a vibration signal was collected for each case using IEPE accelerometers. Data was also obtained using a high-resolution encoder. Signals were analysed using time synchronous averaging and traditional spectrum analysis. The results indicate that the vibration signature of a faulted bevel gear tooth is a pulse in the time domain. Because of this impulse signal, strong sidebands arise in the spectrum around the mesh frequency and the energy in the sidebands is a better indicator of the severity of the tooth defect.
参考中译：
工业环境中齿轮箱的状态监测通常基于齿轮啮合频率和与配合轴转速相关的边带频率的趋势振动级。然而，设置与变速箱健康相关的不同警报的振动级别存在争议。另一个有争议的问题是，故障严重程度的指标是什么：是齿轮啮合频率中的能量还是边带中的能量？本文分析了不同程度的轮齿萌生故障引起的振动特征。对数据进行了时间域和频域分析。实验研究是在机械故障模拟器上进行的。变速箱中的小齿轮故意出现故障，严重程度越来越高，并使用IEPE加速度计收集了每个案例的振动信号。数据也是使用高分辨率编码器获得的。信号分析采用时间同步平均和传统谱分析方法。结果表明，故障伞齿轮轮齿的振动特征在时间域内为脉冲。由于这种脉冲信号，在啮合频率附近的频谱中会出现较强的边带，而边带中的能量是反映牙齿缺陷严重程度的更好指标。
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