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首页> 外文会议>American Society of Mechanical Engineers(ASME)/Society of Tribologists and Lubrication Engineers(STLE) International Joint Tribology Conference 2004(IJTC 2004) vol.1 pt.A; 20041024-27; Long Beach,CA(US) >Vibration Monitoring And Damage Quantification Of Faulty Ball Bearings
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Vibration Monitoring And Damage Quantification Of Faulty Ball Bearings

机译：故障球轴承的振动监测和损伤量化

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摘要

More often then not, the rolling element bearings of rotating machinery are the mechanical components that are first prone to premature failure. Early warning of an impending bearing failure is vital to the safety and reliability of high-speed turbo-machinery. Presently, vibration monitoring is one of the most applied procedures in on-line damage and failure monitoring of rolling element bearings. This paper presents results from an experimental rotor-bearing test rig where quantified damage was induced in the supporting tapered ball bearings. Subsequently the vibration signature due to damage at the inner race of the bearing is examined. Four on-line vibration signature analyzing schemes are used concomitantly: (ⅰ) time averaging, (ⅱ) frequency domain analysis, (ⅲ) joint time-frequency analysis (Wigner-Ville and wavelet transforms) and (ⅳ) chaotic vibration analysis (modified Poincare diagrams). The size/level of the damage is corroborated with the vibration amplitude and the resulting relationships are linearized to provide quantification criteria for bearing progressive failure prediction. The results from the above mentioned methodologies are compared for accuracy and redundancy, thus increasing the reliability for early detection of bearing damage and failure. It is shown that the use of the modified Poincare map can provide an effective way for identification and quantification of bearing damage in rolling element bearings.
机译：通常，旋转机械的滚动轴承是最容易过早失效的机械部件。轴承即将发生故障的预警对于高速涡轮机械的安全性和可靠性至关重要。当前，振动监测是滚动轴承在线损伤和故障监测中应用最广泛的程序之一。本文介绍了一个实验性的转子轴承试验台的结果，该试验台在支撑圆锥滚珠轴承中引起了定量的损坏。随后检查由于轴承内圈损坏引起的振动信号。同时使用了四种在线振动特征分析方案：（ⅰ）时间平均，（ⅱ）频域分析，（ⅲ）联合时频分析（Wigner-Ville和小波变换）和（ⅳ）混沌振动分析（已修改Poincare图）。损伤的大小/水平与振动幅度相符，并且将所得关系线性化以提供用于轴承渐进式故障预测的量化标准。比较了上述方法的结果的准确性和冗余性，从而提高了早期检测轴承损坏和故障的可靠性。结果表明，使用修改后的Poincare图可以提供一种有效的方法来识别和量化滚动轴承中的轴承损坏。

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