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FEATURE EXTRACTION FOR BEARING PROGNOSTICS AND HEALTH MANAGEMENT (PHM) - A SURVEY

机译:轴承预测和健康管理(PHM)的特征提取 - 一项调查

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Feature extraction in bearing PHM involves extracting characteristic signatures from the original sensor measurements, which are sensitive to bearing condition and thus most useful in determining bearing faults. The quality of extracted features directly affects the performance and the effectiveness of bearing PHM. Feature extraction is therefore a critical component in bearing PHM. To optimally improve PHM effectiveness and minimize maintenance costs of bearings, a large amount research has been conducted in extracting salient features for PHM, which leads to a considerable number of feature extraction techniques. Our main effort in this paper is to survey some major techniques explored so far, focusing on more recent advancements. Our endeavor also includes pointing out the advantages and disadvantages of each of those techniques. This paper attempts to serve as a general reference for bearing PHM practitioners and as a general guide for choosing proper feature extraction methods for bearing PHM systems.
机译:在轴承PHM特征提取涉及从原始传感器测量,这对轴承条件敏感,因此在确定轴承故障最有用的提取特征签名。的提取的特征的质量直接影响性能和轴承PHM的有效性。因此特征提取是轴承PHM的关键组件。为了优化提高PHM效率和减少轴承的维护费用,大量的研究已经在提取了PHM显着特征,这导致了相当多的特征提取技术进行。我们在本文中主要精力是调查一些重大的技术探索,到目前为止,着眼于最近的进展。我们的努力还包括指出每个这些技术的优点和缺点。本文试图以用作轴承PHM从业者和作为选择用于承载PHM系统正确特征提取方法的一般指导的一般参考。

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