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A discrepancy analysis methodology for rolling element bearing diagnostics under variable speed conditions

机译：变速条件下滚动轴承诊断的差异分析方法

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摘要

Performing condition monitoring on critical machines such as gearboxes is essential to ensure that the machines operate reliably. However, many gearboxes are exposed to variable operating conditions which impede the condition inference task. Rolling element bearing component failures are important causes of gearbox failures and therefore robust bearing diagnostic techniques are required. In this paper, a rolling element bearing diagnostic methodology based on novelty detection is proposed for machines operating under variable speed conditions. The methodology uses the wavelet packet transform, order tracking and a feature modelling approach to generate a diagnostic metric in the form of a discrepancy measure. The probability distribution of the diagnostic metric, statistically conditioned on the corresponding operating conditions is estimated, whereafter the condition of the rolling bearing element is inferred. The rolling element bearing diagnostic methodology is validated on data from a phenomenological gearbox model and two experimental datasets. (C) 2018 Elsevier Ltd. All rights reserved.
机译：在关键机器（例如变速箱）上执行状态监视对于确保机器可靠运行至关重要。然而，许多变速箱处于可变的工作条件下，这阻碍了条件推断任务。滚动轴承组件故障是变速箱故障的重要原因，因此需要可靠的轴承诊断技术。本文提出了一种基于新颖性检测的滚动轴承诊断方法，用于变速条件下的机器。该方法使用小波包变换，顺序跟踪和特征建模方法来生成差异度量形式的诊断指标。估计统计地基于相应的运行条件的诊断度量的概率分布，然后推断出滚动轴承元件的状态。滚动轴承诊断方法已从现象学变速箱模型的数据和两个实验数据集中进行了验证。 （C）2018 Elsevier Ltd.保留所有权利。

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