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The anomalous and smoothed anomalous envelope spectra for rotating machine fault diagnosis

机译：用于旋转机器故障诊断的异常和平滑的异常信封谱

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摘要

The order-frequency spectral coherence and its integrated spectra (e.g. improved envelope spectrum, squared envelope spectrum) are some of the most powerful methods for performing fault diagnosis under time-varying operating conditions. However, it may require much work to interrogate the order-frequency spectral coherence for symptoms of damage. Hence, in this work we propose a methodology that combines the order-frequency spectral coherence with historical data that were acquired from a healthy machine to obtain an anomalous envelope spectrum, which is further processed for fault diagnosis. This anomalous envelope spectrum is further processed with a smoothing operation to not only perform automatic fault detection, but it is also possible to identify the damaged component if the kinematics of the gearbox are known. The proposed method is investigated on one numerical gearbox dataset and three experimental datasets, where its potential for performing automatic fault detection under time-varying operating conditions is highlighted.
机译：订单频谱相干性及其集成光谱（例如，改进的信封谱，平方包络谱）是用于在时变运行条件下执行故障诊断的一些最强大的方法。然而，它可能需要很多工作来询问令伤害症状的订单频谱相干性。因此，在这项工作中，我们提出了一种方法，该方法将订单频谱相干与从健康机器获取的历史数据结合以获得异常包络谱，这进一步处理了故障诊断。这种异常的包络谱通过平滑操作进一步处理，不仅可以执行自动故障检测，而且如果齿轮箱的运动学是已知的，则也可以识别损坏的部件。在一个数字齿轮箱数据集和三个实验数据集上研究了所提出的方法，其中突出了其在时变运行条件下执行自动故障检测的可能性。

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