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Unsupervised condition change detection in large diesel engines

机译:大型柴油机的无监督状态变化检测

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摘要

This work presents a new method for unsupervised change detection, which combines independent component modeling, and probabilistic outlier detection. The method further provides a compact data representation, which is amenable to interpretation, i.e., the detected condition changes can be investigated further. The method is successfully applied to unsupervised condition change detection in large diesel engines from acoustical emission sensor signal and compared to more classical techniques based on principal component analysis and Gaussian mixture models.
机译:这项工作提出了一种新的无监督变更检测方法,该方法结合了独立的组件建模和概率离群值检测。该方法还提供了紧凑的数据表示形式,其易于解释,即可以进一步研究检测到的条件变化。该方法已成功应用于声发射传感器信号对大型柴油机进行无监督状态变化检测,并与基于主成分分析和高斯混合模型的经典技术进行了比较。

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