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Sensor fault detection for industrial systems using a hierarchical clustering-based graphical user interface

机译:使用基于分层聚类的图形用户界面的工业系统传感器故障检测

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The paper presents an effective and efficient method for sensor fault detection and identification within a large group of sensors based upon hierarchical cluster analysis. Fingerprints of the hierarchical clustering dendrograms are found for normal operation using normalized data, and sensor faults are detected through cluster changes occurring in the dendrogram. The proposed strategy is built into a user-friendly graphical interface, which is applied to a sub-15MW industrial gas turbine. It is shown, through use of real-time operational data, that inoperation sensor faults can be detected and identified by the hierarchical clustering-based graphical user interface.
机译:本文提出了一种有效的,高效的方法,用于基于层次聚类分析的大量传感器中的传感器故障检测和识别。使用归一化的数据可找到用于正常操作的分层聚类树状图的指纹,并通过在树状图中发生的聚类变化来检测传感器故障。所提议的策略已内置到用户友好的图形界面中,该界面已应用于15MW以下的工业燃气轮机。通过使用实时操作数据显示,可以通过基于分层聚类的图形用户界面来检测和识别不工作的传感器故障。

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