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

Zhang, Yu and Bingham, Chris and Gallimore, Michael and Yang, Zhijing and Chen, Jun (2012) Sensor fault detection for industrial systems using a hierarchical clustering-based graphical user interface. In: IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), 13-15 September 2012, Hamburg, Germany.

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Abstract

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 in-operation sensor faults can be detected and identified by the hierarchical clustering-based graphical user interface.

Keywords:sensor fault detection, heirarchical clustering, dendrogram, graphical user interface
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
Divisions:College of Science > School of Engineering
ID Code:12546
Deposited On:20 Nov 2013 10:55

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