Publications:Nonlinear relation mining for maintenance prediction


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Title Nonlinear relation mining for maintenance prediction
Author Ahmed Mosallam and Stefan Byttner and Magnus Svensson and Thorsteinn Rögnvaldsson
Year 2011
PublicationType Conference Paper
Conference IEEE Aerospace conference 2011, 5-12 march
Diva url
Abstract This paper presents a method for mining nonlinear relationships in machine data with the purpose of using such relationships to detect faults, isolate faults and predict wear and maintenance needs. The method is based on the symmetrical uncertainty measure from information theory, hierarchical clustering and self-organizing maps. It is demonstrated on synthetic data sets where it is shown to be able to detect interesting signal relations and outperform linear methods. It is also demonstrated on real data sets where it is considerably harder to select small feature sets. It is also demonstrated on the real data sets that there is information about system wear and system faults in the detected relationships. The work is part of a long-term research project with the aim to construct a self-organizing autonomic computing system for self-monitoring of mechatronic systems.