Monitoring of complex systems of interacting dynamic systems

Authors:
Michael E. Cholette;Jianbo Liu;Dragan Djurdjanovic;Kenneth A. Marko
Affiliations:
University of Texas at Austin, Austin, USA;Michigan State University, Lansing, USA;University of Texas at Austin, Austin, USA;University of Michigan, Ann Arbor, USA
Venue:
Applied Intelligence
Year:
2012

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Abstract

Increases in functionality, power and intelligence of modern engineered systems led to complex systems with a large number of interconnected dynamic subsystems. In such machines, faults in one subsystem can cascade and affect the behavior of numerous other subsystems. This complicates the traditional fault monitoring procedures because of the need to train models of the faults that the monitoring system needs to detect and recognize. Unavoidable design defects, quality variations and different usage patterns make it infeasible to foresee all possible faults, resulting in limited diagnostic coverage that can only deal with previously anticipated and modeled failures. This leads to missed detections and costly blind swapping of acceptable components because of one's inability to accurately isolate the source of previously unseen anomalies. To circumvent these difficulties, a new paradigm for diagnostic systems is proposed and discussed in this paper. Its feasibility is demonstrated through application examples in automotive engine diagnostics.