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Bond-Graph-based Fault Diagnosis in Switched Power Electronic Systems

  • Switched power electronic subsystems are widely used in various applications. A fault in one of their components may have a significant effect on the system’s load or may even cause a damage. Therefore, it is important to detect and isolate faults and to report true faults to a supervisory system in order to avoid malfunction of or damage to a load. If, in a model-based approach to fault detection and isolation of hybrid systems, switching devices are considered as ideal switches then some equations must be reformulated whenever some devices have switched. In this paper, a fixed causality bond graph representation of hybrid system models is used, i.e., computational causalities assigned according to the Standard Causality Assignment Procedure (SCAP) are independent of system modes of operation. The latter are taken into account by transformer moduli mi(t) ∈ {0, 1} ∀t ≥ 0 in a unique set of equations of motion. In a case study, this approach is used for fault diagnosis in a three-phase full-wave rectifier. Residuals of Analytical Redundancy Relations (ARRs) holding for all modes of operations and serving as fault indicators are computed in an offline simulation as part of a DAE system by using a bond graph model of the faulty system instead of the real one and by coupling it to a bond graph of the healthy system by means of residual sinks.

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Document Type:Conference Object
Author:Wolfgang Borutzky
Parent Title (English):32nd IASTED International Conference on Modelling, Identification and Control (MIC 2013), February 11-13, 2013, Innsbruck, Austria
Publisher:ACTA Press
Publication year:2013
Keyword:ARRs; FDI; Switched power electronic systems; unique bond graph representation for all modes of operation
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2016/10/24