Fault detection and isolation of hybrid systems using diagnosers that reason on components
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In this paper, a design methodology and implementation architecure for diagnosers in the framework of hybrid systems is proposed. The design methodo logy is based on the hybrid automata model that represents the system behavior, in which each mode relates to a set of components. The architecture includes a set of modules which achieve mode recognitionand diagnosis tasks both based on residuals generated by structural analysis. The two tasks interact each other since the diagnosis module adapts accordingly to the current mode of the hybrid system. Mode recognition involves detecting mode change and identifying the set of residuals that are consistent with the current mode of the hybrid system. On the other hand, diagnosis involves detecting and isolating the fault by interlinking the components underlying the inconsistencies reported by the residuals, along the DX approach. As an application case study to illustrate the proposed fault diagnosis approach for hybrid systems a partial model of the Barcelona sewer network is used.
CitationVento, J. [et al.]. Fault detection and isolation of hybrid systems using diagnosers that reason on components. A: IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes. "SAFEPROCESS 2012. 8th IFAC International Symposium on Fault Detection, Supervision and Safety for Technical Processes". Mexico City: 2012, p. 1250-1255.
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