Abstract
This work proposes a common framework for Fault Detection and Isolation of discrete and parametric faults in hybrid systems using Hybrid Possible Conflicts , HPCs. Fault detection is based on residual activation for the set of HPCs in the current mode. Using the structural information in each HPC we first search for discrete –related to actuators– fault candidates, because these faults introduce highly non-linear behaviors. To confirm or reject them, we track sets of HPCs in the current and potential faulty modes. We confirm the mode whose HPC residuals become zero, or start the fault isolation of parametric faults if every discrete fault is discarded. We test our approach in a hybrid four tank system.
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Moya Alonso, N., Bregon, A., Alonso-González, C.J., Pulido, B. (2013). A Common Framework for Fault Diagnosis of Parametric and Discrete Faults Using Possible Conflicts. In: Bielza, C., et al. Advances in Artificial Intelligence. CAEPIA 2013. Lecture Notes in Computer Science(), vol 8109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40643-0_25
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DOI: https://doi.org/10.1007/978-3-642-40643-0_25
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