2026-04-28T12:24:30Zhttps://uvadoc.uva.es/oai/request
oai:uvadoc.uva.es:10324/42312021-06-23T16:55:38Zcom_10324_30605com_10324_894col_10324_41
UVaDOC advisor Alonso González, Carlos Javier advisor Pulido Junquera, José Belarmino author Moya Alonso, Noemí editor Universidad de Valladolid. Escuela Técnica Superior de Ingeniería Informática 2014-02-04T13:41:28Z 2014-02-04T13:41:28Z 2013 http://uvadoc.uva.es/handle/10324/4231 b1663119 10.35376/10324/4231 Hybrid systems are very important in our society, we can find them in many engineering fields. They can develop a task by themselves or they can interact with people so they have to work in a nominal and safe state. Model-based Diagnosis (MBD) is a diagnosis branch that bases its decisions in models. This dissertation is placed in the MBD framework with Artificial Intelligence techniques, which is known as DX community. The kind of hybrid systems we focus on have a continuous behaviour commanded by discrete events. There are several works already done in the diagnosis of hybrid systems field. Most of them need to pre-enumerate all the possible modes in the system even if they are never visited during the process. To solve that problem, some authors have presented the Hybrid Bond Graph (HBG) modeling technique, that is an extension of Bond Graphs. HBGs do not need to enumerate all the system modes, they are built as the system visits them at run time. Regarding the faults that can appear in a hybrid system, they can be divided in two main groups: (1) Discrete faults, and (2) parametric or continuous faults. The discrete faults are related to the hybrid nature of the systems while the parametric or continuous faults appear as faults in the system parameters or in the sensors. Both types af faults have not been considered in a unified diagnosis architecture for hybrid systems. The diagnosis process can be divided in three main stages: Fault Detection, Fault Isolation and Fault Identification. Computing the set of Possible Conflicts (PCs) is a compilation technique used in MBD of continuous systems. They provide a decomposition of a system in subsystems with minimal analytical redundancy that makes the isolation process more efficient. They can be used for fault detection and isolation tasks by means of the Fault Signature Matrix (FSM). The FSM is a matrix that relates the different parameters (fault candidates) in a system and the PCs where they are used. eng Attribution-NonCommercial-NoDerivatives 4.0 International Modelos matemáticos Programación de ordenadores Redes de ordenadores Inteligencia artificial Fault Diagnosis of Hybrid Systems with Dynamic Bayesian Networks and Hybrid Possible Conficts info:eu-repo/semantics/doctoralThesis 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URL https://uvadoc.uva.es/bitstream/10324/4231/1/TESIS441-140204.pdf File MD5 08ddd86f3f23730638a640767138d393 4403101 application/pdf TESIS441-140204.pdf