A proposal for the diagnosis of uncertain dynamic systems based on interval models
The performance of a model-based diagnosis system could be affected by several uncertainty sources, such as,model errors,uncertainty in measurements, and disturbances. This uncertainty can be handled by mean of interval models.The aim of this thesis is to propose a methodology for fault detection, i...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2009 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/7750 |
| Acceso en línea: | http://www.tdx.cat/TDX-0706109-112938 http://hdl.handle.net/10803/7750 |
| Access Level: | acceso abierto |
| Palabra clave: | Robustesa Robustez Robustness Anàlisi estructural Análisis estructural Structrural analysis Incertesa Incertidumbre Uncertainty Models intervalars Modelos intervalares Interval model Diagnosi basada en models Diagnosis basada en modelos Model-based diagnosis Diagnosi de falles Diagnosis de fallos Fault diagnosis 004 68 |
| Sumario: | The performance of a model-based diagnosis system could be affected by several uncertainty sources, such as,model errors,uncertainty in measurements, and disturbances. This uncertainty can be handled by mean of interval models.The aim of this thesis is to propose a methodology for fault detection, isolation and identification based on interval models. The methodology includes some algorithms to obtain in an automatic way the symbolic expression of the residual generators enhancing the structural isolability of the faults, in order to design the fault detection tests. These algorithms are based on the structural model of the system. The stages of fault detection, isolation, and identification are stated as constraint satisfaction problems in continuous domains and solved by means of interval based consistency techniques. The qualitative fault isolation is enhanced by a reasoning in which the signs of the symptoms are derived from analytical redundancy relations or bond graph models of the system. An initial and empirical analysis regarding the differences between interval-based and statistical-based techniques is presented in this thesis. The performance and efficiency of the contributions are illustrated through several application examples, covering different levels of complexity. |
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