Active fault diagnosis based on consistencies to a class of hybrid systems by using genetic algorithms and Markov decision process
Abstract:
Systems are growing in complexity and the fault diagnosis process requires using interdisciplinary methods to improve the diagnosis performance in continuous and hybrid systems, particularly when uncertainties affect the diagnosis results. In this work we apply an active diagnosis to a class of hybrid system, which is designed in two parts. First, we use a Genetic Algorithm (GA) to find the proper Analytical Redundancy Relations (ARR) based on the minimal test equation support and structural model analysis over a bipartite graph. These ARR are used as residual generation in a consistency based diagnosis. In the second part, an active diagnosis based on a Markov Decision Process (MDP) is used to get an optimal policy of actions driving the system to the most informative operation points, to minimize the possible ambiguity in the passive fault diagnosis due to existing uncertainties in the system. The active …
Año de publicación:
2020
Keywords:
Fuente:

Tipo de documento:
Other
Estado:
Acceso abierto
Áreas de conocimiento:
- Algoritmo
- Inteligencia artificial
- Ciencias de la computación
Áreas temáticas:
- Física aplicada
- Ciencias de la computación
- Métodos informáticos especiales