Resumen de Pattern recognition based on qualitative representation of signals. Application to situation assessment of dynamic systems
The main focus of situation assessment is to decide on the adequacy of process behaviour with respect to specifications. When is not possible to have a mathematical model to represent the system operation, other non-model-based techniques must be considered. Classification methods are typically proposed as strategies for diagnosis. Here, identification of the functional states is reduced to recognising the current shapes of variables as well-known states, commonly taking advantage of a process expert or past experiences. However, human knowledge is related to concepts and symbols whereas process acquisition systems provide monitoring systems with numerical data. Consequently, these type of knowledge-based decision systems are usually forced to work in a higher level of abstraction using symbolic representations. This thesis deals with the study of classification methods when performing qualitative trends analysis. The aim is to obtain qualitative trends and their classification by means of the extracted knowledge from past experiences. This doctoral dissertation deals with the study of classification methods when performing qualitative trends analysis. The aim is to obtain qualitative trends and their classification by means of the extracted knowledge from past experiences.
