Supervision of Industrial Processes using Self Organizing Maps
Ignacio Díaz, Abel A. Cuadrado, Alberto B. Díez, Manuel Domínguez, Juan Jose Fuertes, Miguel Angel Prada · IGI Global eBooks · 2012
The objective of this chapter is to present, in a comprehensive and unified way, a corpus of data and knowledge visualization techniques based on the Self-Organizing Map (SOM). These techniques allow exploring the behavior of the process in a visual and intuitive way through the integration of existing process-related knowledge with information extracted from data, providing new ways for knowledge discovery. With a special focus on the application to process supervision and modeling, the chapter reviews well known techniques –such as component planes, u-matrix, and projection of the process state– but also presents recent developments for visualizing process-related knowledge, such as fuzzy maps, local correlation maps, and model maps. It also introduces the maps of dynamics, which allow users to visualize the dynamical behavior of the process on a local model basis, in a seamless integration with the former visualizations, making it possible to confront all them for discovery of new knowledge.