Abstract
This first chapter of this paper work refers to Simulink implementation of a neural and fuzzy system of crack prediction, detection, and rejection during the continuous casting processes. The neural and fuzzy system is made up by a neural network used for fissure detection and a fuzzy controller for predicting and rejecting them. This system uses a signal received from the neural network and some data to correct the casting speed and the primary cooling water. The second part of chapter describes the industrial Fuzzy System Decision (FSD) deployment of crack prediction and elimination as well as the adaptive system meant for eliminating any sliding between the semi-finished and the roll drawings (SFA), when the FSD casting speed performs any corrections. The last part of chapter describes an adaptive fuzzy system to eliminate any sliding that may occur between the billets and roll drawings in steel continuous casting plants. Any sliding may compromise the tuning speed of hardware caused by prediction system and crack elimination – therefore, speed corrections are common and applied as a necessary step. Design and production systems are based on an original research of the author.
Keywords: Fuzzy system, neural network, control, crack, continuous casting.
