The implementation of a learning classifier system for parameter identification by signal processing of data from steel strip downcoilers

The aim of this project is to improve the quality and consistency of coiling in a steel hot strip mill. Signal processing is used to gather information on the parameter characteristics of the mill downcoilers as an aid to operator and engineering decision making. The artificial intelligence (AI) paradigm of learning classifier systems (LCS) is proposed for the signal processing.