New Method for Classifying Process Trends Based on Fuzzy Triangular Representation and Hidden Markov Models

This paper presents a strategy to represent and classify process data for detection of abnormal operating conditions. It uses fuzzy triangular episodes for qualitative data representation and a set of hidden Markov models (HMMs) for classification. The method is tested on an industrial vacuum column for detection of column weeping.