Dynamic process fault detection and diagnosis based on a combined approach of hidden Markov and Bayesian network model

The present study introduces a novel methodology for fault detection and diagnosis (FDD), based on a combined approach of data and process knowledge driven techniques. The Hidden Markov Model (HMM) detects the abnormalities based on process history while the Bayesian Network (BN) diagnoses the root causes of faults. An HMM is trained with standard operating condition data while the structure of BN is developed based on process knowledge. The...