Process Industries handling, producing and storing bulk amount of hazardous materials are
a major source of concern in terms of both safety and security. Safety and security cannot be …

Safe and stable operation plays an important role in the chemical industry. Fault detection
and diagnosis (FDD) make it possible to identify abnormal process deviations early and …

This paper presents a data-driven methodology for fault detection and diagnosis (FDD) by
integrating the principal component analysis (PCA) with the Bayesian network (BN). Though …

Multi-agent systems (MASs) are typically composed of multiple smart entities with
independent sensing, communication, computing, and decision-making capabilities …

Fault diagnosis is critical for ensuring safe and stable chemical production. Correct
identification of causal relationships among variables in large-scale chemical processes is a …

Industrial processes are becoming increasingly large and complex, thus introducing
potential safety risks and requiring an effective approach to maintain safe production …

Abstract Through Condition-Based Maintenance strategy, planners can monitor the health of
the machinery and recommend actions based on the information obtained. Nevertheless …

Deep learning is a powerful tool for feature representation, and many methods based on
convolutional neural networks (CNNs) and recurrent neural networks (RNNs) have been …

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 …

A dynamic Bayesian network (DBN) based fault detection, root cause diagnosis, and fault
propagation pathway identification scheme is proposed. The proposed methodology …