A review on basic data-driven approaches for industrial process monitoring
Recently, to ensure the reliability and safety of modern large-scale industrial processes, data-
driven methods have been receiving considerably increasing attention, particularly for the …
driven methods have been receiving considerably increasing attention, particularly for the …
Survey on data-driven industrial process monitoring and diagnosis
SJ Qin - Annual reviews in control, 2012 - Elsevier
This paper provides a state-of-the-art review of the methods and applications of data-driven
fault detection and diagnosis that have been developed over the last two decades. The …
fault detection and diagnosis that have been developed over the last two decades. The …
Data mining and analytics in the process industry: The role of machine learning
Data mining and analytics have played an important role in knowledge discovery and
decision making/supports in the process industry over the past several decades. As a …
decision making/supports in the process industry over the past several decades. As a …
A data-driven Bayesian network learning method for process fault diagnosis
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 …
integrating the principal component analysis (PCA) with the Bayesian network (BN). Though …
Deep convolutional neural network model based chemical process fault diagnosis
H Wu, J Zhao - Computers & chemical engineering, 2018 - Elsevier
Numerous accidents in chemical processes have caused emergency shutdowns, property
losses, casualties and/or environmental disruptions in the chemical process industry. Fault …
losses, casualties and/or environmental disruptions in the chemical process industry. Fault …
Review and perspectives of data-driven distributed monitoring for industrial plant-wide processes
Process monitoring is crucial for maintaining favorable operating conditions and has
received considerable attention in previous decades. Currently, a plant-wide process …
received considerable attention in previous decades. Currently, a plant-wide process …
Review of recent research on data-based process monitoring
Data-based process monitoring has become a key technology in process industries for
safety, quality, and operation efficiency enhancement. This paper provides a timely update …
safety, quality, and operation efficiency enhancement. This paper provides a timely update …
A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process
This paper provides a comparison study on the basic data-driven methods for process
monitoring and fault diagnosis (PM–FD). Based on the review of these methods and their …
monitoring and fault diagnosis (PM–FD). Based on the review of these methods and their …
An analysis of process fault diagnosis methods from safety perspectives
Industry 4.0 provides substantial opportunities to ensure a safer environment through online
monitoring, early detection of faults, and preventing the faults to failures transitions. Decision …
monitoring, early detection of faults, and preventing the faults to failures transitions. Decision …
A deep belief network based fault diagnosis model for complex chemical processes
Z Zhang, J Zhao - Computers & chemical engineering, 2017 - Elsevier
Data-driven methods have been regarded as desirable methods for fault detection and
diagnosis (FDD) of practical chemical processes. However, with the big data era coming …
diagnosis (FDD) of practical chemical processes. However, with the big data era coming …