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 …
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 …
A novel intelligent diagnosis method using optimal LS-SVM with improved PSO algorithm
W Deng, R Yao, H Zhao, X Yang, G Li - Soft computing, 2019 - Springer
Aiming at the problem that the most existing fault diagnosis methods could not effectively
recognize the early faults in the rotating machinery, the empirical mode decomposition, fuzzy …
recognize the early faults in the rotating machinery, the empirical mode decomposition, fuzzy …
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 …
Wind turbine fault detection using a denoising autoencoder with temporal information
Data-driven approaches have gained increasing interests in the fault detection of wind
turbines (WTs) due to the difficulty in system modeling and the availability of sensor data …
turbines (WTs) due to the difficulty in system modeling and the availability of sensor data …
Challenges and opportunities of deep learning-based process fault detection and diagnosis: a review
J Yu, Y Zhang - Neural Computing and Applications, 2023 - Springer
Process fault detection and diagnosis (FDD) is a predominant task to ensure product quality
and process reliability in modern industrial systems. Those traditional FDD techniques are …
and process reliability in modern industrial systems. Those traditional FDD techniques are …
Transforming data into knowledge for improved wastewater treatment operation: A critical review of techniques
The aim of this paper is to describe the state-of-the art computer-based techniques for data
analysis to improve operation of wastewater treatment plants. A comprehensive review of …
analysis to improve operation of wastewater treatment plants. A comprehensive review of …
Total projection to latent structures for process monitoring
Partial least squares or projection to latent structures (PLS) has been used in multivariate
statistical process monitoring similar to principal component analysis. Standard PLS often …
statistical process monitoring similar to principal component analysis. Standard PLS often …