Data-driven performance analyses of wastewater treatment plants: A review
Recent advancements in data-driven process control and performance analysis could
provide the wastewater treatment industry with an opportunity to reduce costs and improve …
provide the wastewater treatment industry with an opportunity to reduce costs and improve …
A review of critical challenges in MI-BCI: From conventional to deep learning methods
Brain-computer interfaces (BCIs) have achieved significant success in controlling external
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …
[HTML][HTML] Machine learning in chemical engineering: strengths, weaknesses, opportunities, and threats
Chemical engineers rely on models for design, research, and daily decision-making, often
with potentially large financial and safety implications. Previous efforts a few decades ago to …
with potentially large financial and safety implications. Previous efforts a few decades ago to …
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 …
Perspectives on nonstationary process monitoring in the era of industrial artificial intelligence
C Zhao - Journal of Process Control, 2022 - Elsevier
The development of the Internet of Things, cloud computing, and artificial intelligence has
given birth to industrial artificial intelligence (IAI) technology, which enables us to obtain fine …
given birth to industrial artificial intelligence (IAI) technology, which enables us to obtain fine …
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 …
Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: A review of researches and future challenges
Abstract Fault Diagnosis and Health Monitoring (FD-HM) for modern control systems have
been an active area of research over the last few years. Model-based FD-HM computational …
been an active area of research over the last few years. Model-based FD-HM computational …
Gaussian process regression for tool wear prediction
D Kong, Y Chen, N Li - Mechanical systems and signal processing, 2018 - Elsevier
To realize and accelerate the pace of intelligent manufacturing, this paper presents a novel
tool wear assessment technique based on the integrated radial basis function based kernel …
tool wear assessment technique based on the integrated radial basis function based kernel …
A review on prognostic techniques for non-stationary and non-linear rotating systems
MS Kan, ACC Tan, J Mathew - Mechanical Systems and Signal Processing, 2015 - Elsevier
The field of prognostics has attracted significant interest from the research community in
recent times. Prognostics enables the prediction of failures in machines resulting in benefits …
recent times. Prognostics enables the prediction of failures in machines resulting in benefits …