A tutorial review of neural network modeling approaches for model predictive control
An overview of the recent developments of time-series neural network modeling is
presented along with its use in model predictive control (MPC). A tutorial on the construction …
presented along with its use in model predictive control (MPC). A tutorial on the construction …
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 …
[PDF][PDF] 动态系统的故障诊断技术
周东华, 胡艳艳 - 自动化学报, 2009 - aas.net.cn
摘要提出了一种全新的分类框架, 将故障诊断方法整体分为两大类, 即定性分析的方法和定量
分析的方法. 对现有的方法在此框架下进行了划分, 并详细介绍了每种方法的基本思想 …
分析的方法. 对现有的方法在此框架下进行了划分, 并详细介绍了每种方法的基本思想 …
The promise of artificial intelligence in chemical engineering: Is it here, finally?
V Venkatasubramanian - AIChE Journal, 2019 - search.ebscohost.com
The article discusses the presence and potential of Artificial Intelligence in Chemical
Engineering and discusses its background. Topics include the Phases of Artificial …
Engineering and discusses its background. Topics include the Phases of Artificial …
Advances and opportunities in machine learning for process data analytics
In this paper we introduce the current thrust of development in machine learning and
artificial intelligence, fueled by advances in statistical learning theory over the last 20 years …
artificial intelligence, fueled by advances in statistical learning theory over the last 20 years …
From model, signal to knowledge: A data-driven perspective of fault detection and diagnosis
This review paper is to give a full picture of fault detection and diagnosis (FDD) in complex
systems from the perspective of data processing. As a matter of fact, an FDD system is a data …
systems from the perspective of data processing. As a matter of fact, an FDD system is a data …
Data-driven soft sensor development based on deep learning technique
In industrial process control, some product qualities and key variables are always difficult to
measure online due to technical or economic limitations. As an effective solution, data …
measure online due to technical or economic limitations. As an effective solution, 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 …
Data-driven soft sensors in the process industry
P Kadlec, B Gabrys, S Strandt - Computers & chemical engineering, 2009 - Elsevier
In the last two decades Soft Sensors established themselves as a valuable alternative to the
traditional means for the acquisition of critical process variables, process monitoring and …
traditional means for the acquisition of critical process variables, process monitoring and …
[图书][B] Fault detection and diagnosis in industrial systems
Early and accurate fault detection and diagnosis for modern manufacturing processes can
minimise downtime, increase the safety of plant operations, and reduce costs. Such process …
minimise downtime, increase the safety of plant operations, and reduce costs. Such process …