A full‐condition monitoring method for nonstationary dynamic chemical processes with cointegration and slow feature analysis
Chemical processes are in general subject to time variant conditions because of load
changes, product grade transitions, or other causes, resulting in typical nonstationary …
changes, product grade transitions, or other causes, resulting in typical nonstationary …
Survey on the theoretical research and engineering applications of multivariate statistics process monitoring algorithms: 2008–2017
Multivariate statistical process monitoring (MSPM) methods are significant for improving
production efficiency and enhancing safety. However, to the authors' best knowledge, there …
production efficiency and enhancing safety. However, to the authors' best knowledge, there …
非平稳间歇过程数据解析与状态监控—回顾与展望
赵春晖， 余万科， 高福荣 - 自动化学报, 2020 - aas.net.cn
间歇过程作为制造业的重要生产方式之一, 其高效运行是智能制造的优先主题.
为了保障生产过程的高效运行, 面向间歇生产的过程数据解析与状态监控算法在最近三十年间 …
为了保障生产过程的高效运行, 面向间歇生产的过程数据解析与状态监控算法在最近三十年间 …
Dual attention-based encoder–decoder: A customized sequence-to-sequence learning for soft sensor development
L Feng, C Zhao, Y Sun - IEEE Transactions on Neural …, 2020 - ieeexplore.ieee.org
Soft sensor techniques have been applied to predict the hard-to-measure quality variables
based on the easy-to-measure process variables in industry scenarios. Since the products …
based on the easy-to-measure process variables in industry scenarios. Since the products …
Recursive exponential slow feature analysis for fine-scale adaptive processes monitoring with comprehensive operation status identification
Due to the compensation of the control loops, industrial processes under feedback control
generally reveal typical dynamic behaviors for different operation statuses. Conventional …
generally reveal typical dynamic behaviors for different operation statuses. Conventional …
Linearity evaluation and variable subset partition based hierarchical process modeling and monitoring
Complex industrial processes may be formulated with hybrid correlations, indicating that
linear and nonlinear relationships simultaneously exist among process variables, which …
linear and nonlinear relationships simultaneously exist among process variables, which …
Pseudo Time-Slice Construction Using a Variable Moving Window k Nearest Neighbor Rule for Sequential Uneven Phase Division and Batch Process Monitoring
Multiphase characteristics and uneven-length batch duration have been two critical issues to
be addressed for batch process monitoring. To handle these issues, a variable moving …
be addressed for batch process monitoring. To handle these issues, a variable moving …
IIoT-enabled health monitoring for integrated heat pump system using mixture slow feature analysis
The sustaining evolution of sensing and advancement in communications technologies has
revolutionized prognostics and health management for various electrical equipment toward …
revolutionized prognostics and health management for various electrical equipment toward …
Multivariate statistical monitoring of key operation units of batch processes based on time-slice CCA
A modern batch process can be characterized by a large scale and multiple operation units,
and local fault detection for the key units of such a batch process is imperative. A time-slice …
and local fault detection for the key units of such a batch process is imperative. A time-slice …
Multiobjective two-dimensional CCA-based monitoring for successive batch processes with industrial injection molding application
Successive batch processes generally involve within-batch and batch-to-batch correlations,
and monitoring of such batch processes is imperative. This paper proposes a multiobjective …
and monitoring of such batch processes is imperative. This paper proposes a multiobjective …