Dynamic system modelling and process monitoring based on long-term dependency slow feature analysis

A process fault diagnosis method using multi‐time scale dynamic feature extraction based on convolutional neural network

(2020) Xinrui Gao et al.   CANADIAN JOURNAL OF CHEMICAL ENGINEERING

Variants of slow feature analysis framework for automatic detection and isolation of multiple oscillations in coupled control loops

(2020) Jie Wang et al.   COMPUTERS & CHEMICAL ENGINEERING

Multistep Dynamic Slow Feature Analysis for Industrial Process Monitoring

(2020) Xin Ma et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Online monitoring of performance variations and process dynamic anomalies with performance-relevant full decomposition of slow feature analysis

(2019) Jiale Zheng et al.   JOURNAL OF PROCESS CONTROL

Data Analytics and Machine Learning for Smart Process Manufacturing: Recent Advances and Perspectives in the Big Data Era

(2019) Chao Shang et al.   Engineering

Recursive Slow Feature Analysis for Adaptive Monitoring of Industrial Processes

(2018) Chao Shang et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Comparative study on monitoring schemes for non-Gaussian distributed processes

(2018) Gang Li et al.   JOURNAL OF PROCESS CONTROL

Real-time fault detection and diagnosis using sparse principal component analysis

(2018) Shriram Gajjar et al.   JOURNAL OF PROCESS CONTROL

A novel dynamic PCA algorithm for dynamic data modeling and process monitoring

(2018) Yining Dong et al.   JOURNAL OF PROCESS CONTROL

Semi-supervised dynamic latent variable modeling: I/O probabilistic slow feature analysis approach

(2018) Lei Fan et al.   AICHE JOURNAL

Monitoring of operating point and process dynamics via probabilistic slow feature analysis

(2016) Feihong Guo et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Probabilistic slow feature analysis-based representation learning from massive process data for soft sensor modeling

(2015) Chao Shang et al.   AICHE JOURNAL

Concurrent monitoring of operating condition deviations and process dynamics anomalies with slow feature analysis

(2015) Chao Shang et al.   AICHE JOURNAL

Survey on data-driven industrial process monitoring and diagnosis

(2012) S. Joe Qin   ANNUAL REVIEWS IN CONTROL

A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process

(2012) Shen Yin et al.   JOURNAL OF PROCESS CONTROL

Determining the state of a process control system: Current trends and future challenges

(2011) Y. Shardt et al.   CANADIAN JOURNAL OF CHEMICAL ENGINEERING