Anomaly Detection with GRU Based Bi-autoencoder for Industrial Multimode Process

A deep learned type-2 fuzzy neural network: Singular value decomposition approach

(2021) Sultan Noman Qasem et al.   APPLIED SOFT COMPUTING

Sparse stacked autoencoder network for complex system monitoring with industrial applications

(2020) Ziwei Deng et al.   CHAOS SOLITONS & FRACTALS

Self-adaptive deep learning for multimode process monitoring

(2020) Hao Wu et al.   COMPUTERS & CHEMICAL ENGINEERING

Fault Detection Method Using Multi-mode Principal Component Analysis Based on Gaussian Mixture Model for Sewage Source Heat Pump System

(2019) Young-Jun Yoo   INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS

A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures

(2019) Yong Yu et al.   NEURAL COMPUTATION

Data-driven monitoring of multimode continuous processes: A review

(2019) Marcos Quiñones-Grueiro et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

A novel process monitoring approach based on variational recurrent autoencoder

(2019) Feifan Cheng et al.   COMPUTERS & CHEMICAL ENGINEERING

A New Online Detection Approach for Rolling Bearing Incipient Fault via Self-Adaptive Deep Feature Matching

(2019) Wentao Mao et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Nonstationary Discrete Convolution Kernel for Multimodal Process Monitoring

(2019) Ruomu Tan et al.   IEEE Transactions on Neural Networks and Learning Systems

Mixtures of Probabilistic PCA With Common Structure Latent Bases for Process Monitoring

(2018) Hariprasad Kodamana et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY

Wind Turbine Fault Detection Using a Denoising Autoencoder With Temporal Information

(2018) Guoqian Jiang et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

Online reduced kernel principal component analysis for process monitoring

(2018) Radhia Fezai et al.   JOURNAL OF PROCESS CONTROL

Automated feature learning for nonlinear process monitoring – An approach using stacked denoising autoencoder and k-nearest neighbor rule

(2018) Zehan Zhang et al.   JOURNAL OF PROCESS CONTROL

A review on the application of deep learning in system health management

(2018) Samir Khan et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Representation learning based adaptive multimode process monitoring

(2018) Feiya Lv et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

A Multi-mode Incipient Sensor Fault Detection and Diagnosis Method for Electrical Traction Systems

(2018) Hongtian Chen et al.   INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS

Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0

(2018) Alberto Diez-Olivan et al.   Information Fusion

Enhancing dynamic soft sensors based on DPLS: A temporal smoothness regularization approach

(2015) Chao Shang et al.   JOURNAL OF PROCESS CONTROL

A Review on Basic Data-Driven Approaches for Industrial Process Monitoring

(2014) Shen Yin et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

An efficient multi-PCA based on-line monitoring scheme for multi-stages imperial smelting process

(2013) Zhi-kun Hu et al.   INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS

Survey on data-driven industrial process monitoring and diagnosis

(2012) S. Joe Qin   ANNUAL REVIEWS IN CONTROL

A novel process monitoring approach with dynamic independent component analysis

(2009) Chun-Chin Hsu et al.   CONTROL ENGINEERING PRACTICE

Nonlinear Dynamic Process Monitoring Using Canonical Variate Analysis and Kernel Density Estimations

(2009) P.-E.P. Odiowei et al.   IEEE Transactions on Industrial Informatics