Nonlinear industrial process fault diagnosis with latent label consistency and sparse Gaussian feature learning

Machine learning based online fault prognostics for nonstationary industrial process via degradation feature extraction and temporal smoothness analysis

(2022) Yun-yun Hu et al.   Journal of Central South University

Multi-lag and multi-type temporal causality inference and analysis for industrial process fault diagnosis

(2022) Jiawei Chen et al.   CONTROL ENGINEERING PRACTICE

Multisource-Refined Transfer Network for Industrial Fault Diagnosis Under Domain and Category Inconsistencies

(2021) Zheng Chai et al.   IEEE Transactions on Cybernetics

Deep learning for fault-relevant feature extraction and fault classification with stacked supervised auto-encoder

(2020) Yalin Wang et al.   JOURNAL OF PROCESS CONTROL

Semi-Supervised Bearing Fault Diagnosis and Classification Using Variational Autoencoder-Based Deep Generative Models

(2020) Shen Zhang et al.   IEEE SENSORS JOURNAL

Fault Description Based Attribute Transfer for Zero-Sample Industrial Fault Diagnosis

(2020) Liangjun Feng et al.   IEEE Transactions on Industrial Informatics

Fault Diagnosis of an Autonomous Vehicle With an Improved SVM Algorithm Subject to Unbalanced Datasets

(2020) Qian Shi et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Using Labeled Autoencoder to Supervise Neural Network Combined with k-Nearest Neighbor for Visual Industrial Process Monitoring

(2019) Shifu Yan et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

A new approach for on-line open-circuit fault diagnosis of inverters based on current trajectory

(2019) Kai-di Li et al.   Journal of Central South University

A novel sparse filtering approach based on time-frequency feature extraction and softmax regression for intelligent fault diagnosis under different speeds

(2019) Zhong-wei Zhang et al.   Journal of Central South University

Representation Learning With Class Level Autoencoder for Intelligent Fault Diagnosis

(2019) Hui Yu et al.   IEEE SIGNAL PROCESSING LETTERS

A method combining refined composite multiscale fuzzy entropy with PSO-SVM for roller bearing fault diagnosis

(2019) Fan Xu et al.   Journal of Central South University

Enhanced Random Forest With Concurrent Analysis of Static and Dynamic Nodes for Industrial Fault Classification

(2019) Zheng Chai et al.   IEEE Transactions on Industrial Informatics

Robust Monitoring and Fault Isolation of Nonlinear Industrial Processes Using Denoising Autoencoder and Elastic Net

(2019) Wanke Yu et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY

Broad Convolutional Neural Network Based Industrial Process Fault Diagnosis With Incremental Learning Capability

(2019) Wanke Yu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Sparse Exponential Discriminant Analysis and Its Application to Fault Diagnosis

(2018) Wanke Yu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Deep PCA Based Real-Time Incipient Fault Detection and Diagnosis Methodology for Electrical Drive in High-Speed Trains

(2018) Hongtian Chen et al.   IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY

Fault Diagnosis Based on Weighted Extreme Learning Machine with Wavelet Packet Decomposition and KPCA

(2018)   IEEE SENSORS JOURNAL

Fault Diagnosis of a Rolling Bearing Using Wavelet Packet Denoising and Random Forests

(2017) Ziwei Wang et al.   IEEE SENSORS JOURNAL

A novel deep autoencoder feature learning method for rotating machinery fault diagnosis

(2017) Haidong Shao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification

(2017) Chen Lu et al.   SIGNAL PROCESSING

Industrial Process Monitoring in the Big Data/Industry 4.0 Era: from Detection, to Diagnosis, to Prognosis

(2017) Marco Reis et al.   Processes

Fault Diagnosis Method of Joint Fisher Discriminant Analysis Based on the Local and Global Manifold Learning and Its Kernel Version

(2016) Jian Feng et al.   IEEE Transactions on Automation Science and Engineering

Improved PLS Focused on Key-Performance-Indicator-Related Fault Diagnosis

(2015) Shen Yin et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Comprehensive Subspace Decomposition with Analysis of Between-Mode Relative Changes for Multimode Process Monitoring

(2015) Chunhui Zhao et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Nonlinear Gaussian Belief Network based fault diagnosis for industrial processes

(2015) Hongyang Yu et al.   JOURNAL OF PROCESS CONTROL

An Adaptive Approach Based on KPCA and SVM for Real-Time Fault Diagnosis of HVCBs

(2011) Jianjun Ni et al.   IEEE TRANSACTIONS ON POWER DELIVERY

On the application of PCA technique to fault diagnosis

(2010) S Ding et al.   TSINGHUA SCIENCE AND TECHNOLOGY