Fault Diagnosis of Complex Chemical Processes Using Feature Fusion of a Convolutional Network

Visualization analysis for fault diagnosis in chemical processes using recurrent neural networks

(2020) Jia-Lin Kang   Journal of the Taiwan Institute of Chemical Engineers

A novel deep learning based fault diagnosis approach for chemical process with extended deep belief network

(2019) Yalin Wang et al.   ISA TRANSACTIONS

Bidirectional Recurrent Neural Network-Based Chemical Process Fault Diagnosis

(2019) Shuyuan Zhang et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method

(2018) Long Wen et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Fault Diagnosis for Rotating Machinery Using Multiple Sensors and Convolutional Neural Networks

(2018) Min Xia et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

Analog Circuit Incipient Fault Diagnosis Method Using DBN Based Features Extraction

(2018) Chaolong Zhang et al.   IEEE Access

Data-Based Line Trip Fault Prediction in Power Systems Using LSTM Networks and SVM

(2018) Senlin Zhang et al.   IEEE Access

Machine Health Monitoring Using Adaptive Kernel Spectral Clustering and Deep Long Short-Term Memory Recurrent Neural Networks

(2018)   IEEE Transactions on Industrial Informatics

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data

(2018) Liang Guo et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

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

(2017) Chen Lu et al.   SIGNAL PROCESSING

A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis

(2017) Long Wen et al.   IEEE Transactions on Systems Man Cybernetics-Systems

An improved weighted recursive PCA algorithm for adaptive fault detection

(2016) Ivan Portnoy et al.   CONTROL ENGINEERING PRACTICE

Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

(2016) Feng Jia et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Recent advances on SVM based fault diagnosis and process monitoring in complicated industrial processes

(2016) Zuyu Yin et al.   NEUROCOMPUTING

Free-Form Region Description with Second-Order Pooling

(2015) Joao Carreira et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

An LWPR-Based Data-Driven Fault Detection Approach for Nonlinear Process Monitoring

(2014) Guang Wang et al.   IEEE Transactions on Industrial Informatics

Data-driven soft sensor development based on deep learning technique

(2014) Chao Shang et al.   JOURNAL OF PROCESS CONTROL

From Model, Signal to Knowledge: A Data-Driven Perspective of Fault Detection and Diagnosis

(2013) Xuewu Dai et al.   IEEE Transactions on Industrial Informatics

Failure diagnosis using deep belief learning based health state classification

(2013) Prasanna Tamilselvan et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Early fault diagnosis of rotating machinery based on wavelet packets—Empirical mode decomposition feature extraction and neural network

(2011) G.F. Bin et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Fault diagnosis of nonlinear processes using multiscale KPCA and multiscale KPLS

(2010) Yingwei Zhang et al.   CHEMICAL ENGINEERING SCIENCE