A Review on Data‐Driven Learning Approaches for Fault Detection and Diagnosis in Chemical Processes

A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification

(2020) B. Kamaruddin et al.   JOURNAL OF PROCESS CONTROL

Leak Detection in Gas Mixture Pipelines under Transient Conditions Using Hammerstein Model and Adaptive Thresholds

(2020) Syed Muhammad Mujtaba et al.   Processes

Manifold regularized stacked autoencoders-based feature learning for fault detection in industrial processes

(2020) Jianbo Yu et al.   JOURNAL OF PROCESS CONTROL

A Feed-Forward Back Propagation Neural Network Approach to Predict the Life Condition of Crude Oil Pipeline

(2020) Nagoor Basha Shaik et al.   Processes

Machine learning and reasoning for predictive maintenance in Industry 4.0: Current status and challenges

(2020) Jovani Dalzochio et al.   COMPUTERS IN INDUSTRY

Sparse Robust Principal Component Analysis with Applications to Fault Detection and Diagnosis

(2019) Lijia Luo et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

A review of data-driven fault detection and diagnosis methods: applications in chemical process systems

(2019) Norazwan Md Nor et al.   REVIEWS IN CHEMICAL ENGINEERING

Fault Detection of a Spherical Tank Using a Genetic Algorithm-Based Hybrid Feature Pool and k-Nearest Neighbor Algorithm

(2019) Md Hasan et al.   Energies

Innovative data regression incorporating deterministic knowledge for soft sensing in the process industry

(2019) Edoardo Copertaro et al.   JOURNAL OF PROCESS CONTROL

Understanding autoencoders with information theoretic concepts

(2019) Shujian Yu et al.   NEURAL NETWORKS

Mechanical fault diagnosis using Convolutional Neural Networks and Extreme Learning Machine

(2019) Zhuyun Chen et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Big data approach to batch process monitoring: Simultaneous fault detection and diagnosis using nonlinear support vector machine-based feature selection

(2018) Melis Onel et al.   COMPUTERS & CHEMICAL ENGINEERING

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

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

Bearing remaining useful life prediction based on deep autoencoder and deep neural networks

(2018) Lei Ren et al.   JOURNAL OF MANUFACTURING SYSTEMS

A Fault Detection and Health Monitoring Scheme for Ship Propulsion Systems Using SVM Technique

(2018) Jing Zhou et al.   IEEE Access

Multiple Fault Diagnosis in Distillation Column using Multi-Kernel Support Vector Machine

(2018) Syed A. Taqvi et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Fault detection in distillation column using NARX neural network

(2018) Syed A. Taqvi et al.   NEURAL COMPUTING & APPLICATIONS

Data-driven soft sensor modeling based on twin support vector regression for cane sugar crystallization

(2018) Yanmei Meng et al.   JOURNAL OF FOOD ENGINEERING

Neural network applications in fault diagnosis and detection: an overview of implementations in engineering-related systems

(2018) Ahmad Azharuddin Azhari Mohd Amiruddin et al.   NEURAL COMPUTING & APPLICATIONS

A Bayesian network-based approach for fault analysis

(2017) Hong-Bae Jun et al.   EXPERT SYSTEMS WITH APPLICATIONS

A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes

(2017) Ki Bum Lee et al.   IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING

Pseudo Time-Slice Construction Using a Variable Moving Window k Nearest Neighbor Rule for Sequential Uneven Phase Division and Batch Process Monitoring

(2017) Shumei Zhang et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Weighted time series fault diagnosis based on a stacked sparse autoencoder

(2017) Feiya Lv et al.   JOURNAL OF CHEMOMETRICS

Coupled Deep Autoencoder for Single Image Super-Resolution

(2017) Kun Zeng et al.   IEEE Transactions on Cybernetics

Data Mining and Analytics in the Process Industry: The Role of Machine Learning

(2017) Zhiqiang Ge et al.   IEEE Access

Big Data in the construction industry: A review of present status, opportunities, and future trends

(2016) Muhammad Bilal et al.   ADVANCED ENGINEERING INFORMATICS

Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: A review of researches and future challenges

(2016) Khaoula Tidriri et al.   ANNUAL REVIEWS IN CONTROL

Design of deep convolutional neural network architectures for automated feature extraction in industrial inspection

(2016) Daniel Weimer et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

Semisupervised Kernel Learning for FDA Model and its Application for Fault Classification in Industrial Processes

(2016) Zhiqiang Ge et al.   IEEE Transactions on Industrial Informatics

PCA-ICA Integrated with Bayesian Method for Non-Gaussian Fault Diagnosis

(2016) Qingchao Jiang et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Convolutional Neural Network Based Fault Detection for Rotating Machinery

(2016) Olivier Janssens et al.   JOURNAL OF SOUND AND VIBRATION

String representations and distances in deep Convolutional Neural Networks for image classification

(2016) Cécile Barat et al.   PATTERN RECOGNITION

Diagnostic Bayesian networks for diagnosing air handling units faults – Part II: Faults in coils and sensors

(2015) Yang Zhao et al.   APPLIED THERMAL ENGINEERING

A combined canonical variate analysis and Fisher discriminant analysis (CVA–FDA) approach for fault diagnosis

(2015) Benben Jiang et al.   COMPUTERS & CHEMICAL ENGINEERING

WPD-PCA-Based Laser Welding Process Monitoring and Defects Diagnosis by Using FNN and SVM

(2015) Deyong You et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Tool condition monitoring (TCM) using neural networks

(2015) Tien-I Liu et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Application of higher order spectral features and support vector machines for bearing faults classification

(2015) Lotfi Saidi et al.   ISA TRANSACTIONS

Online monitoring and control of particle size in the grinding process using least square support vector regression and resilient back propagation neural network

(2015) Ajaya Kumar Pani et al.   ISA TRANSACTIONS

Dynamic neural networks for gas turbine engine degradation prediction, health monitoring and prognosis

(2015) S. Kiakojoori et al.   NEURAL COMPUTING & APPLICATIONS

SVM and PCA based fault classification approaches for complicated industrial process

(2015) Chen Jing et al.   NEUROCOMPUTING

Steel plates fault diagnosis on the basis of support vector machines

(2015) Yang Tian et al.   NEUROCOMPUTING

A Bayesian network dealing with measurements and residuals for system monitoring

(2015) Mohamed Amine Atoui et al.   TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL

Simultaneous Fault Diagnosis using multi class support vector machine in a Dew Point process

(2015) Navid Pooyan et al.   Journal of Natural Gas Science and Engineering

Generalized neural network and wavelet transform based approach for fault location estimation of a transmission line

(2014) Majid Jamil et al.   APPLIED SOFT COMPUTING

Prediction of particulate matter at street level using artificial neural networks coupling with chaotic particle swarm optimization algorithm

(2014) Hong-di He et al.   BUILDING AND ENVIRONMENT

Diffusion maps based k-nearest-neighbor rule technique for semiconductor manufacturing process fault detection

(2014) Yuan Li et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Modeling and predicting the occurrence of brain metastasis from lung cancer by Bayesian network: A case study of Taiwan

(2014) Kung-Jeng Wang et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Development and validation of artificial neural network models of the energy demand in the industrial sector of the United States

(2014) Arash Kialashaki et al.   ENERGY

Improved decision tree construction based on attribute selection and data sampling for fault diagnosis in rotating machines

(2014) Nour El Islem Karabadji et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Incipient fault diagnosis using support vector machines based on monitoring continuous decision functions

(2014) Mehdi Namdari et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Neural networks for analyzing service quality in public transportation

(2014) Concepción Garrido et al.   EXPERT SYSTEMS WITH APPLICATIONS

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

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

Gray-box modeling for prediction and control of molten steel temperature in tundish

(2014) Iftikhar Ahmad et al.   JOURNAL OF PROCESS CONTROL

Artificial neural network approaches for fault classification: comparison and performance

(2014) Tapsi Nagpal et al.   NEURAL COMPUTING & APPLICATIONS

Melt index prediction by fuzzy functions with dynamic fuzzy neural networks

(2014) Senqi Xu et al.   NEUROCOMPUTING

A COMBINATION OF SUPPORT VECTOR MACHINE AND k-NEAREST NEIGHBORS FOR MACHINE FAULT DETECTION

(2013) Amaury B. Andre et al.   APPLIED ARTIFICIAL INTELLIGENCE

Fault detection and identification spanning multiple processes by integrating PCA with neural network

(2013) Jing Zhou et al.   APPLIED SOFT COMPUTING

Fault detection and classification in chemical processes using NMFSC and structural SVMs

(2013) Yi Peng et al.   CANADIAN JOURNAL OF CHEMICAL ENGINEERING

RBF neural network inferential sensor for process emission monitoring

(2013) Surajdeen A. Iliyas et al.   CONTROL ENGINEERING PRACTICE

An Online Fault Diagnosis Strategy for Full Operating Cycles of Chemical Processes

(2013) Jinsong Zhao et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Review of Recent Research on Data-Based Process Monitoring

(2013) Zhiqiang Ge et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

An approach for automated fault diagnosis based on a fuzzy decision tree and boundary analysis of a reconstructed phase space

(2013) Ilhan Aydin et al.   ISA TRANSACTIONS

Bayesian Networks for Clinical Decision Support in Lung Cancer Care

(2013) M. Berkan Sesen et al.   PLoS One

Model selection and fault detection approach based on Bayes decision theory: Application to changes detection problem in a distillation column

(2013) Yahya Chetouani   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Survey on data-driven industrial process monitoring and diagnosis

(2012) S. Joe Qin   ANNUAL REVIEWS IN CONTROL

Dynamic processes monitoring using recursive kernel principal component analysis

(2012) Yingwei Zhang et al.   CHEMICAL ENGINEERING SCIENCE

Fault diagnosis of Tennessee Eastman process with multi-scale PCA and ANFIS

(2012) C.K. Lau et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

An intelligent chiller fault detection and diagnosis methodology using Bayesian belief network

(2012) Yang Zhao et al.   ENERGY AND BUILDINGS

Hybrid Incremental Modeling Based on Least Squares and Fuzzy $K$-NN for Monitoring Tool Wear in Turning Processes

(2012) Francisco Penedo et al.   IEEE Transactions on Industrial Informatics

Fault diagnosis on production systems with support vector machine and decision trees algorithms

(2012) M. Demetgul   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A hybrid approach to faults detection and diagnosis in batch and semi-batch reactors by using EKF and neural network classifier

(2012) A.M. Benkouider et al.   JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES

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

Model-based robust fault detection and isolation of an industrial gas turbine prototype using soft computing techniques

(2012) Hasan Abbasi Nozari et al.   NEUROCOMPUTING

Unified model-based fault diagnosis for three industrial application studies

(2011) Udo Schubert et al.   CONTROL ENGINEERING PRACTICE

Online monitoring and fault identification of mean shifts in bivariate processes using decision tree learning techniques

(2011) Shu-Guang He et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Bayesian Belief Network-based approach for diagnostics and prognostics of semiconductor manufacturing systems

(2011) Lei Yang et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Statistics pattern analysis: A new process monitoring framework and its application to semiconductor batch processes

(2010) Q. Peter He et al.   AICHE JOURNAL

Fault diagnosis based on imbalance modified kernel Fisher discriminant analysis

(2010) Zhi-Bo Zhu et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

A semi-supervised approach to fault diagnosis for chemical processes

(2010) Isaac Monroy et al.   COMPUTERS & CHEMICAL ENGINEERING

Effective fault detection and isolation using bond graph-based domain decomposition

(2010) Xi Zhang et al.   COMPUTERS & CHEMICAL ENGINEERING

Fault diagnosis of industrial systems by conditional Gaussian network including a distance rejection criterion

(2010) Sylvain Verron et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A novel fault diagnosis system using pattern classification on kernel FDA subspace

(2010) Zhi-Bo Zhu et al.   EXPERT SYSTEMS WITH APPLICATIONS

Process Monitoring, Fault Diagnosis and Quality Prediction Methods Based on the Multivariate Statistical Techniques

(2010) Yingwei Zhang et al.   IETE TECHNICAL REVIEW

Unsupervised Process Fault Detection with Random Forests

(2010) Lidia Auret et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Nearest-Neighbor Method for the Automatic Maintenance of Multivariate Statistical Soft Sensors in Batch Processing

(2010) Pierantonio Facco et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Using neural network and decision tree for machine reliability prediction

(2010) Yiyo Kuo et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Induction motor fault diagnosis based on thek-NN and optimal feature selection

(2010) Ngoc-Tu Nguyen et al.   INTERNATIONAL JOURNAL OF ELECTRONICS

Fault detection and isolation of faults in a multivariate process with Bayesian network

(2010) Sylvain Verron et al.   JOURNAL OF PROCESS CONTROL

A fuzzy decision tree method for fault classification in the steam generator of a pressurized water reactor

(2009) Enrico Zio et al.   ANNALS OF NUCLEAR ENERGY

A survey on multistage/multiphase statistical modeling methods for batch processes

(2009) Yuan Yao et al.   ANNUAL REVIEWS IN CONTROL

Fault Detection and Diagnosis in a Sour Gas Absorption Column Using Neural Networks

(2009) R. M. Behbahani et al.   CHEMICAL ENGINEERING & TECHNOLOGY

Moving window kernel PCA for adaptive monitoring of nonlinear processes

(2009) Xueqin Liu et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Inductive data mining based on genetic programming: Automatic generation of decision trees from data for process historical data analysis

(2009) Chao Y. Ma et al.   COMPUTERS & CHEMICAL ENGINEERING

Data-driven Soft Sensors in the process industry

(2009) Petr Kadlec et al.   COMPUTERS & CHEMICAL ENGINEERING

Boosting k-nearest neighbor classifier by means of input space projection

(2009) Nicolás García-Pedrajas et al.   EXPERT SYSTEMS WITH APPLICATIONS

Random forests classifier for machine fault diagnosis

(2009) Bo-Suk Yang et al.   Journal of Mechanical Science and Technology

Fault detection and diagnosis in process data using one-class support vector machines

(2009) Sankar Mahadevan et al.   JOURNAL OF PROCESS CONTROL

Enhanced statistical analysis of nonlinear processes using KPCA, KICA and SVM

(2008) Yingwei Zhang   CHEMICAL ENGINEERING SCIENCE

Performance assessment of a novel fault diagnosis system based on support vector machines

(2008) Ignacio Yélamos et al.   COMPUTERS & CHEMICAL ENGINEERING

ANN-based soft-sensor for real-time process monitoring and control of an industrial polymerization process

(2008) J.C.B. Gonzaga et al.   COMPUTERS & CHEMICAL ENGINEERING

Fault Detection and Diagnosis of Nonlinear Processes Using Improved Kernel Independent Component Analysis (KICA) and Support Vector Machine (SVM)

(2008) Yingwei Zhang   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Random forests and nearest shrunken centroids for the classification of sensor array data

(2008) Matteo Pardo et al.   SENSORS AND ACTUATORS B-CHEMICAL

Artificial neural network approach for fault detection in rotary system

(2007) S. Rajakarunakaran et al.   APPLIED SOFT COMPUTING

Data-based process monitoring, process control, and quality improvement: Recent developments and applications in steel industry

(2007) Manabu Kano et al.   COMPUTERS & CHEMICAL ENGINEERING

Using neural network ensembles for bankruptcy prediction and credit scoring

(2007) C TSAI et al.   EXPERT SYSTEMS WITH APPLICATIONS

Fault detection and identification with a new feature selection based on mutual information

(2007) Sylvain Verron et al.   JOURNAL OF PROCESS CONTROL

Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance

(2007) Maciej A. Mazurowski et al.   NEURAL NETWORKS