Large-scale chemical process causal discovery from big data with transformer-based deep learning

Survey and Evaluation of Causal Discovery Methods for Time Series

(2022) Charles K. Assaad et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

A data-driven Bayesian network model integrating physical knowledge for prioritization of risk influencing factors

(2022) Huixing Meng et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

One step forward for smart chemical process fault detection and diagnosis

(2022) Xiaotian Bi et al.   COMPUTERS & CHEMICAL ENGINEERING

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

(2022) Jiawei Chen et al.   CONTROL ENGINEERING PRACTICE

Fault detection and diagnosis using Bayesian network model combining mechanism correlation analysis and process data: Application to unmonitored root cause variables type faults

(2022) Nan Liu et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

A novel transformer-based multi-variable multi-step prediction method for chemical process fault prognosis

(2022) Yiming Bai et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

A data-driven Bayesian network learning method for process fault diagnosis

(2021) Md. Tanjin Amin et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Process topology convolutional network model for chemical process fault diagnosis

(2021) Deyang Wu et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

A method for detecting causal relationships between industrial alarm variables using Transfer Entropy and K2 algorithm

(2021) Rute Souza de Abreu et al.   JOURNAL OF PROCESS CONTROL

Causal inference for time series analysis: problems, methods and evaluation

(2021) Raha Moraffah et al.   KNOWLEDGE AND INFORMATION SYSTEMS

A novel orthogonal self-attentive variational autoencoder method for interpretable chemical process fault detection and identification

(2021) Xiaotian Bi et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Attention-based Long Short-term Memory Method for Alarm Root-Cause Diagnosis in Chemical Processes

(2020) Rui He et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms

(2020) Angela Stallone et al.   Scientific Reports

An analysis of process fault diagnosis methods from safety perspectives

(2020) Rajeevan Arunthavanathan et al.   COMPUTERS & CHEMICAL ENGINEERING

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

MONITORING NONSTATIONARY PROCESSES USING STATIONARY SUBSPACE ANALYSIS AND FRACTIONAL INTEGRATION ORDER ESTIMATION

(2019) Yuanling Lin et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

A novel fault identification and root-causality analysis of incipient faults with applications to wastewater treatment processes

(2019) Hongchao Cheng et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Detecting and quantifying causal associations in large nonlinear time series datasets

(2019) Jakob Runge et al.   Science Advances

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

(2019) Chao Shang et al.   Engineering

Root causality analysis at early abnormal stage using principal component analysis and multivariate Granger causality

(2019) Hahyung Pyun et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Process system fault detection and diagnosis using a hybrid technique

(2018) Md. Tanjin Amin et al.   CHEMICAL ENGINEERING SCIENCE

Systematic Procedure for Granger-Causality-Based Root Cause Diagnosis of Chemical Process Faults

(2018) Han-Sheng Chen et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Causal network reconstruction from time series: From theoretical assumptions to practical estimation

(2018) J. Runge   CHAOS

Causal decomposition in the mutual causation system

(2018) Albert C. Yang et al.   Nature Communications

Early Fault Detection Method for Rotating Machinery Based on Harmonic-Assisted Multivariate Empirical Mode Decomposition and Transfer Entropy

(2018) Zhe Wu et al.   Entropy

Improved CCM for variable causality detection in complex systems

(2018) Yalin Wang et al.   CONTROL ENGINEERING PRACTICE

Causal inference from noisy time-series data — Testing the Convergent Cross-Mapping algorithm in the presence of noise and external influence

(2017) Dan Mønster et al.   Future Generation Computer Systems-The International Journal of eScience

Root Cause Diagnosis of Process Fault Using KPCA and Bayesian Network

(2017) H. Gharahbagheri et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Transfer entropy coefficient: Quantifying level of information flow between financial time series

(2017) Yue Teng et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

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

(2017) Marco Reis et al.   Processes

Data-driven root cause diagnosis of faults in process industries

(2016) Gang Li et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Abnormal situation management: Challenges and opportunities in the big data era

(2016) Yidan Shu et al.   COMPUTERS & CHEMICAL ENGINEERING

Methods and models in process safety and risk management: Past, present and future

(2015) Faisal Khan et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Distinguishing time-delayed causal interactions using convergent cross mapping

(2015) Hao Ye et al.   Scientific Reports

A novel dynamic bayesian network-based networked process monitoring approach for fault detection, propagation identification, and root cause diagnosis

(2013) Jie Yu et al.   AICHE JOURNAL

Detecting Causality in Complex Ecosystems

(2012) G. Sugihara et al.   SCIENCE