Multi-lag and multi-type temporal causality inference and analysis for industrial process fault diagnosis-Reference-Cited by-同舟云学术

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

Published:2022-07 Issue: Volume:124 Page:105174
ISSN:0967-0661
Container-title:Control Engineering Practice
language:en
Short-container-title:Control Engineering Practice

Author:

Chen Jiawei,Zhao Chunhui

Funder

State Key Laboratory of Synthetical Automation for Process Industries

State Key Laboratory of Industrial Control Technology

Zhejiang University

China National Funds for Distinguished Young Scientists

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference46 articles.

1. Arnold, A., Liu, Y., & Abe, N. (2007). Temporal causal modeling with graphical granger methods. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 66-75).

2. The MVGC multivariate granger causality toolbox: a new approach to granger-causal inference;Barnett;Journal of Neuroscience Methods,2014

3. Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition;Büyükşahin;Neurocomputing,2019

4. Detection and root cause analysis of multiple plant-wide oscillations using multivariate nonlinear chirp mode decomposition and multivariate granger causality;Chen;Computers & Chemical Engineering,2021

5. Systematic procedure for granger-causality-based root cause diagnosis of chemical process faults;Chen;Industrial and Engineering Chemistry Research,2018

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