Risk-based fault detection and diagnosis for nonlinear and non-Gaussian process systems using R-vine copula

Modeling and Testing of Temporal Dependency in the Failure of a Process System

(2019) Arko Ghosh et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Nonlinear and Non-Gaussian Process Monitoring Based on Simplified R-Vine Copula

(2018) Nan Zhou et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Modeling and application of industrial process fault detection based on pruning vine copula

(2018) Junxia Wan et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Data-driven root cause diagnosis of faults in process industries

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

Vine Copula-Based Dependence Description for Multivariate Multimode Process Monitoring

(2015) Xiang Ren et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Truncation of vine copulas using fit indices

(2015) Eike C. Brechmann et al.   JOURNAL OF MULTIVARIATE ANALYSIS

Risk-based fault detection using Self-Organizing Map

(2015) Hongyang Yu et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Truncated regular vines in high dimensions with application to financial data

(2012) E. C. Brechmann et al.   CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE

Dynamic Risk Assessment and Fault Detection Using Principal Component Analysis

(2012) O. Zadakbar et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

SHIPP methodology: Predictive accident modeling approach. Part I: Methodology and model description

(2011) Samith Rathnayaka et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Fault Detection of Non-Linear Processes Using Kernel Independent Component Analysis

(2010) Jong-Min Lee et al.   CANADIAN JOURNAL OF CHEMICAL ENGINEERING

Dynamic risk assessment using failure assessment and Bayesian theory

(2009) Maryam Kalantarnia et al.   JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES

Pair-copula constructions of multiple dependence

(2007) Kjersti Aas et al.   INSURANCE MATHEMATICS & ECONOMICS