Statistical root cause analysis of novel faults based on digraph models

Chemical Engineering Research and Design

Volumn 91, Issue 1, 2013, Pages 87-99

  Wan, Yiming ^a   Yang, Fan ^a   Lv, Ning ^a   Xu, Haipeng ^a   Ye, Hao ^a   Li, Weichang ^b   Xu, Peng ^b   Song, Liming ^b   Usadi, Adam K ^b  

^a TSINGHUA UNIVERSITY   (China)

^b EXXONMOBIL UPSTREAM RESEARCH COMPANY   (United States)

Author keywords

Causal reasoning; Digraph model; Fault diagnosis; Multivariate statistical process monitoring; Novel fault

Indexed keywords

CAUSAL REASONING; CAUSE-EFFECT RELATIONSHIPS; DIGRAPH MODELS; FAULT DIAGNOSIS SYSTEMS; FAULT MECHANISM; FAULTY CONDITION; HISTORICAL DATA; LOCAL CONSISTENCY; MULTIVARIATE STATISTICAL PROCESS MONITORING; NOVEL FAULT; NUMERICAL EXAMPLE; PROCESS BEHAVIOR; PROCESS FLOW DIAGRAMS; QUALITATIVE REASONING; ROOT CAUSE; ROOT CAUSE ANALYSIS; ROOT NODES; STATISTICAL MONITORING; TENNESSEE EASTMAN PROCESS; VARIABLE SELECTION;

ARTIFICIAL INTELLIGENCE; FAILURE ANALYSIS;

DIRECTED GRAPHS;

EID: 84871924235     PISSN: 02638762     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cherd.2012.06.010     Document Type: Article

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