[1]CUI Tiejun,LI Shasha.Intelligent analysis of system fault data and fault causal relationship[J].CAAI Transactions on Intelligent Systems,2021,16(1):92-97.[doi:10.11992/tis.202003001]
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Intelligent analysis of system fault data and fault causal relationship

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 16 Number of periods: 2021 1 Page number: 92-97 Column: 学术论文—智能系统 Public date: 2021-01-05
Title:
Intelligent analysis of system fault data and fault causal relationship
Author(s):
CUI Tiejun1;  LI Shasha2
1. College of Safety Science and Engineering, Liaoning Technical University, Fuxin 123000, China;
2. School of business administration, Liaoning Technical University, Huludao 125105, China
Keywords:
safety system engineering; fault data; causal relationship; intelligent science; intelligent analysis; space fault tree; factor space; driving mode
CLC:
X913;C931.1;TP18
DOI:
10.11992/tis.202003001
Abstract:
To meet the needs of fault data analysis in the future intelligent environment and safety field, we propose the idea of causal relationship analysis of system fault. First, the problems existing in the analysis of system fault data by mathematical statistics are discussed, the correlation and relevance of system fault are studied, showing that the former is based on faulty data, reflecting the fault representation; the latter is based on fault concept, reflecting fault essence. The fault causal analysis in the intelligent situation is divided into four levels: data driven, factor driven, data-factor driven, and data-factor-hypothesis driven. Their characteristics are to separately obtain and understand a wide range of fault causal relationships, both considering and closer to human thought. The ability of the four drivers to analyze the fault causal relationship increases in turn, it can provide a channel for combining safety science and intelligent science.
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