﻿ 系统故障因果关系分析的智能驱动方式研究
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 智能系统学报  2021, Vol. 16 Issue (1): 92-97  DOI: 10.11992/tis.202003001 0

### 引用本文

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.

### 文章历史

1. 辽宁工程技术大学 安全科学与工程学院，辽宁 阜新 123000;
2. 辽宁工程技术大学 工商管理学院，辽宁 葫芦岛 125105

Intelligent analysis of system fault data and fault causal relationship
CUI Tiejun 1, LI Shasha 2
1. College of Safety Science and Engineering, Liaoning Technical University, Fuxin 123000, China;
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.
Key words: safety system engineering    fault data    causal relationship    intelligent science    intelligent analysis    space fault tree    factor space    driving mode

1 故障数据的数理统计

2 系统故障的相关性和关联性

3 故障因果分析的4个驱动层次

3.1 数据驱动

3.2 因素驱动

3.3 数据−因素驱动

3.4 数据−因素−假设驱动

4 结束语

1)论述了目前分析系统故障数据面临的问题。基于数理统计的故障数据分析应用广泛，但只能得到数据层面的因果关系。可能只是表面关系，不是本质关系，也可能是经过了多次因果传递后表现出来的关系。这不利于系统故障的预测、预防与治理。

2)论述了系统故障因果关系的关联性和相关性。关联性存在于概念，取决于知识和概念层面的意义，是广义因果论。相关性在于具体的数据层面，通过数据分析得到不同类型数据之间的关系，是狭义因果论。因素空间承认狭义因果论和广义因果论，并在因素层面上讨论因果关系。

3)将系统故障分析的智能系统划分为4个层次，数据驱动、因素驱动、数据−因素驱动、数据−因素−假设驱动。数据驱动能获得广泛的故障因果关系，因素驱动深入了解故障因果关系，数据−因素驱动兼顾两者，数据−因素−假设驱动更接近于人的思维。

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