﻿ 安全科学中的故障信息转换定律
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 智能系统学报  2020, Vol. 15 Issue (2): 360-366  DOI: 10.11992/tis.201811004 0

### 引用本文

CUI Tiejun, LI Shasha. Conversion law of fault information in safety science[J]. CAAI Transactions on Intelligent Systems, 2020, 15(2): 360-366. DOI: 10.11992/tis.201811004.

### 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. 大连交通大学，辽宁省隧道与地下结构工程技术研究中心，辽宁 大连 116028;
3. 辽宁工程技术大学，工商管理学院，辽宁 葫芦岛 125105

Conversion law of fault information in safety science
CUI Tiejun 1,2, LI Shasha 3
1. College of Safety Science and Engineering, Liaoning Technical University, Fuxin 123000, China;
2. Tunnel and Underground Structure Engineering Center of Liaoning, Dalian Jiaotong University, Dalian 116028 China;
Abstract: To obtain fault information and enable safety decision-making in safety science, this study proposes the conversion law of fault information in safety science. System reliability is a core concept of safety science. With the development of information and intelligent science, the theory of system reliability should also be developed. Information ecology methodology is different from traditional mechanical reductionism and can be used to conduct comprehensive research on fault information. Factor space theory is the mathematical basis of intelligent science based on factors. Space fault tree theory is a systematic scientific method used to analyze the relationship between reliability and factors. Therefore, these three methods enable the natural integration of research factors, system changes, and their characteristics. The methodology, intelligent mathematics foundation, and specific implementation platform for the analysis of system reliability are provided herein. Information ecology methodology and factor space theory can guide and integrate the development of a space fault tree. This paper provides the basic theory of safety science with information and intelligent science for system reliability analysis concepts and methods. Moreover, it attempts to integrate information and intelligent science with safety science.
Key words: safety science    intelligent science    data science    information ecological methodology    factor space    space fault tree    conversion law of fault information    system reliability

1 信息生态方法论概述

2 智能的机制主义及数学原理与故障信息处理

3 空间故障树框架内的故障信息转换定律

4 结束语

1)总结已有文献，给出信息生态系统的论述和定义。

2)研究了智能的机制主义及数学原理与安全信息处理相融合的可能性。将信息生态方法论作为安全科学中系统可靠性研究领域故障信息处理的方法论；将因素空间理论作为故障信息智能处理的数学基础；而将空间故障树理论作为上述两种思想的具体实现平台和安全科学领域的切入点。分析三者融合的可行性及其意义。

3)在空间故障树框架内重新诠释了信息转换定律，即故障信息转化定律。给出了相关定义及其解释，并给出了本体论故障信息−认识论故障信息−故障知识−智能安全策略−智能安全行为的故障信息转化定律。

 [1] 董金金. 智能变电站故障数据自同步方法研究[D]. 济南: 山东大学, 2018. DONG Jinjin. Study on self-synchronization method of fault data in smart substation[D]. Jinan: Shandong University, 2018. (0) [2] 刘琨, 黄明辉, 李一泉, 等. 智能变电站故障信息模型与继电保护在线监测方法[J]. 电力自动化设备, 2018, 38(2): 210-216. LIU Kun, HUANG Minghui, LI Yiquan, et al. Fault information model and online monitoring method for relay protection system in smart substation[J]. Electric power automation equipment, 2018, 38(2): 210-216. (0) [3] 李闻涛, 罗敏, 黄江山. 基于NLP的转向架故障信息处理系统[J]. 机电一体化, 2017, 23(4): 53-59. LI Wentao, LUO Min, HUANG Jiangshan. Bogie fault information processing system based on NLP[J]. Mechatronics, 2017, 23(4): 53-59. (0) [4] 张祎, 南东亮, 常喜强, 等. 适应智能调度的继电保护故障信息系统高级应用研发[J]. 电气技术, 2016(5): 91-95. ZHANG Yi, NAN Dongliang, CHANG Xiqiang, et al. Development of realization of advanced application function for protective relaying fault information system adaptable to smart dispatch[J]. Electrical engineering, 2016(5): 91-95. DOI:10.3969/j.issn.1673-3800.2016.05.020 (0) [5] CUI Tiejun, LI Shasha. Deep learning of system reliability under multi-factor influence based on space fault tree[J]. Neural computing and applications, 2019, 31(9): 4761-4776. DOI:10.1007/s00521-018-3416-2 (0) [6] 崔铁军, 马云东. 多维空间故障树构建及应用研究[J]. 中国安全科学学报, 2013, 23(4): 32-37. CUI Tiejun, MA Yundong. Research on multi-dimensional space fault tree construction and application[J]. China safety science journal, 2013, 23(4): 32-37. (0) [7] 崔铁军, 马云东. DSFT的建立及故障概率空间分布的确定[J]. 系统工程理论与实践, 2016, 36(4): 1081-1088. CUI Tiejun, MA Yundong. Discrete space fault tree construction and failure probability space distribution determination[J]. Systems engineering-theory & practice, 2016, 36(4): 1081-1088. DOI:10.12011/1000-6788(2016)04-1081-08 (0) [8] CUI Tiejun, LI Shasha. Study on the construction and application of discrete space fault tree modified by fuzzy structured element[J]. Cluster computing, 2019, 22(S3): 6563-6577. DOI:10.1007/s10586-018-2342-5 (0) [9] 崔铁军, 汪培庄, 马云东. 01SFT中的系统因素结构反分析方法研究[J]. 系统工程理论与实践, 2016, 36(8): 2152-2160. CUI Tiejun, WANG Peizhuang, MA Yundong. Inward analysis of system factor structure in 01 space fault tree[J]. Systems engineering-theory & practice, 2016, 36(8): 2152-2160. DOI:10.12011/1000-6788(2016)08-2152-09 (0) [10] 崔铁军, 马云东. 系统可靠性决策规则发掘方法研究[J]. 系统工程理论与实践, 2015, 35(12): 3210-3216. CUI Tiejun, MA Yundong. The method research on decision criterion discovery of system reliability[J]. Systems engineering-theory & practice, 2015, 35(12): 3210-3216. DOI:10.12011/1000-6788(2015)12-3210 (0) [11] CUI Tiejun, WANG Peizhuang, LI Shasha. The function structure analysis theory based on the factor space and space fault tree[J]. Cluster computing, 2017, 20(2): 1387-1398. DOI:10.1007/s10586-017-0835-2 (0) [12] LI Shasha, CUI Tiejun, LI Xingsen, et al. Construction of cloud space fault tree and its application of fault data uncertainty analysis[C]//Proceedings of the 2017 International Conference on Machine Learning and Cybernetics. Ningbo, China, 2017: 195–201. (0) [13] LI Shasha, CUI Tiejun, LIU Jian. Study on the construction and application of cloudization space fault tree[J]. Cluster computing, 2019, 22(S3): 5613-5633. DOI:10.1007/s10586-017-1398-y (0) [14] 崔铁军, 马云东. 因素空间的属性圆定义及其在对象分类中的应用[J]. 计算机工程与科学, 2015, 37(11): 2169-2174. CUI Tiejun, MA Yundong. Definition of attribute circle in factor space and its application in object classification[J]. Computer engineering & science, 2015, 37(11): 2169-2174. DOI:10.3969/j.issn.1007-130X.2015.11.026 (0) [15] 崔铁军, 马云东. 基于因素空间的煤矿安全情况区分方法的研究[J]. 系统工程理论与实践, 2015, 35(11): 2891-2897. CUI Tiejun, MA Yundong. Research on the classification method about coal mine safety situation based on the factor space[J]. Systems engineering-theory & practice, 2015, 35(11): 2891-2897. DOI:10.12011/1000-6788(2015)11-2891 (0) [16] CUI Tiejun, LI Shasha. Study on the relationship between system reliability and influencing factors under big data and multi-factors[J]. Cluster computing, 2019, 22(S4): 10275-10297. DOI:10.1007/s10586-017-1278-5 (0) [17] 崔铁军, 李莎莎, 朱宝艳. 空间故障网络及其与空间故障树的转换[J]. 计算机应用研究, 2019, 36(8): 2400–2403. CUI Tiejun, LI Shasha, ZHU Baoyan. Construction space fault network and recognition network structure characteristic[J]. Application research of computers, 2019, 36(8): 2400–2403. (0) [18] 崔铁军, 汪培庄. 空间故障树与因素空间融合的智能可靠性分析方法[J]. 智能系统学报, 2019, 14(5): 853-864. CUI Tiejun, WANG Peizhuang. Intelligent reliability analysis method based on space fault tree and factor space[J]. CAAI transactions on intelligent systems, 2019, 14(5): 853-864. (0) [19] 汪培庄. 因素空间与因素库[J]. 辽宁工程技术大学学报(自然科学版), 2013, 32(10): 1297-1304. WANG Peizhuang. Factor spaces and factor data-bases[J]. Journal of liaoning technical university (natural science edition), 2013, 32(10): 1297-1304. DOI:10.3969/j.issn.1008-0562.2013.10.001 (0) [20] WANG Peizhuang, LIU Zengliang, SHI Yong, et al. Factor space, the theoretical base of data science[J]. Annals of data science, 2014, 1(2): 233-251. DOI:10.1007/s40745-014-0017-5 (0) [21] 汪培庄, 郭嗣琮, 包研科, 等. 因素空间中的因素分析法[J]. 辽宁工程技术大学学报(自然科学版), 2014, 33(7): 865-870. WANG Peizhuang, GUO Sicong, BAO Yanke, et al. Causality analysis in factor spaces[J]. Journal of liaoning technical university (natural science edition), 2014, 33(7): 865-870. (0) [22] 汪培庄. 因素空间与数据科学[J]. 辽宁工程技术大学学报(自然科学版), 2015, 34(2): 273-280. WANG Peizhuang. Factor spaces and data science[J]. Journal of liaoning technical university (natural science edition), 2015, 34(2): 273-280. DOI:10.11956/j.issn.1008-0562.2015.02.026 (0) [23] 钟义信, 张瑞. 信息生态学与语义信息论[J]. 图书情报知识, 2017(6): 4-11. ZHONG Yixin, ZHANG Rui. Information ecology and semantic information theory[J]. Document, informaiton & knowledge, 2017(6): 4-11. (0) [24] 钟义信. 从“机械还原方法论”到“信息生态方法论”——人工智能理论源头创新的成功路[J]. 哲学分析, 2017, 8(5): 133-144. ZHONG Yixin. From Mechanical reductionism to methodology of information ecology: successful approach to innovation for AI theory[J]. Philosophical analysis, 2017, 8(5): 133-144. DOI:10.3969/j.issn.2095-0047.2017.05.011 (0) [25] 钟义信. 从信息科学视角看《信息哲学》[J]. 哲学分析, 2015, 6(1): 17-31. ZHONG Yixin. Information science and its view on information philosophy[J]. Philosophical analysis, 2015, 6(1): 17-31. (0) [26] 钟义信. 高等智能•机制主义•信息转换[J]. 北京邮电大学学报, 2010, 33(1): 1-6. ZHONG Yixin. Advanced intelligence-mechanism approach-information conversion[J]. Journal of beijing university of posts and telecommunications, 2010, 33(1): 1-6. DOI:10.3969/j.issn.1007-5321.2010.01.001 (0)