|本期目录/Table of Contents|

[1]朱珂,周科平.基于解释图的概率多规划识别事故分析方法研究[J].中国安全生产科学技术,2016,12(10):136-141.[doi:10.11731/j.issn.1673-193x.2016.10.023]
　ZHU Ke,ZHOU Keping.Study on accident analysis method with probabilistic multiple plan recognition based on interpretation map[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(10):136-141.[doi:10.11731/j.issn.1673-193x.2016.10.023]
点击复制

基于解释图的概率多规划识别事故分析方法研究
分享到：

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
12
期数:
2016年10期
页码:
136-141
栏目:
现代职业安全卫生管理与技术
出版日期:
2016-10-30

文章信息/Info

Title:
Study on accident analysis method with probabilistic multiple plan recognition based on interpretation map
作者:
朱珂; 周科平
（中南大学 资源与安全工程学院，湖南 长沙 410083）
Author(s):
ZHU Ke;  ZHOU Keping
School of Resources and Safety Engineering, Central South University, Changsha Hunan 410083, China
关键词:
事故分析; 多规划识别; 解释图; 解释集合重要度
Keywords:
accident analysis;  multiple plan recognition;  interpretation map;  importance of interpretation set
分类号:
X913.3
DOI:
10.11731/j.issn.1673-193x.2016.10.023
文献标志码:
A
摘要:
基于多规划识别在行为分析的多目标性、过程性与结果解释性方面的优势，提出了一种改进的概率多规划识别事故分析法，并将其应用于井下电机车撞、压人事故行为分析。通过构建事故规划库和基本事件解释图，找出顶层事故致因的所有解释集合，并定义解释集合重要度对解释集合路径进行重要程度排序，从而找到导致顶层事件发生的最佳解释集合；通过临界重要度系数验算，对解释集合重要度的排序结果进行论证，两者计算结果基本一致且后者优势明显，说明了基于解释图的多规划识别算法应用于事故分析的可行性和优越性；最后指出了此算法对处理逻辑结构复杂的大样本事故分析存在的不足及拟解决办法。
Abstract:
Based on the advantages in the aspects of multi objectives, procedure and results explanatory of multiple plan recognition in behavior analysis, an improved accident analysis method with probabilistic multiple plan recognition was proposed and applied in the behavior analysis of human knock and pinning accidents caused by underground electric locomotive. All the interpretation sets of top accident cause were found out through establishing the accident plan library and the interpretation map of basic events, and the importance of interpretation set was defined to carry out the important degree sorting on the interpretation set path, so as to find out the best interpretation set causing the occurrence of top event. The sorting results about the importance of interpretation set were demonstrated through the checking on critical importance coefficient. It showed that the calculation results of them were basically consistent, and the latter had the more obvious advantage, which illustrates the feasibility and superiority of applying multiple plan recognition algorithm based on interpretation map in accident analysis. Finally, the shortcomings of this algorithm when processing large sample accident analysis with complex logical structure and the proposed solutions were pointed out.

参考文献/References:

［1］魏静，王菊韵，于华. 基于多模块贝叶斯网络的恐怖袭击威胁评估［J］. 中国科学院大学学报，2015，32(2)：264-272. WEI Jing，WANG Juyun，YU Hua. Terrorism threat assessment with multi-module Bayesian network［J］. Journal of University of Chinese Academy of Sciences，2015，32(2)：264-272.
［2］徐磊，李向阳，于明璐. 基于案例推理的应急决策贝叶斯网建模方法［J］. 上海师范大学学报(自然科学版)，2013，42(3)：237-243. XU Lei，LI Xiangyang，YU Minglu. Bayesian network modeling method based on case reasoning for emergency decision-making［J］. Journal of Shanghai Normal University (Natural Sciences)，2013，42(3)：237-243.
［3］Marcio das chagasmoura，Rafael ValenaAzevedo，Enrique Lopez Droguett, et al. Estimation of expected number of accidents and workforce unavailability through Bayesian population variability analysis and Markov-based model［J］. Reliability Engineering and System Safety，2016（150）：136-146.
［4］Luca Bortolussi. Hybrid behavior of Markov population models ［J］. Information and Computation，2015（247）：37-86.
［5］Bhanupongjitwasinkul，Bonaventura-H.W.-Hadikusumo，Abdul Qayoom Memon. A Bayesian Belief Network model of organizational factors for improving safe work behaviors in Thai construction industry ［J］. Safety Science，2016（82）：264-273.
［6］Abhisek Mudgala，Shauna Hallmark，Alicia Carriquiryc, ea al. Driving behavior at a roundabout Ahierarchical Bayesian ［J］. Transportation Research，2014（26）：20-26.
［7］Mashrura Musharraf，Jennifer Smitha，Faisal Khana, et al. Assessing off shore emergency evacuation behavior inavirtual environment using a Bayesian Network approach［J］. Reliability Engineering and System Safety，2016（152）：28-37.
［8］Eugene Charniak，Robert P. Goldman. A Bayesian model of plan recognition ［J］. Artificial Intelligence，1993，1（64）：53-79.
［9］刘莹. 智能规划与规划识别中若干重要问题的研究［D］. 长春：东北师范大学，2013.
［10］王兵，杨小莹，赵春兰，等. 基于贝叶斯网络的钻井作业现场风险评估［J］. 西南石油大学学报(自然科学版)，2015，37(2)：131-137. WANG Bing，YANG Xiaoying，ZHAO Chunlan, et al. Drilling site risk assessment based on bayesian Network［J］. Journal of Southwest Petroleum University（Science &Technology Edition），2015，37(2)：131-137.
［11］汪涛，廖彬超，马昕，等. 基于贝叶斯网络的施工安全风险概率评估方法［J］. 土木工程学报，2010，42(S2)：384-391. WANG Tao，LIAO Bingchao，MA xin, et al. Using Bayesian Network to develop a probability assessment approach for construction safety risk［J］. China Civil Engineering Journal，2010，42(S2)：384-391.）
［12］Jyoti Bhandari，Rouzbeh Abbassi，Vikram Garaniya, et al. Risk analysis of deepwater drilling operations using Bayesian network ［J］. Journal of Loss Prevention in the Process Industries，2015，38：11-23.
［13］Xiao chen LI，Wen ji MAO. Forecasting complex group behavior via multiple plan recognition ［J］. Frontiers of Computer Science，2012，6（1）：102-110.
［14］王思鹏. 事故树分析法在分析井下运输事故中的应用［J］. 煤炭科学技术，2003，32（5）：36-38. WANG Sipeng. FTA applied to analyze transportation accident in underground mine［J］. Coal Science and Technology，2003，32（5）：36-38.
［15］柴建设等. 安全评价技术·方法·实例［M］. 北京：化学工业出版社，2008：159-163
［16］王飞跃等. 社会计算的基本方法与应用［M］. 杭州：浙江大学出版社，2013：167-175.

相似文献/References:

[1]冀成楼,张宏.工业事故调查和分析的发展历程及趋势[J].中国安全生产科学技术,2011,7(6):151.
　JI Cheng-lou,ZHANG Hong.The track of industrial incident investigation and analysis and developing trends[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2011,7(10):151.
[2]张启波,袁凤丽,王清.硫酸储罐爆炸事故分析及预防[J].中国安全生产科学技术,2012,8(2):185.
　ZHANG Qi bo,YUAN Feng li,WANG Qing.Analysis and prevention on explosion accident of sulfuric acid tanks[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2012,8(10):185.
[3]刘〓盼,何启林,彭〓伟.EOC方法在煤矿安全生产事故中的应用研究[J].中国安全生产科学技术,2012,8(10):135.
　LIU Pan,HE Qi lin,PENG Wei.Application research of EOC method in safety production accidents of coal mine[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2012,8(10):135.
[4]王振中,张卫华,吴锋棒.自助加油站典型静电事故案例分析及防范措施[J].中国安全生产科学技术,2013,9(7):169.[doi:10.11731/j.issn.1673-193x.2013.07.031]
　WANG Zhen zhong,ZHANG Wei hua,WU Feng bang.Analysis and preventive measures on typical electrostatic accidents cases of selfservice refueling stations[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2013,9(10):169.[doi:10.11731/j.issn.1673-193x.2013.07.031]
[5]佟淑娇,吴宗之,王如君,等.2001～2013年危险化学品企业较大以上事故统计分析及对策建议[J].中国安全生产科学技术,2015,11(3):129.[doi:10.11731/j.issn.1673-193x.2015.03.021]
　TONG Shu-jiao,WU Zong-zhi,WANG Ru-jun,et al.Statistical analysis and countermeasures on larger and above grades accidents of dangerous chemical enterprises from 2001 to 2013[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2015,11(10):129.[doi:10.11731/j.issn.1673-193x.2015.03.021]
[6]刘清友,唐洋,秦世宽,等.防提安全装置现场应用事故分析与规避措施[J].中国安全生产科学技术,2015,11(5):117.[doi:10.11731/j.issn.1673-193x.2015.05.018]
　LIU Qing-you,TANG Yang,QIN Shi-kuan,et al.Accident cause analysis and avoidance measures for field application of anti-lifting safety device[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2015,11(10):117.[doi:10.11731/j.issn.1673-193x.2015.05.018]
[7]周琳,薛宇敬阳,刘希扬.事故的组织管理原因文献综述[J].中国安全生产科学技术,2016,12(10):185.[doi:10.11731/j.issn.1673-193x.2016.10.031]
　ZHOU Lin,XUE Yujingyang,LIU Xiyang.Literature review on organization and management causes of accidents[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(10):185.[doi:10.11731/j.issn.1673-193x.2016.10.031]
[8]傅贵,索晓,贾清淞,等.10种事故致因模型的对比研究[J].中国安全生产科学技术,2018,14(2):58.[doi:10.11731/j.issn.1673-193x.2018.02.009]
　FU Gui,SUO Xiao,JIA Qingsong,et al.Comparative study on ten accident causation models[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2018,14(10):58.[doi:10.11731/j.issn.1673-193x.2018.02.009]
[9]左博睿,帅斌,黄文成.基于模糊推理的FRAM事故定量分析方法研究[J].中国安全生产科学技术,2020,16(7):11.[doi:10.11731/j.issn.1673-193x.2020.07.002]
　ZUO Borui,SHUAI Bin,HUANG Wencheng.Research on FRAM accident quantitative analysis method based on fuzzy reasoning[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2020,16(10):11.[doi:10.11731/j.issn.1673-193x.2020.07.002]
[10]郑霞忠,柯善钢,陈星,等.基于复杂网络的内河船舶碰撞事故致因分析*[J].中国安全生产科学技术,2023,19(2):211.[doi:10.11731/j.issn.1673-193x.2023.02.029]
　ZHENG Xiazhong,KE Shangang,CHEN Xing,et al.Cause analysis of inland river ship collision accident based on complex network[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2023,19(10):211.[doi:10.11731/j.issn.1673-193x.2023.02.029]

备注/Memo

备注/Memo:
国家自然科学基金项目(51474252)
更新日期/Last Update: 2016-11-30