Article(id=1149739131527410067, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149739129056969102, articleNumber=1003-3033(2024)03-0029-10, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2024.03.0368, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1694707200000, receivedDateStr=2023-09-15, revisedDate=1702915200000, revisedDateStr=2023-12-19, acceptedDate=null, acceptedDateStr=null, onlineDate=1752048770076, onlineDateStr=2025-07-09, pubDate=1711555200000, pubDateStr=2024-03-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752048770076, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752048770076, creator=13701087609, updateTime=1752048770076, updator=13701087609, issue=Issue{id=1149739129056969102, tenantId=1146029695717560320, journalId=1146031787341344770, year='2024', volume='34', issue='3', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752048769486, creator=13701087609, updateTime=1756468931593, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1168278632783950282, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149739129056969102, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1168278632783950283, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149739129056969102, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=29, endPage=38, ext={EN=ArticleExt(id=1149739132307550614, articleId=1149739131527410067, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Feature mining and causative analysis of fire accidents in ship repair and building enterprises, columnId=1149733271128420907, journalTitle=China Safety Science Journal, columnName=Safety social science and safety management, runingTitle=null, highlight=null, articleAbstract=

To investigate the features and causation factors of fire accidents in SRBE,118 fire accidents were studied using method of mathematical statistics. Firstly,accident features were mined in terms of the temporal and spatial attributes of accidents,the three elements of fire and the severity of injuries. Then,based on the improved HFACS-SRBE accident causation model,methods such as Chi-square test,OR and Cramer's V were used to analyze the correlations and their strength between the causal factors. The results show that 14:00-16:00 is the most prone to fire accidents and casualties. The main location of fire accidents is in the ship area,accounting for 33.90%. 59.19% of the ignition source comes from the ignition operation. Ratio of no injuries,slight and minor injuries,serious injuries and deaths is 61:54:3. Through the test of correlations and their strength,it is determined that 15 groups of adjacent level causal factors are correlated,and 26 complete accident causation chains are obtained. Covers communication and coordination→inappropriate operation plans→bad psychological state→decision-making errors is the accident causation chain with the greatest strength of correlation leading to the occurrence of fire accidents in ship repair and building enterprises.

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为探究船舶修造企业(SRBE)火灾事故的特征和致因,运用数理统计方法研究118起火灾事故,从事故的时空属性、火灾三要素和伤害严重程度进行事故特征挖掘;并基于改进的人因分析与分类系统(HFACS-SRBE)事故致因模型,采用卡方检验、让步比(OR)、克莱姆V系数(Cramer' s V)方法,分析致因因素之间的相关性及其强弱。结果表明:14:00—16:00最易发生火灾事故和人员伤亡;火灾事故主要发生地点在船舶区域,占比为33.90%;59.19%的点火源是动火作业;无人员伤害、轻伤和轻微伤、重伤和死亡数量比值为61:54:3。通过相关性及其强弱检验后确定15组相邻层级致因因素存在相关性,并得到26条完整事故致因链。其中,沟通与协调→运行计划不适当→不良心理状态→决策差错是导致船舶修造火灾事故发生关联性强度最大的事故致因链。

, correspAuthors=焦宇, authorNote=null, correspAuthorsNote=
** 焦宇(1981—),男,河南汝州人,博士,副教授,主要从事船舶与海工安全与应急研究。E-mail:
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李显 (1995—),男,河南信阳人,博士研究生,主要研究方向为船舶修造事故数据挖掘,作业过程风险评估。E-mail:

陈文涛,副研究员。

史旦达,教授。

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李显 (1995—),男,河南信阳人,博士研究生,主要研究方向为船舶修造事故数据挖掘,作业过程风险评估。E-mail:

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李显 (1995—),男,河南信阳人,博士研究生,主要研究方向为船舶修造事故数据挖掘,作业过程风险评估。E-mail:

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陈文涛,副研究员。

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史旦达,教授。

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Frontiers in Public Health, 2022, 10: 1-15., articleTitle=Risk factors identification of unsafe acts in deep coal mine workers based on grounded theory and HFACS, refAbstract=null)], funds=[Fund(id=1168130292565946885, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, awardId=51109127, language=CN, fundingSource=国家自然科学基金资助(51109127), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1168130287792828867, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, xref=1, ext=[AuthorCompanyExt(id=1168130287801217476, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, companyId=1168130287792828867, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 College of Ocean Science and Engineering,Shanghai Maritime University,Shanghai 201306,China), AuthorCompanyExt(id=1168130287805411781, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, companyId=1168130287792828867, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 上海海事大学 海洋科学与工程学院,上海 201306)]), AuthorCompany(id=1168130287876714950, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, xref=2, ext=[AuthorCompanyExt(id=1168130287910269383, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, companyId=1168130287876714950, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 Safety Development Research Center,Information Research Institute of Ministry of Emergency Management,Shanghai 201401,China), AuthorCompanyExt(id=1168130287927046600, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, companyId=1168130287876714950, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 应急管理部信息研究院 安全发展研究中心,上海 201401)])], figs=[ArticleFig(id=1168130290418463217, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Fig.1, caption=HFACS-SRBE model, figureFileSmall=nuO4a7SQ5Ak47tw1zCTdgw==, figureFileBig=R80RbT77im89i/jy17jrBw==, tableContent=null), ArticleFig(id=1168130290481377778, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=图1, caption=HFACS-SRBE模型

个人防护装备(Personal Protective Equipment,PPE)。

, figureFileSmall=nuO4a7SQ5Ak47tw1zCTdgw==, figureFileBig=R80RbT77im89i/jy17jrBw==, tableContent=null), ArticleFig(id=1168130290569458163, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Fig.2, caption=Time characteristics of fire accidents in SRBE, figureFileSmall=3lBILYMf8PB1UBjNH3Jb6A==, figureFileBig=e3eXb9E3W7Fiz3aKAi5E3A==, tableContent=null), ArticleFig(id=1168130290628178420, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=图2, caption=SRBE火灾事故时间特征, figureFileSmall=3lBILYMf8PB1UBjNH3Jb6A==, figureFileBig=e3eXb9E3W7Fiz3aKAi5E3A==, tableContent=null), ArticleFig(id=1168130290695287285, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Fig.3, caption=Heinrich accident triangle vs. SRBE building fire accident triangle, figureFileSmall=cS9I3fqLerHfGvw4rpr0pw==, figureFileBig=ACzWX26RyJxTkMyEQE6WHQ==, tableContent=null), ArticleFig(id=1168130290779173366, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=图3, caption=海因里希事故三角形与SRBE火灾事故三角形, figureFileSmall=cS9I3fqLerHfGvw4rpr0pw==, figureFileBig=ACzWX26RyJxTkMyEQE6WHQ==, tableContent=null), ArticleFig(id=1168130290871448055, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Fig.4, caption=Correlations between causation factors at adjacent levels, figureFileSmall=X69OKErl8mozbhmgSQlonQ==, figureFileBig=N3QkQnN/YgpHS664uLMqfA==, tableContent=null), ArticleFig(id=1168130290967917048, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=图4, caption=相邻层级致因因素间的关联关系, figureFileSmall=X69OKErl8mozbhmgSQlonQ==, figureFileBig=N3QkQnN/YgpHS664uLMqfA==, tableContent=null), ArticleFig(id=1168130291127300601, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Tab.1, caption=

Spatial characteristics of fire accidents in SRBE

, figureFileSmall=null, figureFileBig=null, tableContent=
空间特征 内场 厂区外 码头
或坞
船舶 车间 总计
船体车间 12(9) 0(0) 15(4) 20(14) 0(0) 47(27)
机电车间 6(2) 0(0) 10(4) 7(4) 0(0) 23(10)
涂装车间 2(1) 0(0) 3(3) 2(1) 3(2) 10(7)
搭载车间 2(2) 0(0) 1(1) 2(2) 0(0) 5(5)
船台车间 1(0) 0(0) 1(1) 3(1) 0(0) 5(2)
建造部 4(4) 0(0) 0(0) 0(0) 0(0) 4(4)
分段车间 3(3) 0(0) 0(0) 1(0) 0(0) 4(3)
内业车间 1(1) 0(0) 2(0) 0(0) 1(1) 4(2)
舾装车间 0(0) 0(0) 2(2) 2(1) 0(0) 4(3)
机修车间 1(1) 0(0) 0(0) 1(2) 0(0) 2(3)
行政部 1(0) 1(0) 0(0) 0(0) 0(0) 2(0)
资产部 2(1) 0(0) 0(0) 0(0) 0(0) 2(1)
总务部 1(1) 0(0) 0(0) 0(0) 0(0) 1(1)
事业部 0(0) 0(0) 1(0) 0(0) 0(0) 1(0)
物资部 1(0) 0(0) 0(0) 0(0) 0(0) 1(0)
质量部 0(0) 0(0) 0(0) 0(0) 1(1) 1(1)
轮机车间 0(0) 0(0) 0(0) 1(1) 0(0) 1(1)
上建车间 0(0) 0(0) 0(0) 1(0) 0(0) 1(0)
总计 37(25) 1(0) 35(15) 40(27) 5(4) 118(71)
), ArticleFig(id=1168130291282489850, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=表1, caption=

SRBE火灾事故空间特征

, figureFileSmall=null, figureFileBig=null, tableContent=
空间特征 内场 厂区外 码头
或坞
船舶 车间 总计
船体车间 12(9) 0(0) 15(4) 20(14) 0(0) 47(27)
机电车间 6(2) 0(0) 10(4) 7(4) 0(0) 23(10)
涂装车间 2(1) 0(0) 3(3) 2(1) 3(2) 10(7)
搭载车间 2(2) 0(0) 1(1) 2(2) 0(0) 5(5)
船台车间 1(0) 0(0) 1(1) 3(1) 0(0) 5(2)
建造部 4(4) 0(0) 0(0) 0(0) 0(0) 4(4)
分段车间 3(3) 0(0) 0(0) 1(0) 0(0) 4(3)
内业车间 1(1) 0(0) 2(0) 0(0) 1(1) 4(2)
舾装车间 0(0) 0(0) 2(2) 2(1) 0(0) 4(3)
机修车间 1(1) 0(0) 0(0) 1(2) 0(0) 2(3)
行政部 1(0) 1(0) 0(0) 0(0) 0(0) 2(0)
资产部 2(1) 0(0) 0(0) 0(0) 0(0) 2(1)
总务部 1(1) 0(0) 0(0) 0(0) 0(0) 1(1)
事业部 0(0) 0(0) 1(0) 0(0) 0(0) 1(0)
物资部 1(0) 0(0) 0(0) 0(0) 0(0) 1(0)
质量部 0(0) 0(0) 0(0) 0(0) 1(1) 1(1)
轮机车间 0(0) 0(0) 0(0) 1(1) 0(0) 1(1)
上建车间 0(0) 0(0) 0(0) 1(0) 0(0) 1(0)
总计 37(25) 1(0) 35(15) 40(27) 5(4) 118(71)
), ArticleFig(id=1168130291357987323, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Tab.2, caption=

Distribution of ignition sources of fire accidents in SRBE

, figureFileSmall=null, figureFileBig=null, tableContent=
点火源
分类
分类说明 事故
起数
事故数
量子分
类占
比/%
事故数
量整体
占比/
%
直接
火源
明火 电焊火星 22 25.88 18.64
气/切割火星 27 31.76 22.88
高温铁屑/水/块 10 11.76 8.47
割炬/烘枪/
烤把火焰
23 27.06 19.49
未熄灭的烟头 3 3.53 2.54
电火花 电气设备产生的
电弧和静电火花
8 100 6.78
雷击 瞬间的高压放电 0 100 0
间接
火源
加热自
燃起火
热表面 3 13.64 2.54
热辐射 7 31.82 5.93
线路发热起火 10 45.45 8.47
摩擦撞击压
缩起火
2 9.09 1.69
聚焦起火 0 0 0
本身自
燃起火
(无明火
和外来
热源)
物质本身自燃
起火
0 0 0
化学反应热腐蚀/
自燃起火
3 100 2.54
), ArticleFig(id=1168130291437679100, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=表2, caption=

SRBE火灾事故中点火源特征分布

, figureFileSmall=null, figureFileBig=null, tableContent=
点火源
分类
分类说明 事故
起数
事故数
量子分
类占
比/%
事故数
量整体
占比/
%
直接
火源
明火 电焊火星 22 25.88 18.64
气/切割火星 27 31.76 22.88
高温铁屑/水/块 10 11.76 8.47
割炬/烘枪/
烤把火焰
23 27.06 19.49
未熄灭的烟头 3 3.53 2.54
电火花 电气设备产生的
电弧和静电火花
8 100 6.78
雷击 瞬间的高压放电 0 100 0
间接
火源
加热自
燃起火
热表面 3 13.64 2.54
热辐射 7 31.82 5.93
线路发热起火 10 45.45 8.47
摩擦撞击压
缩起火
2 9.09 1.69
聚焦起火 0 0 0
本身自
燃起火
(无明火
和外来
热源)
物质本身自燃
起火
0 0 0
化学反应热腐蚀/
自燃起火
3 100 2.54
), ArticleFig(id=1168130291529953789, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Tab.3, caption=

Distribution of combustibles of fire accidents in SRBE

, figureFileSmall=null, figureFileBig=null, tableContent=
可燃物
分类
分类说明 事故
起数
事故起数
子分类占
比/%
事故起数
整体占
比/%
设备
财产
电器设备 14 16.67 11.86
油布/三防布/回
丝布等布料
14 5.95 11.86
油箱/塑料桶/
管线/管带
25 3.57 21.19
化学品 14 8.33 11.86
麻绳/安全网 5 2.38 4.24
手套/防护服/劳
保鞋等防护品
3 10.71 2.54
木质/纸类材料 7 1.19 5.93
生活/作业废弃物 2 3.57 1.69
人体
组织
面颌部 9 32.14 7.63
1 3.57 0.85
眼睛 3 10.71 2.54
耳朵 2 7.14 1.69
腕及手 13 46.43 11.02
设备财产+
人体组织
衣物+上体 21 52.5 17.8
衣物+下体 19 47.5 16.1
), ArticleFig(id=1168130291685143038, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=表3, caption=

SRBE火灾事故中可燃物特征分布

, figureFileSmall=null, figureFileBig=null, tableContent=
可燃物
分类
分类说明 事故
起数
事故起数
子分类占
比/%
事故起数
整体占
比/%
设备
财产
电器设备 14 16.67 11.86
油布/三防布/回
丝布等布料
14 5.95 11.86
油箱/塑料桶/
管线/管带
25 3.57 21.19
化学品 14 8.33 11.86
麻绳/安全网 5 2.38 4.24
手套/防护服/劳
保鞋等防护品
3 10.71 2.54
木质/纸类材料 7 1.19 5.93
生活/作业废弃物 2 3.57 1.69
人体
组织
面颌部 9 32.14 7.63
1 3.57 0.85
眼睛 3 10.71 2.54
耳朵 2 7.14 1.69
腕及手 13 46.43 11.02
设备财产+
人体组织
衣物+上体 21 52.5 17.8
衣物+下体 19 47.5 16.1
), ArticleFig(id=1168130291769029119, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Tab.4, caption=

Severity of fire accidents under different businesses in SRBE

, figureFileSmall=null, figureFileBig=null, tableContent=
标准分类 修理改装 其他 船舶与海工建造 总计
无伤害事故 19 12 30 61
微伤事故 14 9 20 43
轻伤事故 6 2 3 11
重伤事故 0 0 1 1
死亡事故 1 0 1 2
总计 40 23 55 118
), ArticleFig(id=1168130291823555072, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=表4, caption=

SRBE不同业务下的火灾事故严重程度

, figureFileSmall=null, figureFileBig=null, tableContent=
标准分类 修理改装 其他 船舶与海工建造 总计
无伤害事故 19 12 30 61
微伤事故 14 9 20 43
轻伤事故 6 2 3 11
重伤事故 0 0 1 1
死亡事故 1 0 1 2
总计 40 23 55 118
), ArticleFig(id=1168130291899052545, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Tab.5, caption=

Frequency and percentage of causation factors

, figureFileSmall=null, figureFileBig=null, tableContent=
), ArticleFig(id=1168130292037464578, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=表5, caption=

致因因素频数与占比

, figureFileSmall=null, figureFileBig=null, tableContent=
), ArticleFig(id=1168130292222013955, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=EN, label=Tab.6, caption=

Results of correlation analysis between upper and lower causation factors

, figureFileSmall=null, figureFileBig=null, tableContent=
致因因素 卡方检验 Cramer's
V
OR 95%置信区间
χ2 p 下限 上限
组织影响层级和不安全监督层级
L4-1L3-2 23.178 0.000 0.443 8.9 3.4 23.7
L4-2L3-2 23.356 0.000 0.445 10.3 3.6 29.4
L4-3L3-2 12.454 0.000 0.325 5.3 2.0 14.2
L4-3L3-3 6.320 0.012 0.231 2.7 1.2 5.8
L4-4L3-2 5.672 0.017 0.219 1.5 1.3 1.7
不安全监督层级和不安全行为的前提条件层级
L3-2L21-2 10.551 0.001 0.299 6.7 1.9 23.6
L3-2L22-2 9.042 0.003 0.277 4.0 1.6 10.2
L3-2L21-4 10.582 0.001 0.299 4.1 1.7 9.7
L3-3L21-4 5.434 0.020 0.215 3.1 1.2 8.4
不安全行为的前提条件层级与不安全行为层级
L21-2
L11-1
8.016 0.005 0.261 3.4 1.4 7.9
L21-2
L11-2
12.092 0.001 0.320 4.1 1.8 9.4
L21-2
L11-3
6.152 0.013 0.228 3.6 1.3 10.2
L21-2
L12-1
10.012 0.002 0.291 3.7 1.6 8.5
L21-4
L11-2
6.982 0.008 0.243 3.4 1.3 8.7
L23-3
L11-1
5.220 0.022 0.210 3.0 1.1 7.5
), ArticleFig(id=1168130292423340548, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149739131527410067, language=CN, label=表6, caption=

相邻层级致因因素的相关性分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
致因因素 卡方检验 Cramer's
V
OR 95%置信区间
χ2 p 下限 上限
组织影响层级和不安全监督层级
L4-1L3-2 23.178 0.000 0.443 8.9 3.4 23.7
L4-2L3-2 23.356 0.000 0.445 10.3 3.6 29.4
L4-3L3-2 12.454 0.000 0.325 5.3 2.0 14.2
L4-3L3-3 6.320 0.012 0.231 2.7 1.2 5.8
L4-4L3-2 5.672 0.017 0.219 1.5 1.3 1.7
不安全监督层级和不安全行为的前提条件层级
L3-2L21-2 10.551 0.001 0.299 6.7 1.9 23.6
L3-2L22-2 9.042 0.003 0.277 4.0 1.6 10.2
L3-2L21-4 10.582 0.001 0.299 4.1 1.7 9.7
L3-3L21-4 5.434 0.020 0.215 3.1 1.2 8.4
不安全行为的前提条件层级与不安全行为层级
L21-2
L11-1
8.016 0.005 0.261 3.4 1.4 7.9
L21-2
L11-2
12.092 0.001 0.320 4.1 1.8 9.4
L21-2
L11-3
6.152 0.013 0.228 3.6 1.3 10.2
L21-2
L12-1
10.012 0.002 0.291 3.7 1.6 8.5
L21-4
L11-2
6.982 0.008 0.243 3.4 1.3 8.7
L23-3
L11-1
5.220 0.022 0.210 3.0 1.1 7.5
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船舶修造企业火灾事故特征挖掘与致因分析
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李显 1 , 焦宇 1, ** , 陈文涛 2 , 史旦达 1 , 康与涛 1
中国安全科学学报 | 安全社会科学与安全管理 2024,34(3): 29-38
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中国安全科学学报 | 安全社会科学与安全管理 2024, 34(3): 29-38
船舶修造企业火灾事故特征挖掘与致因分析
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李显1 , 焦宇1, ** , 陈文涛2, 史旦达1, 康与涛1
作者信息
  • 1 上海海事大学 海洋科学与工程学院,上海 201306
  • 2 应急管理部信息研究院 安全发展研究中心,上海 201401
  • 李显 (1995—),男,河南信阳人,博士研究生,主要研究方向为船舶修造事故数据挖掘,作业过程风险评估。E-mail:

    陈文涛,副研究员。

    史旦达,教授。

通讯作者:

** 焦宇(1981—),男,河南汝州人,博士,副教授,主要从事船舶与海工安全与应急研究。E-mail:
Feature mining and causative analysis of fire accidents in ship repair and building enterprises
Xian LI1 , Yu JIAO1, ** , Wentao CHEN2, Danda SHI1, Yutao KANG1
Affiliations
  • 1 College of Ocean Science and Engineering,Shanghai Maritime University,Shanghai 201306,China
  • 2 Safety Development Research Center,Information Research Institute of Ministry of Emergency Management,Shanghai 201401,China
出版时间: 2024-03-28 doi: 10.16265/j.cnki.issn1003-3033.2024.03.0368
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为探究船舶修造企业(SRBE)火灾事故的特征和致因,运用数理统计方法研究118起火灾事故,从事故的时空属性、火灾三要素和伤害严重程度进行事故特征挖掘;并基于改进的人因分析与分类系统(HFACS-SRBE)事故致因模型,采用卡方检验、让步比(OR)、克莱姆V系数(Cramer' s V)方法,分析致因因素之间的相关性及其强弱。结果表明:14:00—16:00最易发生火灾事故和人员伤亡;火灾事故主要发生地点在船舶区域,占比为33.90%;59.19%的点火源是动火作业;无人员伤害、轻伤和轻微伤、重伤和死亡数量比值为61:54:3。通过相关性及其强弱检验后确定15组相邻层级致因因素存在相关性,并得到26条完整事故致因链。其中,沟通与协调→运行计划不适当→不良心理状态→决策差错是导致船舶修造火灾事故发生关联性强度最大的事故致因链。

船舶修造企业(SRBE)  /  火灾事故  /  致因分析  /  人因分析与分类系统(HFACS)模型  /  卡方检验  /  让步比(OR)  /  克莱姆V系数(Cramer's V)

To investigate the features and causation factors of fire accidents in SRBE,118 fire accidents were studied using method of mathematical statistics. Firstly,accident features were mined in terms of the temporal and spatial attributes of accidents,the three elements of fire and the severity of injuries. Then,based on the improved HFACS-SRBE accident causation model,methods such as Chi-square test,OR and Cramer's V were used to analyze the correlations and their strength between the causal factors. The results show that 14:00-16:00 is the most prone to fire accidents and casualties. The main location of fire accidents is in the ship area,accounting for 33.90%. 59.19% of the ignition source comes from the ignition operation. Ratio of no injuries,slight and minor injuries,serious injuries and deaths is 61:54:3. Through the test of correlations and their strength,it is determined that 15 groups of adjacent level causal factors are correlated,and 26 complete accident causation chains are obtained. Covers communication and coordination→inappropriate operation plans→bad psychological state→decision-making errors is the accident causation chain with the greatest strength of correlation leading to the occurrence of fire accidents in ship repair and building enterprises.

ship repair and building enterprises(SRBE)  /  fire accident  /  causation analysis  /  human factors analysis and classification system (HFACS) model  /  Chi-square test  /  odds ratio (OR)  /  Cramer's V
李显, 焦宇, 陈文涛, 史旦达, 康与涛. 船舶修造企业火灾事故特征挖掘与致因分析. 中国安全科学学报, 2024 , 34 (3) : 29 -38 . DOI: 10.16265/j.cnki.issn1003-3033.2024.03.0368
Xian LI, Yu JIAO, Wentao CHEN, Danda SHI, Yutao KANG. Feature mining and causative analysis of fire accidents in ship repair and building enterprises[J]. China Safety Science Journal, 2024 , 34 (3) : 29 -38 . DOI: 10.16265/j.cnki.issn1003-3033.2024.03.0368
船舶修造具有劳动密集、技术密集、信息密集的行业特性,伴随事故高发风险,包括物体打击、触电、高处坠落、火灾和爆炸等[1]。其中,火灾对于船舶与海工装备修造进度影响较大。掌握船舶修造企业Ship Repair and Building Enterprises,SRBE)火灾事故特征和致因规律,对预防该类事故具有重要意义。
基于事故调查报告的统计分析可为事故特征研究提供有用信息[2-3]。丁永明[4]和王颖丽[5]等使用频数统计并研究造船厂工伤事故的多个维度,如事故数量、严重程度以及受伤人员年龄分布。此外,YONG[6]和YOU[7]等则进一步比较了事故作业过程中工人的熟练程度以及新老工人在事故伤害和事故数量方面的差异。目前,船舶事故致因研究多集中于船舶交通事故,如郑霞忠等[8]利用复杂网络模型研究了船舶碰撞;刘子涛[9]和肖仲明[10]等借助贝叶斯网络技术分析船舶倾覆和搁浅。相对而言,船舶修造事故相关致因研究较少。
鉴于此,笔者拟基于SRBE的火灾事故数据进行事故特征挖掘,根据SRBE火灾事故特征,提出SRBE人因分析与分类系统(Human Factors Analysis and Classification System-Ship Repair and Building Enterprises,HFACS-SRBE)事故致因分析模型,采用卡方检验、让步比(Odds Ratio,OR)、克莱姆V系数(Cramer's V)方法,分析致因因素之间的相关性及其强弱,以期为SRBE火灾事故预防,作业人员安全保障提供数据支撑,并为相关领域的从业者及监管部门提供决策参考。
数据来源于中国某著名造船集团安环部的事故数据库。该集团业务集造船和海洋工程装备建造、修理、改装和配套服务于一体。数据库中包含旗下各修造船子公司发生的各类事故报告文本数据。在处理数据时将SRBE业务归为3类,即船舶与海工(海洋工程装备)建造、修理改装、其他(配套服务)。
对于火灾事故数据提取依据如下:首先,考虑到火、爆、烟、燃等关键字,按照《企业职工伤亡事故分类标准》(GB/T 6441—1986)[11]中的事故类别,将数据库中的事故报告文本数据归类;进一步提取全部“火灾”事故类型数据;然后,从剩余全部数据中筛选出“灼烫”事故因接触点火源烧伤的数据和“触电”事故中因电气安全问题导致的人员烧伤数据;最后,获取该集团发生的火灾事故118起。
利用GB/T 6441—1986[11]和《企业职工伤亡事故调查分析规则》(GB/T 6442—1986)[12]帮助企业快速实现事故致因分类与分析,但是,使用该方法也有显著的局限性。由于上述标准颁布年份较早且适用于所有行业,没有考虑到具体行业的特性,所以,在分析事故致因时,企业安全管理人员依据标准中的原因分类很难找到对应的匹配项。
HFACS模型[13]基于瑞士奶酪模型提出,目前已成功应用于各类行业事故分析。考虑将其与采用标准分析的方法融合,结合SRBE火灾事故的特征,参考制造/化工企业事故致因HFACS框架[14-15]提出HFACS-SRBE模型。此模型包含4个层次,25个致因类别,具体架构如图1所示。
卡方检验和OR方法可在HFACS致因分析框架中明确不同层级因素之间的相关性[16],但是,相关性的强弱有待进一步检验。引入Cramer's V系数衡量致因因素之间的关联强度,公式为:
C r a m e r ' s V = χ 2 N ( k - 1 )
式中: χ 2为卡方统计值; N为检验涉及的样本量;k为任一变量的较小类别数。Cramer's V取值范围在0~1之间,数值越大,表示致因因素之间的关联性越强。
统计SRBE火灾事故时间特征分布,如图2所示。2004—2015年,SRBE火灾事故数量整体呈现增长趋势,且在2015年达到顶峰(15起),占全部事故数量的12.71%;2016年,事故数量相较于顶峰时减少46.67%;2016—2019年,事故数量形势趋于稳定,平均每年事故起数为8.5;2020—2022年,事故数量出现骤减,事故仅发生1~2起,且事故均发生在船舶与海工建造过程中,受伤人员数量趋势和事故数量相一致。事故调查报告记载的内容会随国家、行业标准/规划以及企业自身安全生产的要求而丰富和完善。自2013年起,事故调查报告中详细记载事故中涉及人员的信息,包含肇事者和受伤者。2016年,该集团大幅提升安全管理水平,使2016年的火灾事故数量骤减近半。受世界经济形势和疫情影响,2020年世界造船3大指数造船完工量、新接订单量和手持订单量分别同比下降10.79%、14.24%和14.18%,导致2020—2022年间的火灾事故骤减。
每月SRBE火灾事故数量和伤亡人数在1—12月的变化趋势一致。并非每起事故都会造成人员伤亡,且一起事故中多人受到伤害的案例较少,因此,每月伤亡人数总是不高于事故数量。5月发生的火灾事故和造成人员伤亡次数最多,占比为15.25%和18.31%,反之,2月份事故数量和造成人员伤亡次数最少,占比仅为3.39%和4.23%。SRBE生产活动会受到高温天气环境的影响,6—9月也贡献31.36%的火灾事故和32.39%人员伤亡。进一步提取该集团所有存在于建造阶段(分段建造、钢料加工、舾装、船台/船坞合拢、水下作业和试航交付)的事故数据共705起,其中,5月是发生事故次数第2的月份,为78起,高于平均每月事故数量的32.77%,2月发生事故量最少。因此,可将SRBE火灾事故月份特征与建造阶段的任务安排相联系。0:00—24:00发生火灾事故数量和伤亡人数呈现M型趋势,即双峰分布[17];14:00—16:00易于发生事故和人员伤亡,是生产作业员工和企业管理人员最需要警惕的阶段;少量火灾事故发生在深夜和凌晨(20:00—次日8:00),共20起,造成12人伤亡。
按照事故发生地点[18]和事故中伤亡人员统计所属车间/部门的事故空间分布,见表1。圆括号中的数值为伤亡人数,括号外的数值为事故起数,其中,内场是指除去码头或坞、船舶、车间外,造船厂内部的空间,比如食堂、通道等区域。船舶区域内发生的火灾事故和伤亡的人员最多,占比分别为33.90%和38.03%,其次是内场、码头或坞;厂区外涉及到员工宿舍(有些子企业员工宿舍在厂区内部)和厂区门口区域等,统计结果中只有1起员工宿舍空调自燃起火事故;虽然车间的人员涉及事故数量和伤亡人数占比高达91.53%和90.14%,但是,发生在车间内的事故数量和伤亡人数仅为4.24%和5.63%;事故人员所属车间集中在船体、机电和涂装车间,三者累计事故数量和伤亡人数占比达到67.80%和61.97%。
点火源、可燃物和助燃物是每起火灾事故中都并存的3要素。其中,助燃物在SRBE火灾事故中为空气/氧气;点火源划分为直接火源和间接火源,具体分类及说明见表2
表2可知:直接火源导致的火灾事故93起,占全部统计数据的78.81%,其中,涉及明火85起,占直接火源导致的事故比例为91.40%。在明火分类中,除只有3起人员未熄灭烟头乱丢弃导致的火灾外,剩下的4类点火源均在动火作业过程中产生,占全部统计数据的59.19 %。间接火源中,线路发热起火在加热自燃起火中占比最大,多为设备故障导致的火灾,如冰箱、空调、保险装置等。火碱水、乙炔等有强烈的化学反应性质的物质作为点火源在统计中出现3次,而物质本身自燃、聚焦起火以及雷击导致的高压放电导致的事故在统计中并未出现。因此,SRBE应该重点加强对动火作业的监管,并严格要求作业人员执行动火作业必备流程,同时,也应加强对生产生活设备的日常维护保养及检修。
考虑到SRBE特性,并结合A—F 这6类火灾划分方式[19],将事故后果(设备财产损失、人员伤亡、环境污染)作为进行可燃物种类的划分依据。需要说明的是,在SRBE火灾事故调查报告中鲜有提及环境污染,故在可燃物种类划分时只涉及到设备财产和人员伤亡。其中,设备财产损失的火灾事故中包括A—F 类火灾划分方式中的可燃物种类;人员伤亡火灾事故中根据点火源是否直接接触人体组织将可燃物划分为人体组织和设备财产+人体组织2大类,而此时的设备财产是衣物(防护用具+衣着),具体分类及说明见表3
表3可知:在导致设备财产损失的可燃物中,涉及油箱、塑料桶、管线、管带等设备最多,共25起,占全部统计事故的21.19%;涉及电器设备、布料和化学品等可燃物均为14起,占比11.86%。在造成人体组织伤害的部位中,面颌部、脑袋、眼睛、耳朵和腕及手等被点火源直接造成伤害的事故有28起,占比23.73%,此类事故主要由于作业人员未佩戴防护用具。点火源通过先点燃作业人员衣物再造成人体组织伤害的事故共40起,占比33.90%。
海因里希三角形揭示了事故的严重程度和事故发生的次数或者频率之间的关系:如果轻微事故的发生频率很高,当事故次数达到一定数量时,企业生产过程中产生重伤或死亡事故可能就无法避免。按照我国《人体损伤程度鉴定标准》[20],将SRBE火灾事故严重程度划分为轻微伤、轻伤、重伤和死亡事故,同时,考虑到无人员伤害的事故,统计各类事故发生的频数,见表4。结果显示:火灾发生导致的无伤害事故数量最多,占比为51.70%,其次是轻伤和轻微伤事故,占比为45.76%,重伤和死亡事故最少,占比仅为2.54%。
对比海因里希三角形,SRBE火灾事故三角形中,无人员伤害:轻伤和轻微伤:重伤和死亡的比值为61:54:3,如图3所示。事故中造成伤害的数量和严重程度对比海因里希三角形有着明显提升,这一结果也和火灾易对人员造成伤害的危险特性相关,表3中,火灾造成人体组织的伤害事故占全部事故的57.63%。SRBE生产中,火灾集中发生在船舶与海工建造、修理和改装阶段,事故占比达80.51%,而且造成的人员重伤和死亡的事故也均出现在此阶段。
火灾发生时是否有应急处置与救援介入可作为评判火灾事故严重程度的因素,亦有助于判断企业自身应急力量的强弱。以关键词“警”(包含报警、出警、接警、火警)和“消防队”为筛选依据,在118起事故报告中提取满足要求的事故共45起,占比约达到38.14%,说明60%以上的火灾处置可依靠企业自身的应急能力。
基于扎根理论[21]对事故调查报告中涉及到事故致因的语句编码后形成初始概念,将初始概念进行归纳形成初始范畴(对应事故致因的表现形式),接着将初始范畴映射到HFACS-SRBE模型各层级的类别中,最后统计各层级事故因因素出现频次及占比,见表5
表5可知:组织影响层级的事故致因因素发生的次数最多,为 521 次,占比为31.5%。主要涉及安全管理制度未强制实施、安全氛围未形成、风险管理政策不健全和缺乏沟通与交流。不安全行为的前提条件层级涉及事故致因因素中包含人-机-环方面共 489 次,占比为29.5%。事故中警惕性不强、注意力不集中和未接受过培训为主要的人员因素;其他不良天气、高温、强风、作业场地杂乱为突出的环境因素;技术装备集中体现在无PPE防护、保险、信号等装置缺乏。不安全行为层级涉及事故致因因素 331 次,占比为 20%,具体表现在人员操作不当、未评估设备风险和工作前检查不足。不安全监督层级涉及事故致因因素 315 次,占比为 19%,其中,安全培训不到位、未进行监督和未进行隐患整改追查占主要部分。
利用Python软件筛选出各致因因素之间卡方检验 p < 0.05的因素,然后借助SPSS软件求解OR和Cramer'sV值,并将相邻层级OR值大于1的因素整理见表6
表6可知:在HFACS-SRBE模型中,SRBE火灾事故致因因素相邻层级间共有15组相关关系,相关性强弱取值在0.210~0.445之间。关联性最强的2组致因因素为变更管理与计划任务不恰当、沟通与协调和计划任务不恰当。基于HFACS理论,当各个层级的致因因素同时出现或者次第出现时SRBE火灾事故才会发生。15组相邻层级致因因素相关关系中共梳理出26条完整事故致因链,其中,最强相关的事故致因链为沟通与协调→运行计划不适当→不良心理状态→决策差错,进一步绘制所有相邻层级致因因素的相关关系图,如图4所示。
1) 首次将火灾3要素纳入SRBE火灾事故研究中,给出点火源具体分类及分类说明、可燃物种类的划分依据。从事故的时空属性、火灾3要素和伤害严重程度归纳SRBE火灾事故特征。结果表明:0:00—24:00,火灾事故数量和伤亡人数呈现双峰分布;船舶与海工建造阶段火灾事故频发;船舶区域内发生的火灾事故和伤亡的人员最多;59.19%的点火源来源于动火作业;事故造成人员伤害多为轻微伤/轻伤;火灾造成人体组织的伤害事故占全部事故的57.63%。
2) 将HFACS模型与采用依据GB/T 6441—1986[11]和GB/T 6442—1986[12]标准分析的方法相融合,提出适用于SRBE火灾事故致因HFACS-SRBE模型,此模型包含4个层次,25个致因类别。改进后的模型能完善仅采用标准进行事故致因归类困难的方法。
3) 通过挖掘118起事故调查报告中的致因因素,得到15组相邻层级致因因素的相关关系,相关关系强度在0.210~0.445之间。提取完整事故致因链26条,其中,沟通与协调→运行计划不适当→不良心理状态→决策差错是导致SRBE火灾事故发生关联性强度最大的事故致因链。
  • 国家自然科学基金资助(51109127)
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2024年第34卷第3期
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doi: 10.16265/j.cnki.issn1003-3033.2024.03.0368
  • 接收时间:2023-09-15
  • 首发时间:2025-07-09
  • 出版时间:2024-03-28
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  • 收稿日期:2023-09-15
  • 修回日期:2023-12-19
基金
国家自然科学基金资助(51109127)
作者信息
    1 上海海事大学 海洋科学与工程学院,上海 201306
    2 应急管理部信息研究院 安全发展研究中心,上海 201401

通讯作者:

** 焦宇(1981—),男,河南汝州人,博士,副教授,主要从事船舶与海工安全与应急研究。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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