Article(id=1149741762824025008, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149741761771258326, articleNumber=1003-3033(2024)02-0124-07, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2024.02.0293, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1692201600000, receivedDateStr=2023-08-17, revisedDate=1700928000000, revisedDateStr=2023-11-26, acceptedDate=null, acceptedDateStr=null, onlineDate=1752049397425, onlineDateStr=2025-07-09, pubDate=1709049600000, pubDateStr=2024-02-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752049397425, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752049397425, creator=13701087609, updateTime=1752049397425, updator=13701087609, issue=Issue{id=1149741761771258326, tenantId=1146029695717560320, journalId=1146031787341344770, year='2024', volume='34', issue='2', 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=1752049397175, creator=13701087609, updateTime=1756468934610, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1168278645379440971, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149741761771258326, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1168278645379440972, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149741761771258326, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=124, endPage=130, ext={EN=ArticleExt(id=1149741763067294642, articleId=1149741762824025008, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=BIM simulation analysis on visual accessibility of heavy construction machinery installation and lifting operation, columnId=1149733269173878863, journalTitle=China Safety Science Journal, columnName=Safety engineering technology, runingTitle=null, highlight=null, articleAbstract=

In order to improve the safety efficiency of heavy construction machinery installation and lifting operation and improve the visibility of installation and lifting operation personnel,a multi-agent visual accessibility BIM simulation method based on the visual cone method was proposed. The multi-agent visual task of the heavy construction machinery was obtained through the decomposition of the visual task of heavy construction machinery. Taking the installation and dismantling operation of the wk-35 electric shovel as the research object,the multi-agent visual task of hoisting driver,signal operator and cable operator was analyzed,and the multi-agent visual BIM simulation scene of installation,dismantling and hoisting operation was constructed by using Computer Aided Three-dimensional Interactive Application (CATIA) human factor simulation module. The visual cone method was used to calculate the multi-agent visual accessibility value in the process of installation and lifting. The process parameters of the BIM model were adjusted,the trend of multi-agent vision was deduced,and the multi-agent visual accessibility of installation,disassembly and hoisting was evaluated. The simulation results show that the visual accessibility of the lifting driver is poor in the process of lifting and descending,but good in the process of translation. The position of the signal operator and cable man is closely related to their visual accessibility. The visual accessibility of the signal operator is best when the visual field of view just covers the lifting driver and cable man. The cable man needs to constantly adjust his position to achieve the best visual accessibility.

, correspAuthors=Faxing DU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Xiazhong ZHENG, Jun WU, Lianghai JIN, Faxing DU), CN=ArticleExt(id=1149741772617723923, articleId=1149741762824025008, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=重型施工机械安拆吊装作业视觉可达性BIM仿真分析, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为提高重型施工机械安拆吊装作业安全工效,改善安拆作业过程中人员的可视性,提出基于可视锥法的多主体视觉可达性建筑信息模型(BIM)仿真方法。首先,通过重型施工机械视觉任务分解,得到重型施工机械多主体视觉任务;其次,以wk-35型电铲安拆作业为研究对象,分析起重驾驶司机-信号工-司索工多主体视觉任务,运用计算机辅助三维交互应用(CATIA)人因仿真模块,构建安拆吊装作业多主体视觉的BIM仿真场景;然后,采用可视锥法,计算安拆吊装作业过程多主体视觉可达性量值,测度多主体视觉可达性水平,构建重型机械施工机械多主体视觉评价模型;最后,调节BIM模型的过程参数,推演多主体视觉变化趋势,评价安拆吊装作业多主体视觉可达性。结果表明:安拆作业中起重司机在起升下降过程中视觉可达性较差,在平移过程中视觉可达性较好;信号工和司索工的位置与其视觉可达性联系紧密,当信号工处于视野刚好覆盖起重司机和司索工的位置时,其视觉可达性最好,而司索工需不断调整位置,使其视觉可达性达到最佳。

, correspAuthors=杜发兴, authorNote=null, correspAuthorsNote=
** 杜发兴(1977—),男,重庆人,博士,副教授,主要从事地质灾害防治研究工作。E-mail:
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郑霞忠 (1963—),男,湖北鄂州人,博士,教授,博士生导师,主要从事安全科学与工程方面的研究。E-mail:

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郑霞忠 (1963—),男,湖北鄂州人,博士,教授,博士生导师,主要从事安全科学与工程方面的研究。E-mail:

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郑霞忠 (1963—),男,湖北鄂州人,博士,教授,博士生导师,主要从事安全科学与工程方面的研究。E-mail:

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ArticleFig(id=1168128752866304219, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762824025008, language=EN, label=Fig.6, caption=Change of vision for lifting drivers,signalmen and cablemen, figureFileSmall=jST2x6mRBlg6m5g5tI9czA==, figureFileBig=hIB8yTVv3bssOhe7wKDfYg==, tableContent=null), ArticleFig(id=1168128752920830172, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762824025008, language=CN, label=图6, caption=起重司机、信号工和司索工视野变化, figureFileSmall=jST2x6mRBlg6m5g5tI9czA==, figureFileBig=hIB8yTVv3bssOhe7wKDfYg==, tableContent=null), ArticleFig(id=1168128752996327645, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762824025008, language=EN, label=Tab.1, caption=

Visual cone grading of multi-agent at different operation time

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评分主体 作业时刻 平均分
t1 t2 t3 t4 t5
起重司机得分p1 0.607 0.617 0.619 0.628 0.608 0.616
信号工得分p2 0.663 0.652 0.642 0.648 0.604 0.642
司索工得分p3 0.613 0.649 0.645 0.667 0.673 0.650
), ArticleFig(id=1168128753055047902, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762824025008, language=CN, label=表1, caption=

多主体不同作业时刻可视锥法评分

, figureFileSmall=null, figureFileBig=null, tableContent=
评分主体 作业时刻 平均分
t1 t2 t3 t4 t5
起重司机得分p1 0.607 0.617 0.619 0.628 0.608 0.616
信号工得分p2 0.663 0.652 0.642 0.648 0.604 0.642
司索工得分p3 0.613 0.649 0.645 0.667 0.673 0.650
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重型施工机械安拆吊装作业视觉可达性BIM仿真分析
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郑霞忠 1, 2, 3 , 吴俊 2 , 晋良海 1, 2, 3 , 杜发兴 1, 2, 4, **
中国安全科学学报 | 安全工程技术 2024,34(2): 124-130
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中国安全科学学报 | 安全工程技术 2024, 34(2): 124-130
重型施工机械安拆吊装作业视觉可达性BIM仿真分析
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郑霞忠1, 2, 3 , 吴俊2, 晋良海1, 2, 3, 杜发兴1, 2, 4, **
作者信息
  • 1 三峡大学 水电工程施工与管理湖北省重点实验室,湖北 宜昌 443002
  • 2 三峡大学 水利与环境学院,湖北 宜昌 443002
  • 3 三峡大学 安全生产标准化评审中心,湖北 宜昌 443002
  • 4 湖北安环科技有限公司,湖北 宜昌 443002
  • 郑霞忠 (1963—),男,湖北鄂州人,博士,教授,博士生导师,主要从事安全科学与工程方面的研究。E-mail:

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** 杜发兴(1977—),男,重庆人,博士,副教授,主要从事地质灾害防治研究工作。E-mail:
BIM simulation analysis on visual accessibility of heavy construction machinery installation and lifting operation
Xiazhong ZHENG1, 2, 3 , Jun WU2, Lianghai JIN1, 2, 3, Faxing DU1, 2, 4, **
Affiliations
  • 1 Hubei Key Laboratory of Construction and Management in Hydropower Engineering,China Three Gorges University,Yichang Hubei 443002,China
  • 2 College of Hydraulic & Environmental Engineering,Three Gorges University,Yichang Hubei 443002,China
  • 3 Center of Standardization Evaluation for Production Safety,China Three Gorges University,Yichang Hubei 443002,China
  • 4 Hubei Anhuan Technology,Yichang Hubei 443002,China
出版时间: 2024-02-28 doi: 10.16265/j.cnki.issn1003-3033.2024.02.0293
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为提高重型施工机械安拆吊装作业安全工效,改善安拆作业过程中人员的可视性,提出基于可视锥法的多主体视觉可达性建筑信息模型(BIM)仿真方法。首先,通过重型施工机械视觉任务分解,得到重型施工机械多主体视觉任务;其次,以wk-35型电铲安拆作业为研究对象,分析起重驾驶司机-信号工-司索工多主体视觉任务,运用计算机辅助三维交互应用(CATIA)人因仿真模块,构建安拆吊装作业多主体视觉的BIM仿真场景;然后,采用可视锥法,计算安拆吊装作业过程多主体视觉可达性量值,测度多主体视觉可达性水平,构建重型机械施工机械多主体视觉评价模型;最后,调节BIM模型的过程参数,推演多主体视觉变化趋势,评价安拆吊装作业多主体视觉可达性。结果表明:安拆作业中起重司机在起升下降过程中视觉可达性较差,在平移过程中视觉可达性较好;信号工和司索工的位置与其视觉可达性联系紧密,当信号工处于视野刚好覆盖起重司机和司索工的位置时,其视觉可达性最好,而司索工需不断调整位置,使其视觉可达性达到最佳。

重型施工机械  /  安拆吊装作业  /  视觉可达性  /  多主体  /  建筑信息模型(BIM)仿真

In order to improve the safety efficiency of heavy construction machinery installation and lifting operation and improve the visibility of installation and lifting operation personnel,a multi-agent visual accessibility BIM simulation method based on the visual cone method was proposed. The multi-agent visual task of the heavy construction machinery was obtained through the decomposition of the visual task of heavy construction machinery. Taking the installation and dismantling operation of the wk-35 electric shovel as the research object,the multi-agent visual task of hoisting driver,signal operator and cable operator was analyzed,and the multi-agent visual BIM simulation scene of installation,dismantling and hoisting operation was constructed by using Computer Aided Three-dimensional Interactive Application (CATIA) human factor simulation module. The visual cone method was used to calculate the multi-agent visual accessibility value in the process of installation and lifting. The process parameters of the BIM model were adjusted,the trend of multi-agent vision was deduced,and the multi-agent visual accessibility of installation,disassembly and hoisting was evaluated. The simulation results show that the visual accessibility of the lifting driver is poor in the process of lifting and descending,but good in the process of translation. The position of the signal operator and cable man is closely related to their visual accessibility. The visual accessibility of the signal operator is best when the visual field of view just covers the lifting driver and cable man. The cable man needs to constantly adjust his position to achieve the best visual accessibility.

heavy construction machinery  /  install the lifting operation  /  visual accessibility  /  multi-agent  /  building information modeling(BIM) simulation
郑霞忠, 吴俊, 晋良海, 杜发兴. 重型施工机械安拆吊装作业视觉可达性BIM仿真分析. 中国安全科学学报, 2024 , 34 (2) : 124 -130 . DOI: 10.16265/j.cnki.issn1003-3033.2024.02.0293
Xiazhong ZHENG, Jun WU, Lianghai JIN, Faxing DU. BIM simulation analysis on visual accessibility of heavy construction machinery installation and lifting operation[J]. China Safety Science Journal, 2024 , 34 (2) : 124 -130 . DOI: 10.16265/j.cnki.issn1003-3033.2024.02.0293
重型施工机械安拆吊装作业风险大,事故频发。起重吊装作业是由起重司机-信号工-司索工组成的群体性活动,相互之间需要密切的视觉配合。然而,由于施工平面布置较差,人员安全占位不合理,导致作业人员视觉可达性水平较低,极易引发碰撞事故。截至2022年底,全国特种设备事故共结案60起(不包含港澳台)[1],据分析,违章作业是造成事故的主要原因,占比80%。其中吊装作业过程的不安全占位为重要原因,而作业人员的不安全占位和作业人员的视觉可达性水平息息相关[2]。因此,研究重型机械安拆吊装作业的多主体视觉可达性,对提升安拆吊装作业操作行为的安全工效水平具有重要意义。
国内外学者对视觉可达性进行了相关研究,在安拆作业安全方面,GOLCARENARENJI等[3]为提高起重机操作员在复杂工业操作环境中的可见度,提出了一种自动和精确的俯视图人体检测解决方案。SHIN等[4]通过分析韩国近年来起重机安拆事故,发现工人的不安全行为是导致事故发生的重要原因。赵挺生等[5]采用系统理论事故模型及过程分析法,构建了塔吊安装与拆卸作业模型,提高了建筑施工塔吊安装与拆卸作业安全管理水平。李忠辉等[6]利用3DMAX软件建立了煤巷掘进突出危险可视化三维模型,提高了煤巷掘进工作面煤与瓦斯突出危险性的预测准确率,并实现了预测结果的可视化显示。在优化作业视觉方面,崔晓风等[7]基于人机工程理论,建立了虚拟仿真维修平台,通过构造虚拟人视野锥,综合考虑可视距离和可视角度对人的视觉可达性的影响,提出了定量评价方法。晋良海等[8]考虑可视角度和可视距离,分析了最佳视野和最大视野2种可视锥,并根据作业任务构建虚拟场景,测度起重作业视觉信息驱动水平。何春华等[9]基于人眼视野区域建立了视野锥维修可视性分析模型,但鉴于其无法定量评估可视性及视野遮挡的情况,通过软件的二次开发功能,提升了维修可视性分析能力。WU Weiwei等[10]提出了一种自动能见度评估方法,设计并构建了符合视场生理特性的视域模型和能见度影响因素的计算模型,有效解决了潜在的可视性相关工效学问题。BRKIC等[11]提出了基于图纸人体模型和运动学建模的起重机舱室人体工程学评估方法,确定了与能见度和姿态相关的现有起重机舱室的关键特征,并提出了安全标准方面的修改意见。
以上研究成果未对视觉任务进行细粒度化的分解,也未涉及重型施工机械安拆吊装作业多主体视觉可达性水平的测度,鉴于此,笔者将分析重型施工机械安拆吊装作业视觉任务特点,构建多主体视觉可达性建筑信息(Building Information Modeling,BIM)仿真模型,推演安拆作业多主体视觉动态变化过程,测算视觉可达性量值,为提升重型施工机械安拆吊装作业安全工效提供理论依据。
重型施工机械安拆作业过程中,大量工程安拆物件摆放位置错综复杂,为满足施工设计要求,需频繁通过吊装作业来完成物件的安拆。起重驾驶员、信号工、卸货司索工需实时观察和掌握人-机-物-环的态势变化情况,并依据这些视野信息结果来完成取料、运移、安拆等起重操作。视觉是人最主要感知方式,由于视觉信息是人类信息的主要来源,人类有80%的信息是通过视觉获得的。而人的感知引导着人的行为决策,人会依据视觉获得的感知采取相应行动[12]。因此,对视觉可达性的研究既是安拆作业安全的重要一环,又是改善安拆作业环境的重要方法。
重型施工机械安拆吊装作业复杂,总体可以分为:起重机起吊机械各部件和作业人员手动进行各部件的安拆,而起重作业的视觉可达性尤为重要。根据起重机起吊操作视频以及资料绘制安拆吊装作业单次循环作业图如图1所示。
分析涉及到的作业人员:起重司机、信号工、司索工三者的作业职责,从多主体作业职责中分析每个人的视觉任务。起重司机是整个安拆作业的核心位置,既要兼顾自己的操作平台,也要时刻关注信号工的指挥。司索工处于安拆作业的起始和结束的重要位置,在安拆吊装作业开始之前要清扫现场,避免不安全的因素,然后要根据不同的目标物选择不同的绑扎方式以及不同的吊运工具,司索工要指挥起重司机将目标物安放在指定位置,在安拆作业过程中每个作业人员都很重要,其中起重司机、起重信号工、司索工三者的视觉任务和可视性的优良将直接影响安拆作业的有效进行以及作业过程中的安全。通过分析起重司机、信号工、司索工三者的工作职责,得到安拆作业多主体的视觉任务图,如图2所示。
视野分为垂直视角和水平视角2个主要部分,根据这2种视角的视野范围标准设定,可以确定出最佳视野区域和最大视野区域。从人体眼睛的生物学特征来看,这2个视场区的边界是由一个锥形形状的空间构成,其横截面呈现为椭圆形。所构成的人眼多位置视野域如图3所示。
其中构成的最佳角度视野区域是一个在正常视野附近,上下左右各15°的圆锥区域。引入能够精确测量起重驾驶员的可视性水平的改进可视锥法,这种方法基于坐标变换原理,并结合了可视角度和可视距离的信息,从而为起重驾驶员的可视性提供了精准的定量评估。首先,分别构建虚拟场景坐标系A、虚拟人坐标系B、可视锥坐标系O共3个主要用于坐标变换测量的层次坐标系。在虚拟人坐标系B中建立可视锥坐标系O,在虚拟场景坐标系A中建立虚拟人坐标系B。对于O坐标系,其原点是驾驶员的眼睛中心,而X轴代表垂直于视野的方向,Y轴代表水平方向,Z轴则表示正常的视线。另一方面,B坐标系的原点是虚拟人物站立时臀部的中心,X轴指向前方,Y轴指向左侧,而Z轴朝上。为了阐明坐标转换的过程,选择AB等2个坐标系作为例子。具体来说,AB之间的坐标转换关系可以参考图4
在最普遍的情况下,坐标系A与坐标系B的原点不重合,方向也不同。这里采用位置矢量 ApBO 描述坐标系B的坐标原点对于坐标系A的方位,用旋转矩阵   B AR描述标系B相对坐标系A的方位,对于任一点p在坐标系AB中的描述 AP和BP 具有如下变换关系:
  A P = B A R B P + A P B O
旋转矩阵   B AR可以通过下列旋转矩阵变换等式表示:
  B A R = R ( ε X ) R ( ε Y ) R ( ε Z )
其中
R ( ε X ) = 1 0 0 0 0 c o s α s i n α 0 0 - s i n α c o s α 0 0 0 0 1
R ( ε Y ) = s i n β 0 - s i n β 0 0 1 0 0 s i n β 0 c o s β 0 0 0 0 1
R ( ε Z ) = c o s θ s i n θ 0 0 - s i n θ c o s θ 0 0 0 0 1 0 0 0 0 1
式中:εXεYεZ分别为坐标系B相对于坐标系A关于 XYZ 等3个坐标轴的相对旋转量;αβθ分别为坐标系B绕坐标系AXYZ轴旋转的角度,(°)。
对(1)式进行齐次变换:
  A P = B A M B P
齐次变换矩阵   B AM是4×4的方阵,APBP是 4×1 的列向量 B AT具有如下转换形式:
  B A T =   B A R   A P B O 0 0
坐标系A与坐标系C间的变换式为:
M = A 1 A 2
式中:A1为虚拟场景坐标系相对于虚拟人坐标系B的位置;A2为虚拟人坐标系相对于可视锥坐标系O的位置。
根据我国成年人人体主要尺寸的数据,选择 95%的人体上臂臂长 0.791 m,作为可视锥高度。在可视锥坐标系中,分别建立最佳视野可视锥与最大视野可视锥。
其中,最佳视野可视锥的参数方程为:
x o 1 = 0.267   9 u s i n v y o 1 = 0.267   9 u c o s v z o 1 = u
最大视野可视锥的参数方程为:
x o 2 = 0.700   2 u s i n v y o 2 = 0.577   4 u c o s v z o 2 = u
经坐标变换后可得起重物形心在可视锥坐标系O中的坐标为,坐标系O中形心坐标 C与原点O的距离为:
d 1 = x o 1 2 + y o 1 2 + z o 1 2
由可视锥坐标系的位置可得可视角度α=arccos(d2/d1),可视距离为d2=Zo1,可视角度的评分为pj=α/45,可视距离的评分pk=d2/39.5,综合考虑可视角度与可视距离,起重物的最终可视性评分计算式为:
p = β 2 ( p j + p k )
式中β为可视区域因子。根据人眼视野范围,若在人眼视野最佳范围内时β = 1,若不满足时β = 1.2。可视性水平评分范围为0≤p≤1,p值越大,表明作业对象的可视性水平越低。
以wk-35型电铲为例,其中标准铲斗容量35 m3,工作重量1 035 t,开斗电动机功率为11 kW,履带宽度10.8 m。电铲作为重型施工机械,是千万吨级露天矿山的主要采掘设备。安拆电铲步骤复杂,可将电铲分为回转平台上部、回转平台下部、工作装置以及铲斗等。经分析电铲在安装和拆卸的过程是一个可逆的过程,所以选取安装过程作为研究。研究对象分别为作业司机、信号工、司索工,结合三者的可视锥得分,得出整个安拆吊装作业过程作业人员的综合视觉可达性评分。
视觉可达性是重型施工机械安拆吊装作业安全的重要因素,依据可视锥法以及BIM仿真方法,提出基于可视锥法的多主体视觉可达性BIM仿真方法。步骤为:收集相关资料和信息;分析安拆吊装作业多主体视觉任务;构建安拆吊装作业多主体视觉任务联系:提出安拆吊装作业改良可视锥法;运用BIM仿真软件建立安拆吊装作业模型;结合可视锥法和仿真软件中的人机工程分析模块分析安拆吊装作业多主体视态变化,完成安拆吊装作业多主体视觉可达性评价。在安拆电铲回转平台的过程中,起重司机、信号工以及司索工的可视性水平是重型施工机械安拆效率的关键因素。
选取计算机辅助三维交互应用(Computer Aided Three-dimensional Interactive Application,CATAIA)软件建立wk-35型电铲安拆吊装过程仿真模型,以收集到实际场景下作业人员在安拆电铲的资料为背景,选取作业人员在通过起重机安拆吊装回转平台上部构件的过程,通过CATIA软件的人机工程建立安拆吊装作业起重场景以及运动关系如图5所示。
图5可以看出,左侧似履带的构件为电铲的底部构件,右侧为汽车式起重机,悬挂着的物体为被吊运的目标物。在起重场景中信号工站在场地中间,负责统筹协调完成整个起重过程的起吊。司索工站在电铲回转平台上部,负责卸货作业。起重司机在汽车式起重机中负责安拆吊物作业的起重作业。在电铲安装的过程中,回转平台上部构件需要通过起重机来完成起吊,起吊过程中由于起重司机本身视野狭小,起吊的物件较大,起吊过程中司机的视野在随着起吊高度的变化中受到不同程度的遮挡,为了研究起重司机的可视性,更好确定起重司机的视觉变化,基于改良可视锥评价方法,结合CATIA软件中的视野功能,模拟起重过程中起重司机、卸货工、司索工的视野变化,得出整个作业过程中的视态,结合5点做图法,选取电铲安拆作业过程5个重要时刻的视态图,如图6示。其中,t1时刻为吊物开始前的视觉状态;t2时刻为吊物上升过程中的视觉状态;t3时刻为吊物处于最高状态时的视觉状态;t4时刻为起吊下降过程中的视觉状态;t5时刻为起重作业完成后的视觉状态。
信号工的可视性与其自身的位置相关,当使信号工处于良好的位置时,整个吊装作业的可视性会有明显提升。文中将信号工放置在一个良好的位置,此时信号工可以通过头部的上下左右转动扩大范围视野来保证自己处于一个良好的可视性水平。信号工的可视性由于受距离和角度的影响,在上升以及平移过程中较好,在下降过程中较差。同理司索工也会通过头部的上下左右转动来改变自己的可视性,在目标物慢慢起升的过程中,司索工的可视性由于可视距离影响较差,在目标物下落过程中,司索工需要通过不断调整自己与目标物的距离,以达到优化自己可视性的目的。
基于可视锥的视觉可达性评价方法,在作业时刻t1中,可以根据人的视野范围图,结合CATIA软件中人机工程分析模块中的视野功能,可知:目标不位于最佳视野区域内,经过计算在式(10)内,因此,取β= 1.2。根据可视锥法计算起重吊装物体形心坐标为(-41.17,51.85,56.47 ),将起重吊物体形心坐标分别代入式(11)与式(12)后得,可视角度和可视距离分别为 21.5 °和21.07 m;综合可视距离得分与可视角度得分,最后得到起重驾驶作业得可视性得分为0.607。同理可得,作业时刻t2t3t4t5的基于可视锥法的评分分别为0.617、0.619、0.628、0.608。从5个作业时刻的得分可以看出,起重司机的可视性水平基本都处于可视性一般的行列,由此可见:在整个起重过程中,作业司机的视觉可达性并未处于最好的状态,需要通过进一步的改善来提高其作业过程中的可视性。分析起重司机整个过程中的可视锥得分,其中作业时刻t1得分为0.607,是可视性最差的时刻。分析可得:初始状态下起重机和目标物位于同一直线上,导致起重司机的可视性最差,而随着起吊任务的逐渐进行,起重司机的可视性在慢慢提高。依据上述方法分别计算信号工和司索工在整个安拆吊装作业过程中的可视锥得分,根据视态变化图可以看出目标吊物都处于视野最佳范围内,经可视锥法计算目标吊物的视野范围也处于式(9)内,故此处的β取1,通过得分结果可知信号工和司索工的可视性较起重司机好,但也未处于可视性良好的行列,其中信号工的作业位置是提高信号工作业可视性的重要因素。根据可视锥评分方法得到信号工、卸货司索工得分见表1
结合起重司机可视锥评分得分以及辅助工作人员可视锥得分,综合二者得到电铲安拆过程的可视性得分。按照层次分析法确定权重的方法,比较起重司机、信号工、司索工三者在起吊过程中的视觉重要性,其中起重司机>信号工>司索工。利用方根法得到判断矩阵的特征向量为α=(2.466 2,1,0.405)T。获得起重司机在整个安拆吊装作业过程中的视觉权重ω1为63%,信号工在整个安拆吊装作业过程中的视觉权重ω2为26%,卸货司索工在整个安拆吊装作业过程中的视觉权重ω3为11%。则综合视觉可达性评分pk可由下式计算:
p k = p 1 × ω 1 + p 2 × ω 2 + p 3 × ω 3
式中:pk为综合视觉可达性评分;ω1为起重司机的视觉权重,ω2为信号工的视觉权重,ω3为司索工的视觉权重。由式(13)可得综合可视锥得分为0.627,可以看出在信号工和司索工的协助下,整个起重过程中的可视性得到了改善。通过将信号工放在不同位置,发现信号工的视觉可达性在不断变化,可见信号工的视觉可达性与其所在的位置紧密相关,研究发现,将信号工放置在刚好视野覆盖司索工以及起重司机的时候,信号工的视觉可达性达到最佳。
1) 从BIM仿真分析结果可以看出,整个安拆作业起重过程视觉可达性有待改善,其中起重司机的视觉可达性在起升过程中较差,随着平移过程的进行,起重司机的视觉可达性逐渐提高。
2) 信号工和司索工的位置对起重司机的可视性至关重要。通过三者的相关沟通协调,可以弥补相互之间的视觉信息不足,提高整个安拆吊装作业的视觉可达性,减少起吊过程中的碰撞风险。
3) 今后还需在以下几方面加以改善:将信号工放在视野最佳的位置;司索工要根据起吊物的状态不断调整自己的位置,进行视觉补偿。例如:可以安装多个摄像头,弥补作业人员的视觉盲区,通过管控人员的集中调度,降低作业过程中因可视性较低导致的作业风险。
  • 国家自然科学基金面上项目资助(51878385)
  • 国家自然科学基金面上项目资助(52179136)
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doi: 10.16265/j.cnki.issn1003-3033.2024.02.0293
  • 接收时间:2023-08-17
  • 首发时间:2025-07-09
  • 出版时间:2024-02-28
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  • 收稿日期:2023-08-17
  • 修回日期:2023-11-26
基金
国家自然科学基金面上项目资助(51878385)
国家自然科学基金面上项目资助(52179136)
作者信息
    1 三峡大学 水电工程施工与管理湖北省重点实验室,湖北 宜昌 443002
    2 三峡大学 水利与环境学院,湖北 宜昌 443002
    3 三峡大学 安全生产标准化评审中心,湖北 宜昌 443002
    4 湖北安环科技有限公司,湖北 宜昌 443002

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** 杜发兴(1977—),男,重庆人,博士,副教授,主要从事地质灾害防治研究工作。E-mail:
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2种不同金属材料的力学参数

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genus
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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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