Safety risk assessment for port quay crane installation construction

doi:10.16265/j.cnki.issn1003-3033.2022.12.2769

Abstract

Abstract:

In order to improve the safety of port quayside bridge construction, the risk level of quayside bridge installation was determined by identifying the risk factors of quay crane installation. With the safety risk assessment of quay crane installation as the top goal, a risk assessment model based on (C-AHP) was proposed. Firstly, a quay crane installation assessment index system from 4 aspects, human, machine, environment and management, was constructed. The concept of the cloud model was introduced to modify the traditional AHP method scalar theory. The randomness, fuzziness and dispersion of the system were represented by 3 numerical features, expectation, entropy and super entropy, so as to determine the relative weights of each index and the cloud numerical features of risk values. The randomness and fuzziness of each index were quantified by the cloud model, and the overall evaluation results were obtained. Finally, an example analysis was carried out based on the installation of a quay crane at a container terminal in Tianjin port. The results show that the equipment factor has the highest degree of influence on the safety risk of quay crane installation construction, followed by environmental factors, management factors and personnel factors. The overall risk value for the construction safety of the quay crane installation is 47.769, with a risk level of II, which is within the acceptable guideline range and in line with the actual assessment results.

Key words: port, quay crane, installation construction, safety risk assessment, cloud analytic hierarchy process(C-AHP), cloud model

JI Keke, LI Zhengzhong, LIU Shuang, ZHANG Xin, WANG Guangyan, WANG Xuting. Safety risk assessment for port quay crane installation construction[J]. China Safety Science Journal, 2022, 32(12): 102-109.

Figures/Tables 10

Fig.1

Fig.2

Fig.3

Tab.1

Tab.2

Fig.4

Tab.3

Tab.4

Fig.5

Fig.6

References 17

[1]	刘鹏. 岸边桥式起重机现场卸船和安装安全管理研究[J]. 中国设备工程, 2020(6):35-36.
[2]	SHIN I J. Factors that affect safety of tower crane installation/dismantling in construction industry[J]. Safety Science, 2015, 72:379-390. doi: 10.1016/j.ssci.2014.10.010
[3]	STARYKOV M, VAN HOORN F. The influence of a quay crane sea transportation on its further exploitation[J]. Transport, 2018, 33(2): 536-542. doi: 10.3846/16484142.2017.1297328
[4]	于文杰, 郭国平, 吴兵. 基于模糊故障树的长江LNG船舶装卸作业风险预测[J]. 交通信息与安全, 2019, 37(5):46-53.
	YU Wenjie, GUO Guoping, WU Bing. Risk prediction of LNG ships during loading /unloading in the Yangtze River based on fuzzy fault tree[J]. Journal of Transport Information and Safety, 2019, 37(5): 46-53.
[5]	王金辉, 郝伟, 陶泽, 等. 基于模糊贝叶斯网络的塔吊作业安全风险评估[J]. 安全与环境工程, 2021, 28(4):15-20.
	WANG Jinhui, HAO Wei, TAO Ze, et al. Safety risk assessment of tower crane operation based on fuzzy Bayesian network[J]. Safety and Environmental Engineering, 2021, 28(4):15-20.
[6]	黄启录. 起重机综合评价系统研究与实现[D]. 大连: 大连理工大学, 2012.
	HUANG Qilu. Research and implementation of comprehensive evaluation system of cranes[D]. Dalian: Dalian University of Technology, 2012.
[7]	胡静波, 庆光蔚, 王会方, 等. 基于模糊层次综合分析法的桥门式起重机分级评价[J]. 中国安全生产科学技术, 2014, 10(1):187-192.
	HU Jingbo, QING Guangwei, WANG Huifang, et al. Classification evaluation of bridge and gantry cranes based on fuzzy analytic hierarchy process[J]. Journal of Safety Science and Technology, 2014, 10(1): 187-192.
[8]	王卫辉, 孟小胴, 强宝民, 等. 桥式起重机安全评估指标体系研究和系统设计[J]. 中国安全生产科学技术, 2013, 9(9):155-159.
	WANG Weihui, MENG Xiaodong, QIANG Baomin, et al. Research on index system and software system design of bridge cranes safety evaluation on bridge crane[J]. Journal of Safety Science and Technology, 2013, 9(9):155-159.
[9]	舒文杰, 徐桂芳, 魏国前, 等. 桥式起重机金属结构检测及安全评估研究[J]. 制造业自动化, 2014, 36(15):55-60.
	SHU Wenjie, XU Guifang, WEI Guoqian, et al. Metal structure detection in bridge crane and research on safety assessment[J]. Manufacturing Automation, 2014, 36(15):55-60.
[10]	HU Shenping, ZHANG Jinpeng. Risk assessment of marine traffic safety at coastal water area[J]. Procedia Engineering, 2012, 45:31-37. doi: 10.1016/j.proeng.2012.08.116
[11]	TAM V W Y, FUNG I W H. Tower crane safety in the construction industry: a Hong Kong study[J]. Safety Science, 2011, 49(2): 208-215. doi: 10.1016/j.ssci.2010.08.001
[12]	李德毅, 刘常昱, 杜鹢, 等. 不确定性人工智能[J]. 软件学报, 2004, 15(11):1583-1594.
	LI Deyi, LIU Changyu, DU Yi, et al. Artificial intelligence with uncertainty[J]. Journal of Software, 2004, 15(11): 1583-1594.
[13]	纪柯柯, 陈坚, 吴改选, 等. 基于组合赋权-云模型的高速公路路网交通适应性评价[J]. 公路, 2021, 66(3):193-200.
	JI Keke, CHEN Jian, WU Gaixuan, et al. Traffic adaptability evaluation of expressway network based on combined weighting-cloud model[J]. Highway, 2021, 66(3):193-200.
[14]	钟鸣. 基于关联规则和云模型的水库诱发地震风险多层次模糊综合评价[D]. 武汉: 华中科技大学, 2013.
	ZHONG Ming. Multi-level fuzzy comprehensive evaluation of reservoir induced seismic risk based on association rules and cloud model[D]. Wuhan: Huazhong University of Science and Technology, 2013.
[15]	熊楚宸. 基于云模型改进的岸边集装箱起重机模糊综合评价[D]. 武汉: 武汉理工大学, 2020.
	XIONG Chuchen. Fuzzy comprehensive evaluation of shore container crane based on improved cloud model[D]. Wuhan: Wuhan University of Technology, 2020.
[16]	李莎莎, 崔铁军, 马云东. 基于云模型的变因素影响下系统可靠性模糊评价方法[J]. 中国安全科学学报, 2016, 26(2): 132-138.
	LI Shasha, CUI Tiejun, MA Yundong. Research on method for evaluating fuzzily system reliability of variable factors influenced system based on cloud model[J]. China Safety Science Journal, 2016, 26(2): 132-138.
[17]	交通运输部. 港口工程施工安全风险评估指南(沿海码头、护岸及防波堤分册)[Z]. 2017-11-01.

定义		改进标度	定义		改进标度
B_i比B_j 重要	极端重要	A₉(9,0.167,0.05)	B_j比B_i 重要	介于相邻等级间	A_1/2(1/2,0.167/4,0.05/4)
	介于相邻等级间	A₈(8,0.167,0.05)		稍微重要	A_1/3(1/3,0.167/9,0.05/9)
	强烈重要	A₇(7,0.167,0.05)		介于相邻等级间	A_1/4(1/4,0.167/16,0.05/16)
	介于相邻等级间	A₆(6,0.167,0.05)		明显重要	A_1/5(1/5,0.167/25,0.05/25)
	明显重要	A₅(5,0.167,0.05)		介于相邻等级间	A_1/6(1/6,0.167/36,0.05/36)
	介于相邻等级间	A₄(4,0.167,0.05)		强烈重要	A_1/7(1/7,0.167/49,0.05/49)
	稍微重要	A₃(3,0.167,0.05)		介于相邻等级间	A_1/8(1/8,0.167/64,0.05/64)
	介于相邻等级间	A₂(2,0.167,0.05)		极端重要	A_1/9(1/9,0.167/81,0.05/81)
同等重要		A₁(1,0,0)	—	—	—

风险等级	分值区间	接受准则	控制对策	云模型特征参数
等级Ⅳ(重大风险)	[60,100)	不可接受	暂停施工,必须采取措施将风险至少降低到不期望的程度,并加强监测和应急准备	C₄(80,16.99,0.1)
等级Ⅲ(较大风险)	[50,60)	不期望	必须采取措施降低风险,减少风险可能导致的损失	C₃(55,4.25,0.05)
等级Ⅱ(一般风险)	[40,50)	可接受	需采取风险防控措施,严格日常安全生产管理,加强现场巡视	C₂(45,4.25,0.04)
等级Ⅰ(较小风险)	(0,40)	忽略	不需采取特别的风险防控措施	C₁(20,16.99,0.01)

三级指标	权重云数字特征		风险因素的评价云数字特征
V₁₁	(0.064,0.068,0.068)		(29.6,4.111,3.407)
V₁₂	(0.101,0.112,0.112)		(41.6,5.114,3.906)
V₁₃	(0.16,0.179,0.179)		(35.4,4.412,3.489)
V₁₄	(0.381,0.336,0.336)		(16.6,5.114,3.906)
V₁₅	(0.252,0.267,0.267)		(19,2.507,1.511)
V₁₆	(0.042,0.037,0.037)		(47.2,2.607,2.576)
V₂₁	(0.204,0.087,0.203)		(55.6,1.604,1.065)
V₂₂	(0.221,0.676,0.249)		(58,2.106,2.045)
V₂₃	(0.363,0.146,0.339)		(48.2,1.805,1.139)
V₂₄	(0.103,0.0446,0.107)		(53.2,0.902,0.897)
V₂₅	(0.066,0.028,0.065)		(62,3.008,3.008)
三级指标	权重云数字特征	风险因素的评价云数字特征
V₂₆	(0.043,0.015,0.036)	(57.6,0.802,0.058)
V₃₁	(0.074,0.076,0.076)	(25.4,3.108,3.102)
V₃₂	(0.135,0.134,0.134)	(17,2.005,1.738)
V₃₃	(0.414,0.378,0.375)	(64.2,2.106,2.067)
V₃₄	(0.241,0.285,0.283)	(45.4,1.604,0.94)
V₃₅	(0.135,0.126,0.134)	(27.4,1.604,1.443)
V₄₁	(0.062,0.055,0.055)	(16.4,3.91,2.247)
V₄₂	(0.16,0.18,0.18)	(47.4,2.707,2.586)
V₄₃	(0.417,0.375,0.375)	(55.6,1.404,1.371)
V₄₄	(0.263,0.285,0.285)	(31.6,1.604,1.391)
V₄₅	(0.097,0.105,0.105)	(38.2,7.219,6.52)

二级指标	权重云数字特征	风险因素云数字特征
人员因素	(0.108,0.116,0.116)	(24.855,4.184,3.16)
设备因素	(0.566,0.494,0.494)	(53.705,1.8,1.402)
环境因素	(0.229,0.314,0.314)	(45.394,1.997,1.767)
管理因素	(0.098,0.076,0.076)	(43.802,2.411,2.153)