Safety evaluation model of electromechanical equipment in coal mines based on AHP-TOPSIS method and its application

doi:10.16265/j.cnki.issn1003-3033.2024.S1.0025

Abstract

Abstract:

There are many and complex factors influencing the safety status of electromechanical equipment in coal mines, and it is difficult to identify the potential safety hazards. To address these issues, a comprehensive safety evaluation model of electromechanical equipment in coal mines based on AHP-TOPSIS method was proposed. According to the cause theory of electromechanical equipment accidents in coal mines, 20 evaluation indexes were selected from four aspects of human factors, electromechanical equipment maintenance, management organization, and working environment, and the safety status evaluation index system of electromechanical equipment in coal mines was constructed. Then, the AHP method was used to calculate the weight of each index, and the TOPSIS method was used to calculate the relative nearness degree between the sample and the ideal solution. The index weight was coupled with the relative nearness degree, and the safety level of electromechanical equipment in coal mines was predicted. Finally, the model was applied to a mine of Shanxi Coal Group. The results show that the safety level of electromechanical equipment in the coal mines mine is Level Ⅱ. According to the prediction results, the potential safety hazards are identified by reverse order analysis, and the analysis results are in line with the actual situation.

Key words: analytic hierarchy process-technique for order preference by similarity to the ideal solution (AHP-TOPSIS) model, coal mine, electromechanical equipment, safety evaluation, nearness degree

CLC Number:

X936

ZHANG Yanghang. Safety evaluation model of electromechanical equipment in coal mines based on AHP-TOPSIS method and its application[J]. China Safety Science Journal, 2024, 34(S1): 179-184.

Figures/Tables 9

Table 1

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

Table 8

Table 9

References 11

[1]	牛国亮. 地方煤矿机电安全管理现状与对策[J]. 煤矿安全, 2011(4):190-192.
	NIU Guoliang. Current situation and countermeasures of mechanical and electrical safety management in local coal[J]. Safety in Coal Mines, 2011(4):190-192.
[2]	覃日强. 论煤矿机电技术管理在煤矿安全生产中的应用[J]. 煤炭技术, 2012(6):262-263.
	TAN Riqiang. Application of mechanical and electrical technology in coal mine production management[J]. Coal Technology, 2012(6):262-263.
[3]	祁云, 白晨浩, 代连朋, 等. 改进双向长短期记忆神经网络的瓦斯涌出量预测[J/OL]. 安全与环境学报,1-10[2024-06-08].https://doi.org/10.13637/j.issn.1009-6094.2024.0383.
	QI Yun, BAI Chenhao, DAI Lianpeng, et al. Enhanced bidirectional long short term memory neural network for gas emission forecasting[J]. Journal of safety and environment,1-10[2024-06-08].https://doi.org/10.13637/j.issn.1009-6094.2024.0383.
[4]	刘秀丽. 煤矿安全生产中煤矿机电技术管理的合理应用[J]. 西部探矿工程, 2020, 32(2):194-196.
	LIU Xiuli. Reasonable application of mechanical and electrical technology management in coal mine safety production[J]. West China Exploration Engineering, 2020, 32(2):194-196.
[5]	李明轩. 我国煤矿机电事故现状及应对措施[J]. 煤矿安全, 2019, 50(4):245-247.
	LI Mingxuan. Current situation and countermeasures of mechanical and electrical accidents in China's coal mines[J]. Safety in Coal Mines, 2019, 50(4):245-247.
[6]	成剑飞. 井下机电安全生产状况的模糊综合评价[J]. 煤炭与化工, 2017, 40(1):102-105.
	CHENG Jianfei. Fuzzy comprehensive evaluation on status of underground electromechanical safety production[J]. Coal and Chemical Industry, 2017, 40(1):102-105.
[7]	李新玉. 中平能化集团煤矿机电系统化安全评价体系[J]. 煤矿安全, 2011, 42(7):176-178.
	LI Xinyu. Safety evaluation system of coal mine electromechanical system of Zhongping energy and chemical group[J]. Safety in Coal Mines, 2011, 42(7):176-178.
[8]	QI Yun, XUE Kailong, WANG Wei, et al. Coal and gas protrusion risk evaluation based on cloud model and improved combination of assignment[J]. Scientific reports, 2024, 14(1):DOI:10.1038/S41598-024-55382-1.
[9]	王明重, 刘泽功, 张箫剑, 等. 基于AHP和扩展集对理论的采空区遗煤自燃危险性评价研究[J]. 中国安全生产科学技术, 2014, 10(8):183-188.
	WANG Mingchong, LIU Zegong, ZHANG Xiaojian, et al. Research of risk assessment on spontaneous combustion of goaf coal based on analytic hierarchy process and extended set pair theory[J]. China Safety Science Journal, 2014, 10(8):183-188.
[10]	王霞, 段庆全. 基于改进理想点解法的油气管道事故综合预测研究[J]. 中国安全生产科学技术, 2018, 14(4): 119-125.
	WANG Xia, DUAN Qingquan. Study on comprehensive prediction of oil and gas pipeline accidents based on improved TOPSIS[J]. Journal of Safety Science and Technology, 2018, 14(4):119-125.
[11]	QI Yun, WANG Wei, GE Juaqi, et al. Development characteristics of the rock fracture field in strata overlying a mined coal seam group[J]. PloS One,2022: DOI:10.1371/journal.pone.0268955.

目标	一级指标	二级指标
机电设备安全状态评价R	人的因素R₁	员工操作违规率R₁₁
		月均培训时间R₁₂
		员工平均工龄R₁₃
	机电检修R₂	机电设备质量R₂₁
		防护设备齐全度R₂₂
		维修质量R₂₃
		保养和检查频率R₂₄
		机电设备使用年限R₂₅
		安全检查全面性R₂₆
	管理组织R₃	安全章程健全度R₃₁
		管理机构合理性R₃₂
		安全管理时效性R₃₃
		应急机制完善率R₃₄
		安全管理有效率R₃₅
	工作环境R₄	地质构造复杂度R₄₁
		作业空间合理性R₄₂
		载荷能力适配性R₄₃
		粉尘浓度R₄₄
		温度R₄₅
		湿度R₄₆

指标	Ⅰ级	Ⅱ级	Ⅲ级	Ⅳ级	Ⅴ级	样本
R₁₁	<4	<8	<12	<16	≥16	3.5
R₁₂	>9	>7	>5	>3	≤3	7.8
R₁₃	>10	>6	>4	>2	≤2	5.5
R₂₁	>95	>90	>85	>80	≤80	94
R₂₂	>95	>90	>85	>80	≤80	92
R₂₃	>95	>90	>85	>80	≤80	86
R₂₄	>95	>90	>85	>80	≤80	86
R₂₅	>95	>90	>85	>80	≤80	78
R₂₆	>95	>90	>85	>80	≤80	91
R₃₁	>90	>80	>70	>60	≤60	85
R₃₂	>90	>80	>70	>60	≤60	75
R₃₃	>90	>80	>70	>60	≤60	83
R₃₄	>90	>80	>70	>60	≤60	88
R₃₅	>90	>80	>70	>60	≤60	93
R₄₁	>95	>90	>85	>80	≤80	83
R₄₂	>90	>80	>70	>60	≤60	88
R₄₃	>90	>80	>70	>60	≤60	88
R₄₄	<4	<6	<8	<10	≥10	5
R₄₅	<20	<24	<26	<28	≥28	23
R₄₆	<60	<70	<80	<90	≥90	69

R-R_i	R₁	R₂	R₃	R₄
R₁	1	2	3	2
R₂	1/2	1	3/2	1
R₃	1/3	2/3	1	2/3
R₄	1/2	1	3/2	1

R₁-R₁_i	R₁₁	R₁₂	R₁₃
R₁₁	1	2	3
R₁₂	1/2	1	3/2
R₁₃	1/3	2/3	1

R-R₂_i	R₂₁	R₂₂	R₂₃	R₂₄	R₂₅	R₂₆
R₂₁	1	4/3	1	1/3	1/2	1/4
R₂₂	3/4	1	3/4	1/4	3/8	3/16
R₂₃	1	3/4	1	1/3	1/2	1/4
R₂₄	3	3	4	1	3/2	3/4
R₂₅	2	8/3	2	2/3	1	1/2
R₂₆	4	16/3	4	4/5	2	1