矿区架空线路外破风险评估方法

刘振国; 于海; 封士光; 张禹

doi:10.13272/j.issn.1671-251x.2023070004

矿区架空线路外破风险评估方法

doi: 10.13272/j.issn.1671-251x.2023070004

1.
国网新疆电力有限公司电力科学研究院，新疆乌鲁木齐　830011
2.
中国矿业大学电气工程学院，江苏徐州　221116

基金项目: 中央高校基本科研业务费资助项目（2021QN1067）。

详细信息

作者简介:
刘振国（1988—），男，河南濮阳人，工程师，硕士，现从事输变电设备安全性评价方面的工作，E-mail：liuzhenguo227@163.com

中图分类号: TD61
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- 被引次数: 0
出版历程
- 收稿日期: 2023-07-03
- 修回日期: 2023-10-20
- 网络出版日期: 2023-10-24

Risk assessment method for external breakage of overhead lines in mining areas

1.
Electric Power Research Institute of State Grid Xinjiang Electric Power Co., Ltd., Urumqi 830011, China
2.
School of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China

摘要

摘要: 矿区架空线路运行环境恶劣，易受到外界因素影响而导致线路损坏，需要准确评估矿区架空线路外破风险水平。然而现有的定性评估方法存在主观性强、评价结果可比性差等缺点，定量评估方法虽然有着较高的客观性，但其准确评估的基础是大量高质量数据。为均衡评估结果的客观性和评估数据的获取难度，采用半定量评估方法中的作业条件危险性分析（LEC）法，并基于矿区线路实际运行环境对其进行改进，提出了一种基于改进LEC法的矿区架空线路外破风险评估方法。首先，通过分析矿区架空线路的实际运行环境，明确主要的外破风险要素，构建矿区架空线路外破风险评估指标体系。其次，借助基于YOLOv5的图像识别策略来辨识线路环境中的外破风险源，实现线路外破风险数据的实时获取，克服了传统LEC法人工获取的数据实时性较差、数据量不足的缺点。然后，改进了LEC法的要素赋值规则，基于图像辨识结果对要素进行赋值，实现线路外破风险的实时评估，提高了评估结果的客观性，解决了传统LEC法的要素赋值依赖评价者个人经验的弊病。最后，为衡量各类风险带来的叠加影响，利用层次分析法确定各风险评价指标权重，最终实现矿区架空线路外破风险的综合评估。结合露天煤矿实际运行过程中某场景进行案例分析，结果表明该方法能对具体场景中的架空线路外破风险等级进行有效评估。
- 矿区线路 /
- 外破风险 /
- YOLOv5 /
- 改进LEC法 /
- 评价指标体系
Abstract: The operating environment of overhead lines in mining areas is harsh. The lines are easily affected by external factors, leading to line breakage. It is necessary to accurately evaluate the risk level of external breakage of overhead lines in mining areas. However, existing qualitative evaluation methods have shortcomings such as strong subjectivity and poor comparability of evaluation results. Although quantitative evaluation methods have high objectivity, the accurate evaluation is based on a large amount of high-quality data. In order to balance the objectivity of the evaluation results and the difficulty of obtaining evaluation data, the likelihood exposure consequence (LEC) method in semi quantitative evaluation method is adopted. Based on the actual operating environment of mining area lines, an improved LEC method is proposed for the risk assessment of external breakage of overhead lines in mining areas. Firstly, by analyzing the actual operating environment of overhead lines in mining areas, the main risk factors of external breakage are identified. The risk assessment index system for external breakage of overhead lines in mining areas is constructed. Secondly, using the YOLOv5 based image recognition strategy to identify the sources of external breakage risk in the line environment, real-time acquisition of external breakage risk data of the line is achieved. It overcomes the shortcomings of poor real-time performance and insufficient data volume obtained manually by traditional LEC methods. Thirdly, the element assignment rules of the LEC method are improved. The elements are assigned based on image recognition results to achieve real-time evaluation of the risk of external breakage to the line. It improves the objectivity of the evaluation results and solves the problem of the traditional LEC method's element assignment relying on the personal experience of the evaluator. Finally, in order to measure the superimposed impact of various risks, the analytic hierarchy process is used to determine the weight of each risk evaluation index. Ultimately, the comprehensive assessment of the risk of external breakage to overhead lines in mining areas is achieved. A case study is conducted during the actual operation of an open-pit coal mine. The results show that this method can effectively evaluate the risk level of external breakage of overhead lines in specific scenarios.
- mining area route /
- external breakage risk /
- YOLOv5 /
- improved LEC method /
- evaluation index system

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图 1 矿区架空线路外破风险评估指标体系

Figure 1. Risk assessment index system for external breakage of overhead lines in mining area

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图 2 矿区架空线路外破风险评估层次结构模型

Figure 2. Hierarchical structure model of risk assessment for external breakage of overhead lines in mining area

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图 3 待评估场景

Figure 3. Scenario to be assessed

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图 4 不同时刻待评估场景

Figure 4. Scenario to be assessed at different moments

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表 1 风险源存在分值L赋值

Table 1. Assignment of risk source presence score L

目标可信度	L	描述
（0.9，1]	8	风险源一定存在
（0.8，0.9]	7	风险源极有可能存在
（0.7，0.8]	6	风险源较大可能存在
（0.6，0.7]	5	风险源可能存在
（0.5，0.6]	3	风险源不一定存在

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表 2 风险源频繁度分值E赋值

Table 2. Assignment of risk source frequency score E

风险源持续时长/min	E	描述
（40，60]	8	风险源长期存在
（30，40]	7	风险源存在较长时间
（20，30]	6	风险源存在一段时间
[10，20]	5	风险源短时出现
＜10	3	风险源偶然出现

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表 3 风险要素及其对应编号

Table 3. Risk elements and their corresponding numbers

风险要素	指标	编号
车辆类型	吊斗铲	A1
	卡车	A2
	推土机	A3
	挖掘机	A4
风险源在预警区间内	是	X1
风险源在预警区间内	否	X2
风险源持续向预警区间移动	是	Y1
风险源持续向预警区间移动	否	Y2

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表 4 不同气象因素的风险调节系数取值

Table 4. The values of risk adjustment coefficient for different meteorological factors

风险调节系数	影响因素	分级标准	风险调节系数取值
K_t	气温t/（°C）	t≤5	0
		5＜t≤15	0.02
		15＜t≤25	0.05
		t＞25	0.07
K_h	相对湿度h/（%）	h≥70	0
		50≤h＜70	0.02
		30≤h＜50	0.05
		h＜30	0.07
K_w	风速w/（m·s⁻¹）	0＜w≤3.3	0
		3.3＜w≤10.7	0.03
		10.7＜w≤17.1	0.05
		w＞17.1	0.10

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表 5 事故倾向度分值C赋值

Table 5. Assignment of accident propensity score C

外破风险源	评估场景	C
车辆（A）	A1，X1，Y1	7.3
	A1，X1，Y2	6.8
	A1，X2，Y1	5.4
	A1，X2，Y2	4.5
	A2，X1，Y1	4.4
	A2，X1，Y2	3.4
	A2，X2，Y1	2.8
	A2，X2，Y2	1.8
	A3，X1，Y1	4.5
	A3，X1，Y2	3.5
	A3，X2，Y1	3.6
	A3，X2，Y2	2.3
	A4，X1，Y1	6.8
	A4，X1，Y2	6.3
	A4，X2，Y1	4.7
	A4，X2，Y2	3.8
漂浮异物（B）	B，X1，Y1	7.2
	B，X1，Y2	6.7
	B，X2，Y1	5.8
	B，X2，Y2	4.3
火焰及烟雾（G）	G	9.5
人员活动（D）	D，X1，Y1	5.9
	D，X1，Y2	5.3
	D，X2，Y1	4.3
	D，X2，Y2	3.3

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表 6 不同风险值对应的事故风险等级及风险得分

Table 6. Accident risk level and risk score corresponding to different risk values

风险值R	事故风险等级	描述	基础风险得分
＞240	Ⅳ	极有可能导致事故发生	10
（180，240]	Ⅲ	导致事故发生的可能性较大	8
（80，180]	Ⅱ	导致事故发生的可能性不大	4
≤80	Ⅰ	不太可能导致事故发生	2

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表 7 判断矩阵标度含义

Table 7. Meaning of judgment matrix scale

标度数值	含义
1	指标i与j重要性相同
3	指标i比j稍微重要
5	指标i比j明显重要
7	指标i比j重要得多
9	指标i比j极端重要
2，4，6，8	上述相邻判断的中间程度

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表 8 平均随机一致性指标取值

Table 8. The value of average random consistency index

m	2	3	4	5	6	7
r_I	0	0.58	0.90	1.12	1.24	1.32

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表 9 不同外破风险源对应权重

Table 9. The weights corresponding to different external breakage risk sources

标签	风险源	原始权重	转换后权重
A	车辆	0.260 2	6
B	漂浮异物	0.127 3	3
G	火焰及烟雾	0.565 6	12
D	人员活动	0.046 9	1

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表 10 不同风险源单项风险加权得分

Table 10. Individual weighted scores of different risk sources

风险源	单项风险加权得分
风险源	风险等级Ⅰ	风险等级Ⅱ	风险等级Ⅲ	风险等级Ⅳ
车辆	12	24	48	60
漂浮异物	6	12	24	30
火焰及烟雾	24	48	96	120
人员活动	2	4	8	10

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表 11 线路外破风险等级评估标准

Table 11. Risk level assessment criteria for external breakage of lines

风险等级	评价指标	处置措施
正常（Ⅰ）	$p'_\max $＜10 R_t＜24	正常运行，无需特殊处理
低风险（Ⅱ）	10≤$p'_\max $＜24 24≤R_t＜36	定期巡检，加强管理
中风险（Ⅲ）	24≤$p'_\max $＜60 36≤R_t＜72	及时消除隐患，重点监视
高风险（Ⅳ）	$p'_\max $≥60 R_t≥72	立刻排查并处理风险因素

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表 12 待评估场景中各风险源分值

Table 12. Score of each risk source in the scenario to be assessed

风险源编号	L	E	C	K	R
1	7	5	2.3	—	80.50
2	6	8	2.3	—	110.40
3	5	8	6.3	—	252.00
4	5	5	9.5	1.1	261.25

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参考文献(21)

[1]	赵明辉. 煤矿供电系统安全评价研究及应用[D]. 西安:西安科技大学,2019. ZHAO Minghui. Safety evaluation and application of coal mine power supply system[D]. Xi'an:Xi'an University of Science and Technology,2019.
[2]	吴昊. 输电系统运行风险评估方法[J]. 电力系统及其自动化学报,2017,29(12):139-145. doi: 10.3969/j.issn.1003-8930.2017.12.022 WU Hao. Operation risk assessment method for transmission system[J]. Proceedings of the CSU-EPSA,2017,29(12):139-145. doi: 10.3969/j.issn.1003-8930.2017.12.022
[3]	李轶. 基于多源数据融合的电网巡检安全评价方法研究[D]. 宜昌:三峡大学,2019. LI Yi. Research on safety evaluation method of power grid inspection based on multivariate data fusion[D]. Yichang:China Three Gorges University,2019.
[4]	黄新波,吴明松,朱永灿,等. 基于模糊数学的电缆线路风险评估模型研究[J]. 高压电器,2021,57(9):19-25. doi: 10.13296/j.1001-1609.hva.2021.09.003 HUANG Xinbo,WU Mingsong,ZHU Yongcan,et al. Research on risk assessment model of cable line based on fuzzy mathematics[J]. High Voltage Apparatus,2021,57(9):19-25. doi: 10.13296/j.1001-1609.hva.2021.09.003
[5]	胡志鹏,刘剑,张玻,等. 基于风险关键特征量的输电线路运行环境风险评估[J]. 电力系统自动化,2017,41(18):160-166. doi: 10.7500/AEPS20161213002 HU Zhipeng,LIU Jian,ZHANG Bo,et al. Risk assessment of operation environment for transmission lines based on risk key characteristic[J]. Automation of Electric Power Systems,2017,41(18):160-166. doi: 10.7500/AEPS20161213002
[6]	颜祖明. 基于数据驱动的输电线路状态评估方法及运维策略研究[D]. 广州:广东工业大学,2022. YAN Zuming. Research on state assessment method and operation and maintenance strategy of transmission lines based on data-driven[D]. Guangzhou:Guangdong University of Technology,2022.
[7]	刘小杰,付建国,苏敬厚,等. 基于安全评价的黑岱沟矿运输系统管控措施制定[J]. 煤矿安全,2015,46(增刊1):71-75. doi: 10.13347/j.cnki.mkaq.2015.S1.018 LIU Xiaojie,FU Jianguo,SU Jinghou,et al. Decision of Heidaigou Mine transport system control based on safety assessment[J]. Safety in Coal Mines,2015,46(S1):71-75. doi: 10.13347/j.cnki.mkaq.2015.S1.018
[8]	王长申,孙亚军,杭远. 安全检查表法评价中小煤矿潜在突水危险性[J]. 采矿与安全工程学报,2009,26(3):297-303. doi: 10.3969/j.issn.1673-3363.2009.03.009 WANG Changshen,SUN Yajun,HANG Yuan. Using safety checklist in assessment of potential risk of water inrush from medium and small mines[J]. Journal of Mining & Safety Engineering,2009,26(3):297-303. doi: 10.3969/j.issn.1673-3363.2009.03.009
[9]	陈友鹏,陈璟华,何东升,等. 基于蒙特卡洛模拟和综合评判法的配电变压器抗短路能力评估[J]. 广东电力,2022,35(1):60-69. doi: 10.3969/j.issn.1007-290X.2022.001.007 CHEN Youpeng,CHEN Jinghua,HE Dongsheng,et al. Evaluation of short-circuit resistance ability of distribution transformer based on Monte Carlo simulation and comprehensive evaluation method[J]. Guangdong Electric Power,2022,35(1):60-69. doi: 10.3969/j.issn.1007-290X.2022.001.007
[10]	康新兴. 基于蒙特卡罗仿真的电力变压器故障树分析[J]. 国外电子测量技术,2018,37(10):5-9. doi: 10.19652/j.cnki.femt.1800994 KANG Xinxing. Fault tree analysis of power transformer based on Monte Carlo simulation[J]. Foreign Electronic Measurement Technology,2018,37(10):5-9. doi: 10.19652/j.cnki.femt.1800994
[11]	曾芬钰,郝世旺. 电力变压器设备风险评估研究综述[J]. 电工电气,2023(2):9-14,66. doi: 10.3969/j.issn.1007-3175.2023.02.002 ZENG Fenyu,HAO Shiwang. Research review on the risk assessment of power transformer equipments[J]. Electrotechnics Electric,2023(2):9-14,66. doi: 10.3969/j.issn.1007-3175.2023.02.002
[12]	云玉新,赵富强,张磊,等. 结合相关系数及改进层次分析法的油浸式变压器质量评估[J]. 重庆理工大学学报(自然科学),2022,36(5):203-210. YUN Yuxin,ZHAO Fuqiang,ZHANG Lei,et al. Quality evaluation of oil-immersed transformer based on correlation coefficient and improved analytic hierarchy process[J]. Journal of Chongqing University of Technology (Natural Science),2022,36(5):203-210.
[13]	沙池橙,林祖荣,钱振东,等. 基于灰色关联分析的定向权重式架空输电线路状态模糊评价方法[J/OL]. 武汉大学学报(工学版):1-11[2023-05-12]. http://kns.cnki.net/kcms/detail/42.1675.T.20220426.1115.002.html. SHA Chicheng,LIN Zurong,QIAN Zhendong,et al. Fuzzy evaluation method of directional weight overhead transmission line state based on grey correlation analysis[J/OL]. Engineering Journal of Wuhan University:1-11[2023-05-12]. http://kns.cnki.net/kcms/detail/42.1675.T.20220426.1115.002.html.
[14]	方权,刘闯,宋敏,等. 模糊评价与PSO优化的LSSVM架空输电线路故障率预测[J]. 水电能源科学,2021,39(1):171-175. FANG Quan,LIU Chuang,SONG Min,et al. Failure rate prediction of overhead transmission line based on fuzzy evaluation and PSO-optimized LSSVM[J]. Water Resources and Power,2021,39(1):171-175.
[15]	刘君,赵立进,黄良,等. 基于TOPSIS和灰色关联分析的变压器状态评价方法[J]. 电力科学与技术学报,2019,34(4):63-68. doi: 10.3969/j.issn.1673-9140.2019.04.009 LIU Jun,ZHAO Lijin,HUANG Liang,et al. State evaluation method for power transformer based on the TOPSIS and grey relational analysis[J]. Journal of Electric Power Science and Technology,2019,34(4):63-68. doi: 10.3969/j.issn.1673-9140.2019.04.009
[16]	王书明. 某垃圾焚烧发电项目电气系统安全性评价[J]. 电力系统保护与控制,2017,45(24):163-168. doi: 10.7667/PSPC201780 WANG Shuming. Safety evaluation of electrical system for a waste incineration power generation project[J]. Power System Protection and Control,2017,45(24):163-168. doi: 10.7667/PSPC201780
[17]	王君莉. 煤矿电气火灾风险的PHA−LEC评估模型及其应用[J]. 煤矿机械,2017,38(12):138-140. doi: 10.13436/j.mkjx.201712049 WANG Junli. Risk assessment model for coal mine electrical fire based on PHA-LEC and application[J]. Coal Mine Machinery,2017,38(12):138-140. doi: 10.13436/j.mkjx.201712049
[18]	毛吉星. 煤矿风险管理技术与应用研究[J]. 煤矿安全,2016,47(11):230-233. doi: 10.13347/j.cnki.mkaq.2016.11.064 MAO Jixing. Research on coal mine risk management technology and its application[J]. Safety in Coal Mines,2016,47(11):230-233. doi: 10.13347/j.cnki.mkaq.2016.11.064
[19]	黄悦华,陈照源,陈庆,等. 基于边缘计算和改进YOLOv5s算法的输电线路故障实时检测方法[J]. 电力建设,2023,44(1):91-99. doi: 10.12204/j.issn.1000-7229.2023.01.011 HUANG Yuehua,CHEN Zhaoyuan,CHEN Qing,et al. Real-time detection method for transmission line faults applying edge computing and improved YOLOv5s algorithm[J]. Electric Power Construction,2023,44(1):91-99. doi: 10.12204/j.issn.1000-7229.2023.01.011
[20]	龙乐云,周腊吾,刘淑琴,等. 改进YOLOv5算法下的输电线路外破隐患目标检测研究[J]. 电子测量与仪器学报,2022,36(11):245-253. doi: 10.13382/j.jemi.B2205638 LONG Leyun,ZHOU Lawu,LIU Shuqin,et al. Identification of hidden damage targets by external forces based on domain adaptation and attention mechanism[J]. Journal of Electronic Measurement and Instrumentation,2022,36(11):245-253. doi: 10.13382/j.jemi.B2205638
[21]	张可颖,吴新桥,赵继光,等. 基于特征工程和集成学习与模型融合的输电走廊实时山火风险评估模型[J/OL]. 电网技术:1-13 [2023-05-12]. https://doi.org/10.13335/j.1000-3673.pst.2022.2235. ZHANG Keying,WU Xinqiao,ZHAO Jiguang,et al. A real-time wildfire risk assessment model for transmission corridors based on feature engineering,ensemble learning and model fusion[J/OL]. Power System Technology:1-13 [2023-05-12]. https://doi.org/10.13335/j.1000-3673.pst.2022.2235.