煤矿灾害监测系统数据可靠性评价

doi:10.16265/j.cnki.issn1003-3033.2026.05.1025

摘要/Abstract

摘要：

数据可靠性对精准判识煤矿灾害风险至关重要,为准确评价煤矿灾害监测预警系统的数据可靠性,通过梳理“一规程四细则”等相关政策法规、标准规范和文献资料,融合大数据和地理信息系统(GIS)空间分析技术,提出一套煤矿灾害监测系统可靠性评价方法,并在山西某煤矿开展灾害防治现场实践验证。结果表明:从灾害监测系统多源信息中提取不精确性、异类性与冲突性特征,是精准识别超限、失效、信息缺失、位置错误、频率异常等多类不可靠信息的核心关键。构建涵盖合法性、合规性、合理性3大类437小类的煤矿灾害监测系统可靠性评价指标体系,最大程度上还原煤矿灾害监测系统全寿命周期内的多源关联信息;试验矿井2025年2月正常生产期间,该方法共识别出不可靠信息56 753条,经人工核实评价准确率为100%。文中方法可在灾害预警数据预处理阶段,动态评价煤矿现有的多类型监测系统是否满足灾害预警的要求,及时提醒开展监测系统维护与升级工作。

关键词: 煤矿灾害, 监测系统, 数据可靠性, 可靠性评价, 地理信息系统(GIS), 空间分析

Abstract:

Data reliability is essential for accurate identification of coal mine disaster risks. To accurately evaluate the data reliability of coal mine disaster monitoring and early warning systems, relevant policies, regulations, standards and literatures including the One Regulation and Four Detailed Rules were systematically reviewed, and a reliability evaluation method for coal mine disaster monitoring systems was proposed by integrating big data and GIS spatial analysis technology. The method was verified via field practice in disaster prevention and control at a coal mine in Shanxi Province. Results indicate that extracting the characteristics of imprecision, heterogeneity and conflict from multi-source monitoring information is the core to accurately identify unreliable data, including over-limit values, equipment failures, missing information, positional errors and abnormal frequencies. A reliability evaluation index system covering 3 primary categories (legitimacy, compliance and rationality) and 437 subcategories is constructed, which can fully restore multi-source associated information of the monitoring system throughout its full life cycle. During normal production in February 2025 at the test mine, 56 753 pieces of unreliable information were identified by this method, with a 100% accuracy rate verified by manual inspection. Furthermore, this method can dynamically assess whether existing mine monitoring systems meet disaster early warning requirements during the data preprocessing stage, and timely prompt mine maintenance and system upgrading.

Key words: coal mine disaster, monitoring system, data reliability, reliability evaluation, geographic information system (GIS), spatial analysis

中图分类号:

X936

秦凯, 邓志刚, 舒龙勇, 魏帅豪. 煤矿灾害监测系统数据可靠性评价[J]. 中国安全科学学报, 2026, 36(5): 190-198.

Qin Kai, Deng Zhigang, Shu Longyong, Wei Shuaihao. Data reliability evaluation for coal mine disaster monitoring system[J]. China Safety Science Journal, 2026, 36(5): 190-198.

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一级指标	二级指标	三级指标	指标解释	指标分级
一级指标	二级指标	三级指标	指标解释	完全满足	基本满足	部分满足	不满足
合法性	系统建设	系统配置要求	建设了要求的各类系统	是	—	—	否
	系统建设	数据采集要求	采集数据满足要求	是	—	—	否
	必备测点	传感器布置	传感器布置满足要求	是	—	—	否
	必备测点	特殊位置测点	井下特殊位置测点满足要求	是	—	—	否
合规性	数据采集频率	实时数据上传频率	按规定频率上传	是	非必备点缺失	必备点缺失	否
		基础信息上传频率	按规定频率上传	是	—	—	否
		基础信息上传频率	基础信息变化后及时上传	是	—	—	否
		异常信息上传频率	按规定频率上传异常信息	是	—	—	否
	数据项完整性	数据格式规范	上传数据应满足规范要求	满足	—	—	不满足
	数据项完整性	实时、基础、异常数据完整性	实时数据、基础、异常信息各项完整	完整	非必选项缺失	必选项缺失	无法解析
	测点合理性	测点布置要求	测点布置合规性比例/%	≥95	≥85	≥70	<70
	测点合理性	传感器标校要求	满足不同传感器的标校要求	满足	—	—	不满足
合理性	数据合理性	超量程数据	上传数据是否在量程之内	是	—	—	否
		零值数据	上传数据在出现异常0值	否	—	—	是
		采集数据失真	是否存在数据失真	否	—	—	是
	时间合理性	数据时效性	监测数据滞后时间t_m/min	≤10	(10,30]	(30,60]	>60
			基础信息滞后时间t_o/min	≤30	(10,50]	(50,60]	>60
			异常信息滞后时间t_u/min	≤10	(10,30]	(30,60]	>60
			上传时间大于当前时间	否	—	—	是
	位置合理性	测点位置失效	位置合理测点比/%	>90	>80	>70	≤70
	位置合理性	测点布设合理性	系统测点布置是否可优化	否	是	—	—
总计			437类

灾害类型	三级指标规则数	总数	完全满足(A)	基本满足(B)	部分满足(C)	不满足(D级)
瓦斯	354	256 253	133 251	46 125	38 437	38 440
顶板	311	96 870	48 476	19 855	12 389	16 150
水害	363	10 367	5 032	1 960	1 212	2 163
总计	1 028	363 490	186 759	67 880	52 038	56 753