针对智能采煤工作面系统开发人体可靠性分析模型

IF 10.2 2区 经济学 0 ENVIRONMENTAL STUDIES Resources Policy Pub Date : 2024-10-28 DOI:10.1016/j.resourpol.2024.105375
Yan Zhang , Ninghao Sun , Xiangyang Hu , Ruipeng Tong
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引用次数: 0

摘要

当前,安全生产形势依然严峻,用工荒问题日益突出,是影响煤炭工业安全生产和可持续发展的关键因素。要从根本上解决这些问题,建设智能化煤矿已成为必然趋势。在当前的建设背景下,智能化煤矿的运营更依赖于人与系统的交互,带来了新的人为错误风险。适用的人为可靠性分析(HRA)方法可以有效识别和评估风险,进一步提高智能煤矿的安全水平。然而,针对智能煤矿的人的可靠性分析研究尚处于初级阶段,缺乏适用的理论基础和方法体系。为弥补上述局限,以智能采煤工作面(ICMF)系统为研究对象,首先结合系统结构和任务特点,构建了适合 ICMF 操作的认知模型,为启动智能煤矿人的安全研究奠定了认知理论基础。在此基础上,提出了 ICMF-HRA 变量,包括一般人为失效事件(HFE)、七种主要乘员功能(MCF)、十八种乘员活动基元(CAP)、二十五种乘员失效模式(CFM)、二十九种性能影响因素(PIF),以及三种定性依赖结构(即:HFE-MCF-CAP-CIF-PIF)、利用模糊贝叶斯网络建立了三种定性依赖结构(即 HFE-MCF-CAP-CFM、CFM-PIF 和 PIF-PIF)以及它们之间的六种定量概率关系,从而构成了 ICMF-HRA 模型。此外,结合通信中断事件阐述了该模型的应用,证实了该模型的可用性和适应性。ICMF-HRA 模型填补了智能煤矿 HRA 研究的空白,可用于预测和回顾分析,为风险防范和处置提供决策支持。本研究有望为提高智能煤矿的人的安全水平奠定理论基础,提供实用工具,进一步促进煤炭工业的安全与可持续发展。
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Developing the human reliability analysis model tailored for intelligent coal mining face system
The still severe situation of work safety and the increasingly prominent issue of labor shortage are currently the key factors affecting the safety and sustainable development of coal industry. To fundamentally solve these problems, the construction of intelligent coal mines has become an inevitable trend. In the current construction context, intelligent coal mining operations rely more on human-system interaction, bringing new human error risks. The applicable human reliability analysis (HRA) method can effectively identify and evaluate the risks, and further improve the safety level of intelligent coal mines. However, research on HRA for intelligent coal mines is still in early stages, lacking applicable theoretical basis and methodological system. To make up for the limitations, focusing on the research object of intelligent coal mining face (ICMF) system, firstly, a cognitive model suitable for ICMF operations was constructed combining with the system structure and task characteristics, laying a cognitive theoretical foundation for initiating research on human safety of intelligent coal mines. Based on this, the ICMF-HRA variables including general human failure event (HFE), seven main crew functions (MCFs), eighteen crew activity primitives (CAPs), twenty-five crew failure modes (CFMs), and twenty-nine performance influencing factors (PIFs), and three qualitative dependency structures (i.e., HFE-MCF-CAP-CFM, CFM-PIF, and PIF-PIF) and six quantitative probability relationships between them are developed using fuzzy Bayesian network, which constitutes the ICMF-HRA model. Moreover, the application of this model is elaborated combining communication interruption event, confirming the availability and adaptability of this model. The ICMF-HRA model fills the HRA research gap of intelligent coal mines and can be used for predictive and retrospective analysis, providing decision support for risk prevention and disposal. This study is expected to establish theoretical basis and provide practical tool for improving human safety level of intelligent coal mines, further promoting the safety and sustainable development of coal industry.
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来源期刊
Resources Policy
Resources Policy ENVIRONMENTAL STUDIES-
CiteScore
13.40
自引率
23.50%
发文量
602
审稿时长
69 days
期刊介绍: Resources Policy is an international journal focused on the economics and policy aspects of mineral and fossil fuel extraction, production, and utilization. It targets individuals in academia, government, and industry. The journal seeks original research submissions analyzing public policy, economics, social science, geography, and finance in the fields of mining, non-fuel minerals, energy minerals, fossil fuels, and metals. Mineral economics topics covered include mineral market analysis, price analysis, project evaluation, mining and sustainable development, mineral resource rents, resource curse, mineral wealth and corruption, mineral taxation and regulation, strategic minerals and their supply, and the impact of mineral development on local communities and indigenous populations. The journal specifically excludes papers with agriculture, forestry, or fisheries as their primary focus.
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