摘要
煤矿作业场所涉及的职业危害因素众多,为解决煤矿作业场所职业危害综合评估过程中指标因素存在模糊性与不确定性问题,引入云模型理论并结合组合赋权技术构建煤矿作业场所职业危害评估模型。以某煤矿所辖的综采工作面为研究背景,选取作业人员状况、尘毒物质、物理因素、设备因素、管理因素等五个方面共20个影响因素作为评价指标,利用正向云发生器计算隶属于不同等级的确定度,基于欧式距离组合运用AHP和EWM计算各指标的组合权重以降低决策者的主观影响,依据评估指标云模型特征参数确定该煤矿作业场所职业危害等级。研究结果表明,该煤矿作业场所综合评估等级为C4级,与实际评估情况基本相符,具有一定的可靠性与可操作性,为煤矿作业场所的职业危害评估提供了新的借鉴与思路。
In order to solve the problem of ambiguity and uncertainty of index factors in the integrated assessment of occupational hazards in coal mine workplaces, the cloud model theory is introduced and combined with the combination of assignment techniques to build an occupational hazard assessment model for coal mine workplaces. Using a coal mine’s general mining face as the research background, a total of 20 influencing factors in five aspects, such as operator condition, dust and toxic substances, physical factors, equipment factors, and management factors, were selected as evaluation indicators, and the determinacy of belonging to different levels was calculated using a forward cloud generator, and the combination weights of each indicator were calculated based on Euclidean distance combination using AHP and EWM to reduce the subjective influence of decision makers, and the occupational hazard level of the coal mine workplace was determined based on the characteristic parameters of the evaluation indicator cloud model.The results of the study show that the comprehensive assessment grade of the coal mine workplace is C4,which is basically consistent with the actual assessment situation and has certain reliability and operability, and provides new reference and ideas for the assessment of occupational hazards in coal mine workplaces.
作者
屈扬
张学博
QU Yang;ZHANG Xue-bo(Henan College of Industry and Information Technology,Jiaozuo 454000,China;College of Safety Science and Engineering,Henan Polytechnik University,Jiaozuo 454003,China)
出处
《煤炭工程》
北大核心
2021年第10期153-159,共7页
Coal Engineering
基金
国家自然科学基金项目(51704099)。
关键词
煤矿
作业场所
组合赋权
云模型
职业危害评估
coal mine
workplace
portfolio empowerment
cloud model
occupational hazard assessment
