当今智能矿山技术较不完善，实现煤矿井下无人开采的应用较为困难，煤矿井下仍需大量工人进行生产作业，导致煤矿事故中人因事故的比例一直居高不下。多年以来，疲劳作为人为因素中的一个潜在的原因一直被忽视，直到近几年，一些事故数据和相关研究的涌现，疲劳问题才开始受到应有的关注。但目前国内外对于疲劳的研究大多集中在交通领域，研究对象主要是空管等人员，而在其他领域的研究相对缺乏。因此，本文在全面分析矿工疲劳影响因素的基础上，建立相应的指标体系和评价模型开展矿工疲劳的风险评价研究。

本文首先进行矿工疲劳影响因素的识别，在国内外关于疲劳影响因素分析的基础上，根据人因SHEL模型的结构与原理，从矿工个人、个人与其他人员、环境、硬件、软件层面识别影响矿工疲劳的因素，采用DEMATEL-ISM法确定矿工疲劳影响因素的影响程度及其层次结构。其次进行矿工疲劳风险评价指标体系的构建，根据矿工疲劳影响程度分析、层次结构分析以及相关文献分析的结果初步选取矿工疲劳风险评价指标，运用专家调查法对指标进行二次筛选，最终建立由4个方面25项指标构成的矿工疲劳风险评价指标体系。最后进行矿工疲劳风险评价模型的构建，通过ANP法确定各个风险指标的权重，采用云模型评价法进行量化评价，构建基于ANP-云模型的矿工疲劳风险评价模型，应用该模型对陕西某煤矿矿工疲劳的风险进行评价。

由ANP法计算得到4个一级指标的权重按照大小依次为管理因素（0.4257）、环境因素（0.2230）、设备因素（0.1780）、个人因素（0.1733）。将ANP计算结果与云模型相结合进行评价，通过观察云图、计算云相似度和隶属度，最终确定4个一级指标的风险等级为：个人因素、管理因素为“中等风险”；设备因素、环境因素为“较低风险”，陕西某煤矿矿工疲劳总体风险等级为“中等风险”，针对风险等级较高的个人因素以及管理因素提出相应的风险缓解措施。

本文形成一套适用于矿工疲劳风险评价研究的方法体系，通过案例验证，证明了本文所构建的ANP-云模型在疲劳风险评价中的有效性和可行性，能够为类似项目的风险管理、科学运营提供思考。

Nowadays, the intelligent mining technology is not perfect, and it is difficult to realize the application of unmanned mining in the coal mine, and a large number of workers are still needed to carry out production operations in the coal mine, resulting in the proportion of human accidents in the coal mine has been high. For many years, fatigue as a potential cause of human factors has been ignored, and it is only in recent years, with the emergence of accident data and related studies, that fatigue has begun to receive the attention it deserves. However, at present, most of the research on fatigue at home and abroad focuses on the field of transportation, and the research objects are mainly air traffic control personnel, while the research in other fields is relatively lacking. Therefore, based on the comprehensive analysis of the influencing factors of miners' fatigue, this thesis establishes the corresponding index system and evaluation model to carry out the risk assessment research of miners' fatigue.

This thesis first identifies the influencing factors of miners' fatigue. Based on the analysis of the influencing factors of fatigue at home and abroad, and according to the structure and principle of human factor SHEL model, the influencing factors of miners' fatigue are identified from the aspects of individual miners, individuals and other personnel, environment, hardware and software. DEMATEL-ISM method was used to determine the influence degree and hierarchy of the influencing factors of miners' fatigue. Secondly, the construction of miners' fatigue risk evaluation index system is carried out. According to the results of miners' fatigue impact degree analysis, hierarchical structure analysis and relevant literature analysis, the miners' fatigue risk evaluation index is initially selected, and the index is secondary screened by the expert investigation method. Finally, the miners' fatigue risk evaluation index system composed of 25 indicators from 4 aspects is established. Finally, the fatigue risk evaluation model of miners was constructed, the weight of each risk index was determined by ANP method, the cloud model evaluation method was used for quantitative evaluation, and the fatigue risk evaluation model of miners based on ANP-cloud model was constructed, and the fatigue risk of miners in a coal mine in Shaanxi province was evaluated by this model.

According to the ANP method, the weights of the four first-level indicators are management factor (0.4257), environmental factor (0.2230), equipment factor (0.1780) and personal factor (0.1733). The ANP calculation results were combined with the cloud model for evaluation. By observing the cloud map and calculating the cloud similarity and membership degree, the risk levels of the four first-level indicators were determined as follows: personal factor and management factor were "medium risk"; Equipment factors and environmental factors are "low risk", and the overall risk level of miners' fatigue in a coal mine in Shaanxi province is "medium risk", and corresponding risk mitigation measures are proposed for personal factors and management factors with high risk levels.

This thesis forms a method system suitable for mining fatigue risk assessment research, and proves the effectiveness and feasibility of the ANP-cloud model constructed in this paper in fatigue risk assessment through case verification, which can provide thoughts for the risk management and scientific operation of similar projects.

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