个体与环境交互作用下煤矿员工安全行为能力评价及动态预警

A great many related analyses show that human factor is the essential reason why coal mining accidents take place so frequently. In view of the complexity of coal mining safety environment system in our country, this project, by analysis of the typical coal mining accidents and on the basis of systematic thinking, takes coal miners’ safety behaviors as the research object to identify and verify the key influencing factors for miners’ safety behaviors. Using methods such as ridge regression analysis, this project calculates correlation coefficient between influencing factors on miners’ safety behaviors, and obtains the influence degree posed by environment factors on the miners’ safety behaviors via the miners’ individual factors, so as to reveal the law of interaction between individuals and environment. Considering the correlation between different influencing factors, in this project, SAS software is applied to obtain the actual ratio at which different environment factors interact with safety behavioral ability; meanwhile, the simulation model, constructed according to system dynamics, is applied to compare and evaluate the safety behavioral abilities from different miners groups. In the project, the indexes of all compositions in miners’ safety behavioral ability and the safety threshold of aggregate level of safety behavioral ability are obtained by adjusting the variables. And using programming language, a dynamic pre-warning system is constructed under the restraint of both single index and overall indexes. Additionally, the regulation mechanism of miners’ safety behavior is proposed with empirical and behavioral experimental research. By using multi-disciplinary theories and methods, the interaction mechanism between individual miners and environment is clarified, which can enrich Behavioral Science Theory system and help solve the difficult problem of quantization of safety behavior ability. This study can also provide decision-making reference for effective regulation and controlling of miners’ safety practice and prevention of coal mining accidents.

大量煤矿事故分析表明，人因是事故频发的主要致因。鉴于我国煤矿安全环境系统的复杂性，本项目以员工安全行为为研究对象，剖析典型煤矿事故，基于系统思考，识别和验证员工安全行为的关键影响因素；运用岭回归分析法等，计算员工安全行为影响因素间的关联系数，得出环境因素通过员工个体因素对其安全行为的影响程度，从而揭示员工个体与环境的交互作用规律；考虑不同影响因素间关联，借助SAS软件，求解不同因素对安全行为能力的实际作用率；应用系统动力学构建的仿真模型，对比评价不同群体员工安全行为能力；通过调控变量，求出员工安全行为能力各构成指标和总水平的安全阀值，采用编程语言，构建单指标和总水平双重阀值约束下的动态预警系统，并开展行为实验和实证应用研究。项目应用多学科理论和方法，理清员工个体与环境交互作用机理，突破安全行为评价难以量化的科学问题，可丰富行为科学理论体系，为有效调控员工安全行为实践和预防事故提供决策参考。

大量煤矿事故分析表明，人因是事故频发的主要致因。鉴于我国煤矿安全环境系统的复杂性，本项目以员工安全行为为研究对象，剖析典型煤矿事故，识别和验证员工安全行为的关键影响因素；借助典型事故分析、实地调研以及问卷调查、行为事件访谈等，验证所提取影响因子的可靠性和科学性。在甄别煤矿员工安全行为能力影响指标的基础上，对指标进行优选，量化指标层级结构，构建切实有效的煤矿员工安全行为能力评价指标体系。采用网络层次分析法计算煤矿员工安全行为能力各指标权重，根据权重值明晰指标对员工安全行为能力的影响程度；运用岭回归分析法，计算员工安全行为影响因素间的关联系数，分析关键影响因素对煤矿员工安全行为能力的作用路径，求解关键影响因素对员工安全行为能力的实际作用率，从而揭示员工个体与环境的交互作用规律。应用系统动力学构建的仿真模型，描述系统内函数间的关联，建立SD流图和仿真模型，对比评价不同群体员工安全行为能力，进一步明确煤矿员工安全行为能力预警机制，通过调控变量，求出员工安全行为能力各构成指标和总水平的安全阈值，采用编程语言，构建多指标安全阈值和总阈值双重约束下的安全行为预警系统。然后以模糊数学、神经网络理论为基础，构建基于模糊AHP的煤矿员工安全行为能力预警模型及基于补偿模糊神经网络的煤矿员工安全行为能力预警模型，对预警指标进行综合评价，根据预警指标值及预警界限，进行单指标预警及系统综合预警，并开展行为实验和实证应用研究。选取代表性案例煤矿，实证研究并验证煤矿员工安全行为能力预警测度效果，观测煤矿员工安全行为能力预警管理发展趋势。最后，依据预警分析与规避对策，以期实现煤矿安全预警管理模式的良好运行及员工不安全行为的有效综合管控。.项目应用多学科理论和方法，理清了员工个体与环境交互作用机理，突破了安全行为评价难以量化的科学问题，丰富了行为科学理论体系，为有效调控员工安全行为实践和预防事故提供了决策参考。