基于免疫机理的瓦斯异常涌出预警

Study on Early Warning of Abnormal Gas Emission Based on the Immune Mechanism

为了降低瓦斯异常涌出事故概率及危险程度,提出将生物免疫系统机理运用到瓦斯异常涌出预警系统.通过比较生物免疫系统和瓦斯异常涌出系统的相似性,提出基于免疫机理的预警系统包括监测监控子系统、控制决策子系统、应急救援子系统和记忆库子系统.依据Ag-Ab(抗原-抗体)模型建立起瓦斯异常涌出预警系统指标体系,并用层次分析法赋予相关权重.结果表明:瓦斯特性(AgⅢ)和安全管理(Ab I)对预警系统的影响较大,需要重点关注.通过MATLAB的Mamdani型模糊推理系统建立起预警模型,研究表明该模型能动态地进行预警,并根据预警级别进行响应,以提高响应速度从而降低涌出事故概率及危险性,为煤矿的瓦斯异常涌出预警提供参考和依据.

In order to reduce the probability and danger degree of abnormal gas emission, it is proposed to apply the mechanism of biological immune system to the early warning system of abnormal gas emission. By comparing the similarity between biological immune system and abnormal gas emission system, an early warning system based on immune mechanism is proposed, including monitoring and monitoring subsystem, control decision subsystem, emergency rescue subsystem, and memory subsystem. According to the Ag-Ab(antigen-antibody) model, the index system of gas abnormal out of the early warning system is established, and the relevant weight is given by the hierarchical analysis method. Results show that gas characteristics(Ag Ⅲ) and safety management(Ab I) have a great impact on early warning systems and need to be focused on. An early warning model is established through MATLAB’s Mamdani fuzzy inference system, and the research shows that the model can dynamically provide early warning and respond according to the early warning level, so as to improve the response speed and reduce the probability and danger of the outburst accident, which provides a certain reference and basis for the early warning of gas emission from coal mines.