【作者】 钟震宇；

【导师】 赵云胜； 蔡康旭；

【作者基本信息】 中国地质大学 ， 安全工程， 2006， 博士

【摘要】 如何改善恶劣的小煤矿安全生产状况是一个亟待解决的课题。应用煤矿安全生产监控系统对煤矿的生产状况进行监控，将在很大程度上减少生产事故的发生。但对于数量上占绝对多数的小煤矿而言，大型监控系统未能较好地发挥其作用。针对这一情况，近年来一些科研院所推出了面向小煤矿的“小型煤矿安全生产监控系统”，但它仍不能从根本上解决小煤矿管理不到位、技术人员缺乏、工作效率低等问题。 归其原因，长期以来的这种各矿自成体系的监管模式不适合小煤矿的具体情况，为此，本文探讨了一种新型监管模式——集群监管模式，并以该模式为基础，研发了与之相配套的更适合于小煤矿的通风瓦斯集群监控系统。 本论文做了如下几方面研究工作： 1、提出了小煤矿通风瓦斯集群监管模式 对于单个小煤矿而言，由于其开采规模与自身能力有限，难以将煤矿安全生产监控工作落实到位。而集群监管模式的提出，就是通过将多个小煤矿的实力联合起来，将有限资源重新整合，达到改善小煤矿安全生产状况的目的。该模式采用多个煤矿共一套监控系统，由远程监控中心负责对各矿集中监控。它能有效地避免单个煤矿的管理水平低，运转不正常，系统不兼容，监测监控人员配备不足等问题，形成区域范同内的集中联网调度指挥，从而实现小煤矿大管理，这种全新的管理模式必将促成小煤矿安全生产管理体制的一场重大变革。 2、研发了小煤矿通风瓦斯集群监控系统 该系统的特点是在各矿只配备智能分站和相应的显示报警装置，分站为无人值守的工作方式；作为监控核心的监控主机放置在远程监控中心，中心的技术人员通过远程监控的方式对各矿集中监管、调度。 对于监控系统而言，现场数据采集的准确性是确保系统有效发挥作用的关键而又基础的一环。为此，本文对瓦斯传感器的自校正技术进行了探讨。瓦斯传感器自校正技术分为硬件自校正和软件自校正两大类，而基于神经网络、遗传算法等方法的软件自校正技术已经取代硬件自校正技术成为传感器自校正技术的主流方向。尽管基于神经网络、遗传算法的软件自校正技术有着良好的校正精度，但却存在着系统开销大、硬件实现困难等问题。对此。本文提出了基于灰色预测理论的GM(1，1)模型的瓦斯传感器自校正技术，它是采用查表法的思想，该方法所需的原始数据少，有效避免了需要通过大量的测试获取分段函数的麻烦，易于单片机实现，也易于校正曲线的重构。通过对KJ-1型甲烷检测元件的校正测试，得出该方法的校正精度满足要求。 选择合适的通信方式有利于数据传输的准确可靠，同时也能节约成本。本系统采用的更多还原

【Abstract】 How to improve the serious situation of safety production in small coalmines is an urgent research topic. The application of Coalmine Safety Production Monitoring System to monitor the safety production situation can greatly reduce production accidents; but in terms of most small coalmines, the system doesn’t bring much effect. So in recent years, some research institutes come up with a Small Coalmine Safety Production Monitoring System developed specially for small coalmines. However, it still can’t solve small coalmines’ existing problems of lacking technicians, poor management, low efficiency, etc.In fact, the individual monitoring mode is not efficient considering the present situation in small coalmines. Therefore, this dissertation puts forward a completely new monitoring mode — Intensive Monitoring & Managing Mode For Small Coalmines, and correspondingly, develops a Ventilation & Gas Intensive Monitoring System For Small Coalmine.The dissertation has done research work in the following aspects:1. Putting forward the Intensive Monitoring & Managing Mode For Small Coalmines.For a small coalmine, because of its limited production scale and capability, it feels difficult to do the overall safety production monitoring. As for the Intensive Monitoring & Managing Mode, it could unite all the small coalmines in the region in order to achieve the goal of safety production. The new mode proposes that all the coalmines share one set of monitoring system and the monitoring task is performed by a remote monitoring center. It forms a large network to direct and control the safety production in each coalmine involved and thus can well solve single coalmine’s existing problem of low-level management, lacking monitoring technicians and the difficulty in maintaining and repairing equipments. It realizes the idea of Small Coalmine, Great Management and definitely will help bring about a big reform in small coalmines’ safety production management system.2. Developing the Ventilation & Gas Intensive Monitoring System For Small Coalmine.In this system, unmanned intelligent substation and devices for displaying and alarming are put in individual coalmine. As the core of the system, the monitoring computer is put in the remote monitoring center and the technicians there are in charge of the total control of the safety production in all coalmines.The accuracy of the data obtained in each coalmine is one of the key problems to be solved in the new system. So the dissertation discusses the self-correction technology for gas sensor.更多还原