基于视觉计算的井下信息感知理论与预警方法研究

项目名称： 基于视觉计算的井下信息感知理论与预警方法研究

项目编号： No.U1261114

项目类型： 联合基金项目

立项/批准年度： 2013

项目学科： 冶金与矿业学科

项目作者： 李占利

作者单位： 西安科技大学

项目金额： 60万元

中文摘要： 煤炭工业是我国国民经济和社会发展的基础产业，煤矿事故的频频发生使得煤矿安全成为国家和社会高度关心的问题。随着煤矿安全监测技术的迅速发展和工业视频监控系统的广泛应用，煤矿事故率逐渐下降，但与国外先进采煤国家相比仍有较大差距。采用新理论新技术不断提高煤矿安全监测的智能化水平，将是未来煤矿安全生产监控的发展方向。本课题对获取的大量煤矿井下视频图像，应用视觉计算的理论和方法进行分析，建立井下运动目标的检测及其状态信息描述和参数计算模型，从而达到对运动目标的行为分析和感知理解；采用视觉计算手段，结合标记目标的设计，建立静态目标的形变计算新理论，并在此基础上进行形变趋势分析研究，形成基于视觉计算的井下静态目标感知理论。在井下目标信息感知理论研究基础上，研究危险预防预报预警新方法，为最终研发智能矿井井下综合信息传感器奠定理论基础，为研发保障煤矿安全生产的新技术新产品提供理论依据。

中文关键词： 视觉计算；信息感知；预警方法；目标跟踪；形变计算

英文摘要： The coal mine industry is our country’s basic industry of national economic and social development. Because of the frequent occurrence of coal mine accidents, the coal mine safety has been highly concerned by the state and society. With the rapid development of coal mine safety monitoring technology and industrial video surveillance system widely used, the rate of coal mine accidents is decreased gradually. But there is still a large gap between our country and foreign advanced mining countries. It will be the development direction of future coal mine production safety monitoring, that using new theory and new technology to continuously improve the intelligence level of the coal mine safety monitoring. In this project, the visual computing theories and methods will be used to analyze a large number of the acquired coal mine video images, and the model of underground moving targets detection and their status information description and parameters calculation will be established, thus realizes the behavior analysis and perceived understanding of the moving targets; Using visual computing means, a new deformation calculating theory of the underground static targets will be established with the design of marked targets. Based on that, the deformation trend will be analyzed, and perception theory of the underground s

英文关键词： Visual computing；information perception；early warning method；object tracking；deformation computing