基于综合图像处理技术的烧结铁矿粉高效利用研究

项目名称： 基于综合图像处理技术的烧结铁矿粉高效利用研究

项目编号： No.51504216

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 矿业工程

项目作者： 苏步新

作者单位： 冶金工业规划研究院

项目金额： 21万元

中文摘要： 铁矿粉的微观特性对于烧结生产十分重要，但目前不能对其进行定量分析。通过综合图像处理技术进行点线面多特征分析评价，得到铁矿粉微观特性定量指标，从而为铁矿石优化制粒和优化配矿提供微观特性指标。烧结矿矿相的合理组成是烧结矿强度和冶金性能优良的基础，传统方法通过人工数点进行定量计算，工作量大，效率低。通过对烧结矿矿相图像进行灰度特性和纹理特性分析，建立知识库规则，从而实现烧结矿矿相组成检测的高效识别和精确计算。利用综合图像处理技术高效检测铁矿粉微观特性和快速定量给出烧结矿矿物组成，给烧结铁矿粉高效利用提供有力的技术支撑。

中文关键词： 铁矿石；烧结矿；图像处理

英文摘要： The micro-characteristics of iron ore are vital to the sintering production while the quantitative analysis of them have not been carried out at present. To acquire the quantitative indexes of the micro-characteristics of iron ore, the multifeature analysis including point, line and region based on comprehensive image processing techniques was carried out so as to provide micro-characteristics indexes for optimizing sintering granulation and ore blending process. The proper mineral composition of iron ore sinter play a basic role in the strength and metallurgical properties of iron ore sinter. However, the traditional point counting method which is used to acquire the mineral composition of iron ore sinter is of high labor intensity and of low efficiency. Therefore, the mineral composition of iron ore sinter was obtained efficiently and effectively by analyzing the grey feature image and the texture feature image of the iron ore sinter based on knowledge base rules. The high-efficiency of obtaining micro-characteristic and mineral composition of iron ore based on comprehensive image processing techniques would provide effectively technical support for the high-efficiency application of iron ores.

英文关键词： iron ore;sinter;image processing