基于微观形貌的钢渣集料耐磨性能衰减规律研究
Study on the Attenuation Law of Wear Resistance of Steel Slag Aggregate Based on Microstructure
刘新元 1姚腾飞 2武旭 3刘沛麟 2屈上智2
作者信息
- 1. 甘肃省交通投资管理有限公司,甘肃兰州 730030
- 2. 兰州交通大学甘肃省交通土建材料研发与应用行业技术中心,甘肃兰州 730070
- 3. 兰州交通大学甘肃省交通土建材料研发与应用行业技术中心,甘肃兰州 730070;甘肃省交通规划勘察设计院股份有限公司,甘肃兰州 730010
- 折叠
摘要
为了研究钢渣集料耐磨性能衰减规律及其机理,使用加速磨光机对2种钢渣集料进行了磨光试验,通过摆式仪测量了不同磨光时间下2种集料的磨光值,分析了其耐磨性能衰减规律;采用激光共聚焦显微镜测量了不同磨光时间下2种钢渣集料表面微观形貌,研究了其微观形貌随磨光时间的变化;利用灰色关联度分析方法,分析了不同磨光时间下钢渣集料微观形貌评价指标与磨光值间的关联度.研究结果表明:随着磨光时间的增加,钢渣集料的磨光值均逐渐下降;钢渣集料的耐磨性与抗滑性取决于其成料方式和加工特性;钢渣集料的磨光值与波峰密度、尖度关联度达到0.75以上,可作为评价钢渣集料耐磨性能的可靠指标,而算数平均高度、最大高度、波峰平均曲率和偏斜度等指标可作为辅助性指标.
Abstract
In order to study the attenuation law of wear resistance and mechanization of steel slag aggregate,the ac-celerated polishing machine was used to polish two kinds of steel slag aggregates.Under different polishing time,the polishing values of two kinds of aggregates were measured by pendulum instrument to analyze the attenuation law of wear resistance;The surface micro-morphology was measure by laser confocal microscope to study the change rule of micro-morphology with polishing time;The grey correlation analysis method was used to analyze the correlation between the microscopic morphology evaluation index of steel slag aggregate and the polishing value under different polishing time.The results show that the polishing values of the two steel slag aggregates decrease gradually with the increase of polishing time;The wear resistance and skid resistance of steel slag aggregate depend on the way of ma-terial preparation and processing characteristics;The correlation between the polishing value of steel slag aggregate and the peak density and sharpness is above 0.75,which can be used as a reliable index to evaluate the wear resistance.The arithmetic mean height,maximum height,peak mean curvature and skewness can be used as auxiliary indexes.
关键词
道路工程/钢渣/集料/微观形貌/耐磨性能/规律Key words
road engineering/steel slag/aggregate/micro-morphology/wear resistance/law引用本文复制引用
基金项目
甘肃省自然科学基金在站博士后专项(23JRRA875)
出版年
2024
国家科技期刊平台
NSTL
万方数据