化工进展2017，Vol.36Issue(9)：3195-3202,8.DOI:10.16085/j.issn.1000-6613.2017-0071
基于图像分析的底吹搅拌反应器混合特性
Study on mixing characteristics in bottom-blowing stirred reactor using image analysis
摘要
Abstract
The oxygen-enriched bottom-blowing smelting process is taken as research object. In order to measure and compare the local mixing characteristics in the bottom-blowing stirred reactor,the grayscale intensity was obtained based on field images of bubble perturbation. According to the actual size of bottom-blowing copper melting furnace,the test platform for water model of gas blowing was built. By watching high-speed videos of experimental process at different design parameters,the field RGB images of water model above the nozzles were captured and saved. Only the area undisturbed by apparatus was extracted as the study area. Finally,the grayscale intensity average and standard deviation of green component can be obtained. It was found that the green component of bubble RGB images extracted the contour features of actual bubble images more than other grayed images at our experimental conditions. The horizontal profiles of green component present obvious single apex and double peak,corresponding to the operating conditions of single-line nozzle and double-line nozzles, respectively. These results proved the validity of grayscale intensity for characterizing the mixing process. The mean and standard deviation time series of grayscale intensity in study area were calculated.Results showed that most times series follow Gaussian distributions statistically at the dynamic equilibrium stage of the bath. This work provides some academic bases and references on pushing the research about adopting image analysis techniques to investigate flow and mixing in the bottom-blowing stirred reactors.关键词
气液两相流/分布/搅拌容器/混合/成像Key words
gas-liquid flow/distributions/stirred vessel/mixing/imaging分类
矿业与冶金引用本文复制引用
肖清泰,王仕博,李鹏,高勤,徐建新,王华..基于图像分析的底吹搅拌反应器混合特性[J].化工进展,2017,36(9):3195-3202,8.基金项目
国家自然科学基金(51666006,51406071,U150220046)、张文海院士工作站(2015IC005)及云南省科技领军人才项目(2015HA019). （51666006,51406071,U150220046）
