| 基于主成分分析和变权相似性的粉体混合均匀性判断 |
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| 引用本文： | 刘鹏,田建艳,高炜,高云松,王国华,杨胜强. 基于主成分分析和变权相似性的粉体混合均匀性判断[J]. 金刚石与磨料磨具工程, 2019, 39(6): 13-19. DOI: 10.13394/j.cnki.jgszz.2019.6.0003 |
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| 作者姓名： | 刘鹏 田建艳 高炜 高云松 王国华 杨胜强 |
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| 作者单位： | 太原理工大学 电气与动力工程学院,太原030024;太原理工大学 机械与运载工程学院,太原030024;廊坊市北方天宇机电技术有限公司,河北 廊坊 065000 |
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| 基金项目： | 山西省研究生教育创新计划项目(2019SY156)。山西省回国留学人员科研资助项目(2017-032)山西省自然科学基金重点项目(201801D111002)山西省重点研发计划项目(201903D121057) |
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| 摘 要： | 为判断烧结型滚抛磨块制备过程中粉体原料的混合均匀性, 提出基于多图像相似性的粉体混合均匀度检测方法。 首先设计粉体采样装置在线采集粉体样本, 并利用数字显微镜采集粉体样本图像。 然后提取基于灰度直方图的图像灰度分布统计特征作为粉体图像特征参数, 采用主成分分析法(PCA)对特征参数降维, 并构建粉体图像特征矩阵。 最后计算每组图像中各粉体图像与样本密度中心的变权重相似度, 取其最小值作为该组图像的相似度, 并设定合适阈值判断粉体是否混合均匀。 试验结果表明: 该方法可以较为准确地判断混合终点, 并确定最佳混合时间, 适用于磨块粉体原料混合均匀性的判断, 从而提高生产效率和磨块质量, 提高经济效益。
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| 关 键 词： | 烧结型滚抛磨块 变权相似性 粉体图像相似性 混合均匀性 |
Judgment of powder mixing uniformity basedon principal component analysis and similarity with variable weight |
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| LIU Peng,TIAN Jianyan,GAO Wei,GAO Yunsong,WANG Guohua,YANG Shengqiang. Judgment of powder mixing uniformity basedon principal component analysis and similarity with variable weight[J]. Diamond & Abrasives Engineering, 2019, 39(6): 13-19. DOI: 10.13394/j.cnki.jgszz.2019.6.0003 |
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| Authors: | LIU Peng TIAN Jianyan GAO Wei GAO Yunsong WANG Guohua YANG Shengqiang |
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| Affiliation: | 1. Collegeof Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China;2. College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China;3. North Tianyu Electromechanical Technology Co., Ltd., Langfang 065000, Hebei, China |
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| Abstract: | To judge the mixing uniformity of powder materials during the preparation of sintered abrasive blocks, a detection method of powder uniformity based on the similarity of multiple powder imagesis proposed. Firstly, a deviceis designed to collect powder samples online, the image of which is collected by digital microscope. Then, the statistical features of gray distribution based on gray histogram are extracted as the feature parameters of the collected images. Principal component analysis (PCA) is used to reduce the dimension of image features and to construct image feature matrix. Finally the variable weight similarity of each powder image tothe sample density center in each set of images is calculated. The smallest one taken as the similarity with an appropriate thresholdis set to judge the powder whether to mix evenly. The experimental results show that the proposed method can accurately judge the mixing endpoint and determine the optimal mixing time. It is suitable for judging the mixing uniformity of powder materials in the sintered abrasive blocks. It is helpful to improve production efficiency and grinding block quality andincrease economic benefit. |
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