[1]黄鹏,贾民平,钟秉林,等.磨损磨粒显微形态分析与自动识别技术[J].东南大学学报(自然科学版),2006,36(3):411-415.[doi:10.3969/j.issn.1001-0505.2006.03.016]
 Huang Peng,Jia Minping,Zhong Binglin,et al.Micromorphology analysis and automatic identification technique for wear particles[J].Journal of Southeast University (Natural Science Edition),2006,36(3):411-415.[doi:10.3969/j.issn.1001-0505.2006.03.016]
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磨损磨粒显微形态分析与自动识别技术()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
36
期数:
2006年第3期
页码:
411-415
栏目:
机械工程
出版日期:
2006-05-20

文章信息/Info

Title:
Micromorphology analysis and automatic identification technique for wear particles
作者:
黄鹏1 贾民平1 钟秉林1 胡献国2
1 东南大学机械工程学院, 南京 210096; 2 合肥工业大学机械与汽车工程学院, 合肥 230009
Author(s):
Huang Peng1 Jia Minping1 Zhong Binglin1 Hu Xianguo2
1 College of Mechanical Engineering, Southeast University, Nanjing 210096, China
2 School of Mechanical and Automotive Engineering, Hefei University of Technology, Hefei 230009, China
关键词:
磨损磨粒 图像预处理 特征参数 灰色定权聚类
Keywords:
wear particle image pretreatment characteristic parameter fixed-weight-grey-clustering
分类号:
TH117.3
DOI:
10.3969/j.issn.1001-0505.2006.03.016
摘要:
在磨粒自动识别系统中,首先对彩色磨粒图像进行预处理,运用图像增强、自适应阈值选取、磨粒的标识和图像二值化方法成功地提取了特征磨粒; 然后根据磨粒的识别特征建立描述磨粒形态的特征参数体系,确定了磨粒的三类特征参数(颜色、表面纹理和形状尺寸参数),并对磨粒进行特征量提取创建参数数据库; 最后以提取的磨粒特征量为基础,运用灰色定权聚类的方法成功地识别了6种特征磨粒(正常磨粒、球形磨粒、切削磨粒、严重滑动磨粒、Fe2O3磨粒、Fe3O4磨粒).实验表明所提方法切实可行.
Abstract:
In the system of automatic identification for wear particles, the pretreatment methods including image enhancement, selection of adaptive threshold, marking debris and binary image are successfully applied to extract debris information from the color debris image. Then the characteristic parameter system of wear particles is produced by studying recognition character of wear particles. Three types of characteristic parameters(color, surface texture and shape and size)are confirmed. And a parameter database is founded with the extracted numerical descriptors of debris. Finally, the theory of fixed-weight-grey-clustering is successfully used to classify six types of wear particles(rubbing, spherical, cutting, severe sliding, Fe2O3 and Fe3O4 wear particles)according to their morphology numerical parameters analysis. The experimental results show that the methods proposed are feasible and effective.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金资助项目(50475078).
作者简介: 黄鹏(1981—),男,博士生; 贾民平(联系人),男,博士,教授,博士生导师,mpjia@seu.edu.cn.
更新日期/Last Update: 2006-05-20