基于磨粒特征分析的铁谱图像灰色关联度判决研究
he study of grey relational degree identification based on characterization analysis of wear debris in the ferrographic image
铁谱技术实现自动化、智能化是铁谱研究领域的难点和热点问题。计算机技术，尤其是数字图像分析技术的运用，可以在很大程度上解决其中的一些关键问题。本文以VC++ 6.0为开发平台，基于数字图像分析提取图谱中磨粒特征参量，如面积、圆度及纵横比等，建立了特征参数矩阵。在基于所提取的特征参量进行模式识别时，采用灰色关联度理论对磨粒的类别判决作了探索研究，开发了一套用于磨粒类别判决的软件系统。使用该软件系统对实际铁谱图像进行分析，实现了铁谱中磨粒分类的自动化。
t has been focused that how to realize automatization and intelligence in the ferrographic diagnosis field in order to overcome the subjectivity of diagnosis process. It is reported that a characteristic metric has been built in the basis on VC++ 6.0 platform with the characteristic parameters, such as area, roundness, aspect ratio and so on, which extracted from image of wear debris based on digital image analysis. However, the extraction of characteristic parameters from a ferrographic image is not the ultimate purpose for ferrographic diagnosis. These wear particles should be classified into several per-decision degrees and their statistical distribution should also be calculated. In the present paper, the grey relational degree theory was introduced to recognize the wear debris and a new software system was developed to deal with the questions occurred in the ferrographic automatizational diagnosis. It was shown that the identification rules can be used to treat some real wear de
胡献国、詹松、郑寿森
自动化技术、自动化技术设备计算技术、计算机技术自动化基础理论
铁谱特征参量特征提取灰色关联度
Ferrographic imageCharacteristic parameterCharacteristic extractionGrey
胡献国,詹松,郑寿森.基于磨粒特征分析的铁谱图像灰色关联度判决研究[EB/OL].(2004-01-08)[2025-08-11].http://www.paper.edu.cn/releasepaper/content/200401-13.点此复制
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