基于极限学习机的铁谱磨粒图像识别系统  

Ferrograghy Wear Particles Image Recognition Based on Extreme Learning Machine

作　　者：李琼[1] Li Qiong(College of Computer Science and Information Engineering, Tianjin University of Science andTechnology, Tianjin ,300457)

机构地区：[1]天津科技大学计算机科学与信息工程学院,天津300457

出　　处：《电子测试》2019年第4期47-48,40,共3页Electronic Test

摘　　要：本文提出了将极限学习机用于铁谱磨粒识别的方法。根据红色氧化物、疲劳磨粒、切削磨粒、球形磨粒和严重滑动磨粒五种典型磨粒的不同特征分别提取它们的形状特征、颜色特征和纹理特征作为支持向量机分类器的输入,以五种磨粒作为分类器的输出,建立基于极限学习机的磨粒分类器。In this paper, we propose to employ ELM for ferrograghy wear particles image recognition. We extract the shape features, color features and texture features of five typical kinds of wear particles (red oxide, fatigue wear particles, cutting wear particles, spherical wear particles, severe sliding particles) as the input of the ELM classifier and set five types of wear particles as the output of the ELM classifier. Therefore, the novel ferrograghy wear particle classifier is founded based on ELM.

关 键 词：磨粒 极限学习机 识别 特征提取 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP181[自动化与计算机技术—计算机科学与技术]