ISIJ International
Online ISSN : 1347-5460
Print ISSN : 0915-1559
ISSN-L : 0915-1559
Instrumentation, Control and System Engineering
Wear Debris Classification of Steel Production Equipment using Feature Fusion and Case-based Reasoning
Hongbing WangRong HuangLiyuan GaoWeishen WangAnjun XuFei Yuan
Author information

2018 Volume 58 Issue 7 Pages 1293-1299


Wear debris classification is of great significance for identifying machine wear states. In this paper, a method of wear debris classification using feature fusion and CBR is proposed. The method integrates local feature LBP, global feature FD and Tamura coarseness, and then the fused features are applied in CBR system with different weights and different similarity, which is adaptable, extendable, modular and fast. The results show that the subdivision of wear debris images into size 32*32 when calculating LBP is helpful for improving the classification, the combination of local features and global features can get better results. The comparative experimental results of different classification methods show that the CBR system has the shortest time-consuming while maintaining high classification accuracy.

Information related to the author
© 2018 by The Iron and Steel Institute of Japan
Previous article Next article