Image recognition method for defect on coke with lowquality coal

Yasuhiro Saito, Tetsuya Kanai, Daisuke Igawa, Yukinori Miyamoto, Shohei Matsuo, Yohsuke Matsushita, Hideyuki Aoki, Seiji Nomura, Hideyuki Hayashizaki, Shigeto Miyashita

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The image recognition method was proposed to quantify non-adhesion grain boundaries which were considered as a factor of coke strength besides pores, and the correlation between coke strength and the amount of defects evaluated by the method was investigated in comparison with the one by the marking method. Coke with low-quality coal was fractured by a diametral-compression test, and the fracture crosssections were observed by a scanning electron microscopy (SEM) and a 3D laser scanning microscope (LSM). The marking method and image recognition method were applied to SEM and LSM images, respectively. As a result, the fracture strength measured by the diametral-compression test was linearly decreased with an increase in blending ratio of low-quality coal. In the marking method, most non-adhesion grain boundaries were not detected up to 50% in the blending ratio, and the boundaries increased sharply from 50 to 100% in the blending ratio. On the other hand, in the recognition method, the defects which were composed of both pores and non-adhesion grain boundaries, increased linearly with the blending ratio, and the amount of defects corresponded to coke strength. Therefore, the image recognition method is expected as the quantification technique of defects decreasing coke strength.

Original languageEnglish
Pages (from-to)2512-2518
Number of pages7
JournalIsij International
Volume54
Issue number11
DOIs
Publication statusPublished - 2014 Jan 1

Keywords

  • Coke
  • Ironmaking
  • Low-quality coal
  • Non-adhesion grain boundary

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering
  • Metals and Alloys
  • Materials Chemistry

Fingerprint Dive into the research topics of 'Image recognition method for defect on coke with lowquality coal'. Together they form a unique fingerprint.

  • Cite this

    Saito, Y., Kanai, T., Igawa, D., Miyamoto, Y., Matsuo, S., Matsushita, Y., Aoki, H., Nomura, S., Hayashizaki, H., & Miyashita, S. (2014). Image recognition method for defect on coke with lowquality coal. Isij International, 54(11), 2512-2518. https://doi.org/10.2355/isijinternational.54.2512