Intelligent assessment of subsurface cracks in optical glass generated in mechanical grinding process

Yong Jie Zhao, Yun Hui Yan, Ke Chen Song, Hao Nan Li

Research output: Journal PublicationArticlepeer-review

7 Citations (Scopus)

Abstract

Grinding process of optical glass has been reported to be related with the creation of subsurface cracks. However, for the time being, most measurement methods have been depended on human operations. In this paper, an intelligent assessment method based on image processing technique is proposed. Grinding trials proved that, the proposed method can accurately (with the biggest relative error of 3.53%) and quickly (nearly 1.6 seconds per micrographs) recognize and measure the subsurface crack depths. More importantly, the proposed method has good robustness to different-sized images. Besides, the method does not require any input parameters or any adjustment of thresholds, therefore the method does not require any prior knowledge of either mechanical grinding process or brittle material behaviors relating with subsurface cracks. Based on above, the proposed method is expected to be meaningful to both metrology equipment companies and optical glass manufacturers.

Original languageEnglish
Pages (from-to)17-25
Number of pages9
JournalAdvances in Engineering Software
Volume115
DOIs
Publication statusPublished - Jan 2018
Externally publishedYes

Keywords

  • Automatic detection
  • Grinding
  • Image processing
  • Optical glass
  • Subsurface damage

ASJC Scopus subject areas

  • Software
  • General Engineering

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