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Proceedings Article

Wear and breakage monitoring of cutting tools by an optical method: theory

[+] Author Affiliations
Jianfeng Li, Yongqing Zhang, Fangrong Chen, Zhiren Tian

Shandong Univ. of Technology (China)

Yao Wang

Jinan Power Equipment Factory (China)

Proc. SPIE 2899, Automated Optical Inspection for Industry, 481 (October 3, 1996); doi:10.1117/12.253022
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From Conference Volume 2899

  • Automated Optical Inspection for Industry
  • Frederick Y. Wu; Shenghua Ye
  • Beijing, China | November 04, 1996

abstract

An essential part of a machining system in the unmanned flexible manufacturing system, is the ability to automatically change out tools that are worn or damaged. An optoelectronic method for in situ monitoring of the flank wear and breakage of cutting tools is presented. A flank wear estimation system is implemented in a laboratory environment, and its performance is evaluated through turning experiments. The flank wear model parameters that need to be known a priori are determined through several preliminary experiments, or from data available in the literature. The resulting cutting conditions are typical of those used in finishing cutting operations. Through time and amplitude domain analysis of the cutting tool wear states and breakage states, it is found that the original signal digital specificity (sigma) 2x and the self correlation coefficient (rho) (m) can reflect the change regularity of the cutting tool wear and break are determined, but which is not enough due to the complexity of the wear and break procedure of cutting tools. Time series analysis and frequency spectrum analysis will be carried out, which will be described in the later papers.

© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Jianfeng Li ; Yongqing Zhang ; Fangrong Chen ; Zhiren Tian and Yao Wang
"Wear and breakage monitoring of cutting tools by an optical method: theory", Proc. SPIE 2899, Automated Optical Inspection for Industry, 481 (October 3, 1996); doi:10.1117/12.253022; http://dx.doi.org/10.1117/12.253022


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