Research on automatic monitoring method of face milling cutter wear based on dynamic image sequence

Tool wear is an important factor affecting the quality of finished products, productivity, and the normal operation of machine tools, so tool condition monitoring (TCM) has become a research hotpot in the field of intelligent manufacturing. Compared with traditional monitoring methods, vision-based...

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Bibliographic Details
Published in:International journal of advanced manufacturing technology 2020-10, Vol.110 (11-12), p.3365-3376
Main Authors: Qin, Aoping, Guo, Liang, You, Zhichao, Gao, Hongli, Wu, Xiangdong, Xiang, Shoubing
Format: Article
Language:English
Subjects:
CAE) and Design
Computer-Aided Engineering (CAD
Engineering
Error analysis
Face milling
Face milling cutters
Five axis
Image acquisition
Image processing
Industrial and Production Engineering
Intelligent manufacturing systems
Machine tools
Machinery condition monitoring
Mechanical Engineering
Media Management
Modules
Original Article
Target recognition
Tool wear
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Summary:Tool wear is an important factor affecting the quality of finished products, productivity, and the normal operation of machine tools, so tool condition monitoring (TCM) has become a research hotpot in the field of intelligent manufacturing. Compared with traditional monitoring methods, vision-based tool condition monitoring methods are more accurate and intuitive. However, the existing visual monitoring method requires manual adjustment of the tool position, and the degree of automation needs to be improved. Therefore, this paper proposes automatic face milling cutter condition monitoring method based on dynamic image sequence. We first acquire the dynamic image sequence of face milling cutter with the spindle rotating, then forward the dynamic image sequence to the image processing module to extract target area. And the images after image processing are propagated to the image selection module to obtain the image to be measured. Finally, forward the selected image to wear value measurement module to obtain the wear value. The presented automatic face milling cutter condition monitoring method is verified on a five-axis milling center. Compared with the direct measurement results of industrial digital microscope, the measurement error of the proposed method is within 4%, which is a reliable and effective online monitoring method for milling cutter wear.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-020-05955-x