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Wear state detection of the end milling cutter based on wear volume estimation
by
Zhan, Yang
, Tian, Ying
, Chen, Yujing
, Wang, Taiyong
, Zhao, Kaining
in
Algorithms
/ CAE) and Design
/ Computer-Aided Engineering (CAD
/ Cutting wear
/ Deformation effects
/ Deformation wear
/ Degradation
/ End milling cutters
/ Engineering
/ Industrial and Production Engineering
/ Mathematical analysis
/ Mechanical Engineering
/ Media Management
/ Milling cutters
/ Original Article
/ Precision machining
/ Reconstruction
/ Tool wear
/ Trends
2024
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Wear state detection of the end milling cutter based on wear volume estimation
by
Zhan, Yang
, Tian, Ying
, Chen, Yujing
, Wang, Taiyong
, Zhao, Kaining
in
Algorithms
/ CAE) and Design
/ Computer-Aided Engineering (CAD
/ Cutting wear
/ Deformation effects
/ Deformation wear
/ Degradation
/ End milling cutters
/ Engineering
/ Industrial and Production Engineering
/ Mathematical analysis
/ Mechanical Engineering
/ Media Management
/ Milling cutters
/ Original Article
/ Precision machining
/ Reconstruction
/ Tool wear
/ Trends
2024
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Do you wish to request the book?
Wear state detection of the end milling cutter based on wear volume estimation
by
Zhan, Yang
, Tian, Ying
, Chen, Yujing
, Wang, Taiyong
, Zhao, Kaining
in
Algorithms
/ CAE) and Design
/ Computer-Aided Engineering (CAD
/ Cutting wear
/ Deformation effects
/ Deformation wear
/ Degradation
/ End milling cutters
/ Engineering
/ Industrial and Production Engineering
/ Mathematical analysis
/ Mechanical Engineering
/ Media Management
/ Milling cutters
/ Original Article
/ Precision machining
/ Reconstruction
/ Tool wear
/ Trends
2024
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Wear state detection of the end milling cutter based on wear volume estimation
Journal Article
Wear state detection of the end milling cutter based on wear volume estimation
2024
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Overview
The process of high-speed and high-precision machining is highly dependent on the wear process of the tool, so it is necessary to obtain the accurate identification of the wear state of the tool and the timely prediction of the degradation trend through effective detection methods. However, the influencing factors of the real cutting process are complex and variable. The milling process is a complex spatial deformation process, accompanied by very high cutting accuracy requirements, and it is hard to use VB value, the currently popular singular linear indicator of wear state evaluation, to describe the current wear state of end mills precisely and difficult to make a valid decision proof for subsequent dynamic degradation trends. For these issues, a three-dimensional wear region reconstruction and calculation method for end milling cutters based on bi-sensor monitoring information is proposed in this paper, which can be accurately used to estimate the volume of current wear areas and give more reasonable predictions of future wear trends. Firstly, an in situ wear detection device with a bi-sensor based on an industrial camera and line laser scanner is designed, which can obtain the wear shape and depth information synchronously with high precision. Secondly, aiming at the problem of missing wear information due to uneven furring wear on the rear tool face of the end milling tool, this paper proposes a combined threshold segmentation method to extract the complete tool wear region, which improves the calculation precision of the wear region. Thirdly, the SFS algorithm, which integrates high-precision scale information from line laser data, is utilized to reconstruct the rear tool surface topography. This reconstruction allows for accurate estimation of the wear volume. Finally, the experiment results have shown that the wear volume can reflect the wear state of the tool more quickly and comprehensively compared with the traditional tool wear width standard, and it can provide early warning before the tool enters severe wear condition.
Publisher
Springer London,Springer Nature B.V
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