A novel algorithm for tool wear online inspection based on machine vision

To inspect the tool wear condition in the process of numerical control (NC) machining for difficult-to-cut material, an online inspection system for tool wear is developed based on machine vision. With the help of MATLAB software, a self-matching algorithm is proposed according to the characteristic...

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Bibliographic Details
Published inInternational journal of advanced manufacturing technology Vol. 101; no. 9-12; pp. 2415 - 2423
Main Authors Hou, Qiulin, Sun, Jie, Huang, Panling
Format Journal Article
LanguageEnglish
Published London Springer London 01.04.2019
Springer Nature B.V
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ISSN0268-3768
1433-3015
DOI10.1007/s00170-018-3080-9

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Summary:To inspect the tool wear condition in the process of numerical control (NC) machining for difficult-to-cut material, an online inspection system for tool wear is developed based on machine vision. With the help of MATLAB software, a self-matching algorithm is proposed according to the characteristics of tool wear images. The corresponding user-friendly graphical user interface (GUI) of the algorithm is developed. The bottom edges are separated by the adaptive connecting domain labeling to analyze wear condition of each edge. Then, each edge is arranged regularly by the improved rotatory positioning. The cutting edge is extracted by the method of partial angle threshold to fit and calculate the bottom wear value. It is shown that the absolute values of errors on the maximum wear width are less than 0.007 mm by using the self-matching algorithm. In the case of severe wear and breakage, the absolute values of errors on the maximum wear width are less than 0.057 mm because of uneven reflected light. The system features high response speed, high inspecting accuracy, and anti-noise performance. It is proved to be able to increase the utilization of cutting tools and guarantee the quality of workpiece. This method is potential to guarantee the reliability of cutting tool in aerospace manufacturing.
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ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-018-3080-9