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In-process tool wear measurement system based on image analysis for CNC drilling machines

 
: Lins, R.G.; Guerreiro, B.; Marques De Araujo, P.R.; Schmitt, R.

:

IEEE transactions on instrumentation and measurement 69 (2020), Nr.8, S.5579-5588
ISSN: 0018-9456
Englisch
Zeitschriftenaufsatz
Fraunhofer IPT ()

Abstract
Tool condition monitoring (TCM) has been a constant field of research. Conventionally, some sensors are installed at specific parts of the machine, and by using the signal-processing techniques, the tool wear is estimated. In this article, a direct system based on image analysis has been developed to automate the in-process tool wear measurement. The method uses only a single camera installed inside the machine and a tree-stage measurement process composed of image treatment, image comparison, and wear measurement. Experimental results show that the detection of similar images has a success index rate (SIR) equal to 98.89%, whereas the measurement error of the average flank wear and the maximum flank wear is estimated to be 3.57% and 2.92%, respectively.

: http://publica.fraunhofer.de/dokumente/N-602709.html