Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard

Abstract: The purpose of this study was to develop an automatic indirect (non-invasive) system to identify the condition of drill bits on the basis of the measurement of feed force, cutting torque, jig vibrations, acoustic emission and noise which were all generated during machining. The k-nearest n...

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Autores principales:	Jegorowa,Albina, Górski,Jarostaw, Kurek,Jarostaw, Kruk,Michat
Lenguaje:	English
Publicado:	Universidad del Bío-Bío 2020
Materias:	Drilling melamine faced particleboard k-NN classifier tool condition identification MATLAB.
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2020000200189
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spelling	oai:scielo:S0718-221X20200002001892020-05-08Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboardJegorowa,AlbinaGórski,JarostawKurek,JarostawKruk,Michat Drilling melamine faced particleboard k-NN classifier tool condition identification MATLAB. Abstract: The purpose of this study was to develop an automatic indirect (non-invasive) system to identify the condition of drill bits on the basis of the measurement of feed force, cutting torque, jig vibrations, acoustic emission and noise which were all generated during machining. The k-nearest neighbors algorithm classifier (k-NN) was used. All data analyses were carried out in MATLAB (MathWorks - USA) environment. It was assumed that the most simple (but sufficiently effective in practice) tool condition identification system should be able to recognize (in an automatic way) three different states of the tool, which were conventionally defined as “Green” (tool can still be used), “Red” (tool change is necessary) and “Yellow” (intermediate, warning state). The overall accuracy of classification was 76 % what can be considered a satisfactory result at this stage of studies.info:eu-repo/semantics/openAccessUniversidad del Bío-BíoMaderas. Ciencia y tecnología v.22 n.2 20202020-04-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2020000200189en10.4067/S0718-221X2020005000205
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Drilling melamine faced particleboard k-NN classifier tool condition identification MATLAB.
spellingShingle	Drilling melamine faced particleboard k-NN classifier tool condition identification MATLAB. Jegorowa,Albina Górski,Jarostaw Kurek,Jarostaw Kruk,Michat Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard
description	Abstract: The purpose of this study was to develop an automatic indirect (non-invasive) system to identify the condition of drill bits on the basis of the measurement of feed force, cutting torque, jig vibrations, acoustic emission and noise which were all generated during machining. The k-nearest neighbors algorithm classifier (k-NN) was used. All data analyses were carried out in MATLAB (MathWorks - USA) environment. It was assumed that the most simple (but sufficiently effective in practice) tool condition identification system should be able to recognize (in an automatic way) three different states of the tool, which were conventionally defined as “Green” (tool can still be used), “Red” (tool change is necessary) and “Yellow” (intermediate, warning state). The overall accuracy of classification was 76 % what can be considered a satisfactory result at this stage of studies.
author	Jegorowa,Albina Górski,Jarostaw Kurek,Jarostaw Kruk,Michat
author_facet	Jegorowa,Albina Górski,Jarostaw Kurek,Jarostaw Kruk,Michat
author_sort	Jegorowa,Albina
title	Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard
title_short	Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard
title_full	Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard
title_fullStr	Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard
title_full_unstemmed	Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard
title_sort	use of nearest neighbors (k-nn) algorithm in tool condition identification in the case of drilling in melamine faced particleboard
publisher	Universidad del Bío-Bío
publishDate	2020
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2020000200189
work_keys_str_mv	AT jegorowaalbina useofnearestneighborsknnalgorithmintoolconditionidentificationinthecaseofdrillinginmelaminefacedparticleboard AT gorskijarostaw useofnearestneighborsknnalgorithmintoolconditionidentificationinthecaseofdrillinginmelaminefacedparticleboard AT kurekjarostaw useofnearestneighborsknnalgorithmintoolconditionidentificationinthecaseofdrillinginmelaminefacedparticleboard AT krukmichat useofnearestneighborsknnalgorithmintoolconditionidentificationinthecaseofdrillinginmelaminefacedparticleboard
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Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard

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