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| Format: | Artículo científico |
| Language: | en |
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Universidad del Bío Bío
2020
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| Online Access: | https://www.redalyc.org/articulo.oa?id=48564749005 https://www.redalyc.org/journal/485/48564749005/ https://www.redalyc.org/journal/485/48564749005/html/ https://www.redalyc.org/journal/485/48564749005/48564749005.epub https://www.redalyc.org/journal/485/48564749005/movil |
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| author | Albina Jegorowa |
| author_facet | Albina Jegorowa |
| contents | Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard Albina Jegorowa Jarosław Górski Jarosław Kurek Michał Kruk Agrociencias MATLAB Drilling NN classifier faced particleboard tool condition identification 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. 2020 artículo científico 0717-3644 https://www.redalyc.org/articulo.oa?id=48564749005 https://www.redalyc.org/journal/485/48564749005/ https://www.redalyc.org/journal/485/48564749005/html/ https://www.redalyc.org/journal/485/48564749005/48564749005.epub https://www.redalyc.org/journal/485/48564749005/movil en http://www.redalyc.org/revista.oa?id=485 Maderas. Ciencia y Tecnología application/pdf Universidad del Bío Bío Maderas. Ciencia y Tecnología (Chile) Num.2 Vol.22 |
| format | Artículo científico |
| id | redalyc_48564749005 |
| language | en |
| publishDate | 2020 |
| publisher | Universidad del Bío Bío |
| spellingShingle | Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard Albina Jegorowa Agrociencias MATLAB Drilling NN classifier faced particleboard tool condition identification Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard Albina Jegorowa Jarosław Górski Jarosław Kurek Michał Kruk Agrociencias MATLAB Drilling NN classifier faced particleboard tool condition identification 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. 2020 artículo científico 0717-3644 https://www.redalyc.org/articulo.oa?id=48564749005 https://www.redalyc.org/journal/485/48564749005/ https://www.redalyc.org/journal/485/48564749005/html/ https://www.redalyc.org/journal/485/48564749005/48564749005.epub https://www.redalyc.org/journal/485/48564749005/movil en http://www.redalyc.org/revista.oa?id=485 Maderas. Ciencia y Tecnología application/pdf Universidad del Bío Bío Maderas. Ciencia y Tecnología (Chile) Num.2 Vol.22 |
| title | Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard |
| topic | Agrociencias MATLAB Drilling NN classifier faced particleboard tool condition identification |
| url | https://www.redalyc.org/articulo.oa?id=48564749005 https://www.redalyc.org/journal/485/48564749005/ https://www.redalyc.org/journal/485/48564749005/html/ https://www.redalyc.org/journal/485/48564749005/48564749005.epub https://www.redalyc.org/journal/485/48564749005/movil |