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dc.contributor.authorArévalo Ruedas, Jose Humberto
dc.contributor.authorEspinel Blanco, Edwin
dc.contributor.authorFlorez Solano, Eder
dc.coverage.spatialColombiaen_US
dc.date.accessioned2025-09-24T20:04:00Z
dc.date.available2025-09-24T20:04:00Z
dc.date.issued2021-09-24
dc.identifier.issn1742-6588en_US
dc.identifier.urihttps://repositorioinstitucional.ufpso.edu.co/xmlui/handle/20.500.14167/5601
dc.description.abstractLa vida útil de las herramientas es un factor económico muy importante en la industria metalúrgica, por lo que cualquier mejora de la herramienta o del material que pueda prolongar la vida útil de las herramientas es productiva. El deterioro de las herramientas puede causar daños, grietas y vibraciones en las mismas, e incluso daños en la máquina. El control eficaz del desgaste de las herramientas es muy importante. El control eficaz del desgaste de las herramientas es de suma importancia. En la actualidad, existen algunas herramientas que pueden obtener las condiciones necesarias mediante el procesamiento digital de imágenes y estudiar su vida útil en función de su ciclo de trabajo, así como los tipos de relaciones posibles entre los píxeles de la imagen y los diferentes modos de funcionamiento, lo que permite la extracción o el aislamiento de los objetos considerados. Este trabajo analiza el desgaste de la herramienta con la aplicación de matrices bidimensionales con el conjunto de herramientas del software MATLAB, que permite monitorizar el estado de las plaquitas con la comparación de imágenes en escala de grises, además, se está estudiando un método de análisis basado en interfaces; a través de él, los usuarios pueden acceder a la base de datos que se ha implementado, así como a un conjunto de imágenes utilizadas para verificar las funciones desarrolladas, determinando el desgaste de la herramienta de corte.en_US
dc.language.isoen_USen_US
dc.relationhttps://iopscience.iop.org/article/10.1088/1742-6596/2139/1/012018/metaen_US
dc.titleAnálisis de desgaste en herramientas de corte mediante la técnica de procesamiento de imágenes con aplicación de matrices bidimensionalesen_US
dc.title.translatedWear analysis in cutting tools by the technique of image processing with the application of twodimensional matricesen_US
dc.contributor.cvlacJose Humberto Arévalo Ruedas [0000056272]en_US
dc.contributor.cvlacEdwin Espinel Blanco [0001200917]en_US
dc.contributor.cvlacEder Flórez Solano [0000668125]en_US
dc.contributor.googlescholarJose Humberto Arévalo Ruedas [cmXTAEMAAAAJ]en_US
dc.contributor.googlescholarEdwin Espinel Blanco [3ODKG4cAAAAJ]en_US
dc.contributor.googlescholarEder Flórez Solano [kjgjoYkAAAAJ]en_US
dc.contributor.orcidJose Humberto Arévalo Ruedas [0000-0003-4672-4533]en_US
dc.contributor.orcidEdwin Espinel Blanco [0000-0003-4479-2874]en_US
dc.contributor.orcidEder Flórez Solano [0000-0003-2527-0413]en_US
dc.contributor.scopusEdwin Espinel Blanco [57209774810]en_US
dc.contributor.scopusEder Flórez Solano [57200310518]en_US
dc.description.abstractenglishThe useful life of the tools is a very important economic factor in the metal industry, so any improvement of the tool or material that can extend the useful life of the tools is productive. Tool deterioration can cause damage, cracking and vibration to the tool, and even damage to the machine. Effective tool wear control is most important. Effective tool wear control is most important. At present, there are some tools that can obtain the necessary conditions through digital image processing, and study their lifespan according to their work cycle, as well as the types of possible relationships between the pixels of the image and the different modes of operation, allowing the extraction or isolation of the objects considered. This work analyzes the wear of the tool with the application of two-dimensional matrices with the toolbox of the MATLAB software, which allows to monitor the status of the inserts with the comparison of images in gray scales, in addition, a method of analysis based on interfaces is also being studied; through it, users can access the database that has been implemented, as well as a set of images used to verify the functions developed, determining the wear on the cutting tool.en_US
dc.subject.proposalAnálisis de desgasteen_US
dc.subject.proposalMatrices bidimensionalesen_US
dc.subject.proposalTécnica de procesamientoen_US
dc.subject.keywordsWear analysisen_US
dc.subject.keywordsTwo-dimensional matricesen_US
dc.subject.keywordsProcessing techniqueen_US
dc.publisher.facultyFacultad ingenieríasen_US
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTen_US
dc.relation.referencesMoldovan O G, Dzitac S, Moga I, Vesselenyi T, Dzitac I 2017 Tool-wear analysis using image processing of the tool flank. Symmetry 9(12) 296en_US
dc.relation.referencesLee Y, Kang T, Kim S, Lee Y, Shin D, Kim J 2021 Improving wear resistance of cBN-based cutting tools using TiN coating on cBN powder surface Colloids and Surfaces A: Physicochemical and Engineering Aspects 631 127758en_US
dc.relation.referencesDominguez-Caballero J A, Manson G A, Marshall M B 2016 Tool condition monitoring of ceramic inserted tools in high-speed machining through image processing International Journal of Materials and Metallurgical Engineering 10(8) 1427en_US
dc.relation.referencesPrado-Cerqueria M T 2015 Análisis de Desgaste de Herramienta y Optimización de Proceso Mecanizado Mediante Visión Computarizada y Consumo Eléctrico (Vigo: Universidad de Vigo)en_US
dc.relation.referencesThakre A A, Lad A V, Mala K 2019 Measurements of tool wear parameters using machine vision system Modelling and Simulation in Engineering 2019 1876489en_US
dc.relation.referencesMartínez-Arellano G, Terrazas G, Ratchev S 2019 Tool wear classification using time series imaging and deep learning The International Journal of Advanced Manufacturing Technology 104(9) 3647en_US
dc.relation.referencesPeng R, Pang H, Jiang H, Hu Y 2020 Study of tool wear monitoring using machine vision Automatic Control and Computer Sciences 54(3) 259en_US
dc.relation.referencesThe MathWorks Inc. 2018 MATLAB R2019b, 9.7.0.1190202 (Massachusetts: The MathWorks Inc.)en_US
dc.relation.referencesSaligheh A, Hajialimohammadi A, Abedini V 2020 Cutting forces and tool wear investigation for face milling of bimetallic composite parts made of aluminum and cast iron alloys International Journal of Engineering 33(6) 1142en_US
dc.relation.referencesMohanta N, Singh R K, Sharma A K 2020 Online monitoring system for tool wear and fault prediction using artificial intelligence International Conference on Contemporary Computing and Applications (Lucknow: Institute of Electrical and Electronics Engineers)en_US
dc.relation.referencesD’Addona D M, Teti R 2013 Image data processing via neural networks for tool wear prediction Procedia CIRP 12 252en_US
dc.relation.referencesHou Q, Sun J, Huang P 2019 A novel algorithm for tool wear online inspection based on machine vision The International Journal of Advanced Manufacturing Technology 101(9) 2415en_US
dc.relation.referencesWu X, Liu Y, Zhou X, Mou A 2019 Automatic identification of tool wear based on convolutional neural network in face milling process Sensors 19(18) 3817en_US
dc.relation.referencesInternational Organization for Standardization (ISO) 1989 Tool-life Testing in Milling – Part 1: Face Milling, ISO 8688-1 (Switzerland: International Organization for Standardization)en_US
dc.relation.referencesSharma E, Shivali, Jyotsna, Mahapatra P, Doegar A 2017 Tool condition monitoring using the chain code technique, pixel matching and morphological operations International Conference on Computational Intelligence and Communication Technology (Ghaziabad: Institute of Electrical and Electronics Engineers)en_US
dc.relation.referencesBergs T, Holst C, Gupta P, Augspurger T 2020 Digital image processing with deep learning for automated cutting tool wear detection Procedia Manufacturing 48 947en_US
dc.relation.referencesOng P, Lee W K, Lau R J H 2019 Tool condition monitoring in CNC end milling using wavelet neural network based on machine vision The International Journal of Advanced Manufacturing Technology 104(1) 1369en_US
dc.relation.referencesOo H H, Wang W, Liu Z 2020 Tool wear monitoring system in belt grinding based on image-processing techniques The International Journal of Advanced Manufacturing Technology 111(7) 2215en_US
dc.relation.referencesCampillo Fuentes J A 2012 Programación de una Interfaz Gráfica con Diferentes Módulos Para el Tratamiento Digital de Imágenes en Entornos Industriales (Cartagena: Universidad Politécnica De Cartagena)en_US
dc.relation.referencesGu P, Zhu C, Yu Y, Liu D, Tao Z, Wu Y 2021 Evaluation and prediction of drilling wear based on machine vision The International Journal of Advanced Manufacturing Technology 114(7) 2055en_US
dc.relation.referencesBagga P J, Makhesana M A, Patel K, Patel K M 2021 Tool wear monitoring in turning using image processing techniques Materials Today: Proceedings 44 771en_US
dc.relation.referencesBagga P J, Makhesana M A, Patel K M 2021 A novel approach of combined edge detection and segmentation for tool wear measurement in machining Production Engineering 15(3) 519en_US
dc.relation.referencesZhang X, Zheng G, Cheng X, Xu R, Zhao G, Tian Y 2020 Fractal characteristics of chip morphology and tool wear in high-speed turning of iron-based super alloy Materials 13(4) 1020en_US
dc.relation.referencesPrakash M, Kanthababu M, Kumar A, Arun N, Venkadesan V 2020 Identification of tool wear status and correlation of chip morphology in micro-end milling of mild steel (SAE 1017) using acoustic emission signal IOP Conference Series: Materials Science and Engineering 912(1) 032066:1en_US
dc.relation.referencesSanz A J 2013 Reconocimiento Automático de Formas (Barcelona: Universidad de Barcelona)en_US
dc.relation.referencesGarcía-Ordás M T, Alegre E, González-Castro V, Alaiz-Rodríguez R 2017 A computer vision approach to analyze and classify tool wear level in milling processes using shape descriptors and machine learning techniques The International Journal of Advanced Manufacturing Technology 90(5) 1947en_US
dc.identifier.DOI10.1088/1742-6596/2139/1/012018en_US


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