Classification of CNC Vibration Speeds by Heralick Features
In the contemporary landscape of industrial manufacturing, the concept of computer numerical control (CNC) has emerged due to the optimization of conventional machinery, distinguished by its remarkable precision and expeditious processing capabilities. These inherent advantages have seamlessly paved...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Graz University of Technology
2024-03-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/106543/download/pdf/ |
| _version_ | 1797234254951743488 |
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| author | Melih Kuncan Kaplan Kaplan Yılmaz Kaya Mehmet Recep Minaz H. Metin Ertunç |
| author_facet | Melih Kuncan Kaplan Kaplan Yılmaz Kaya Mehmet Recep Minaz H. Metin Ertunç |
| author_sort | Melih Kuncan |
| collection | DOAJ |
| description | In the contemporary landscape of industrial manufacturing, the concept of computer numerical control (CNC) has emerged due to the optimization of conventional machinery, distinguished by its remarkable precision and expeditious processing capabilities. These inherent advantages have seamlessly paved the way for the pervasive integration of CNC machines across a myriad of industrial manufacturing sectors. The present study embarks upon a comprehensive inquiry, delving into the intricate analysis of a specialized prototype CNC molding machine, encompassing a meticulous assessment of its structural rigidity, robustness, and propensity for vibrational occurrences. Moreover, an insightful exploration is undertaken to discern the intricate interplay between vibrational signals and intricate machining processes, particularly under diverse conditions such as the presence or absence of the cutting tool, and at varying rotational speeds denoted in revolutions per minute (RPM). The trajectory of this research voyage encompasses an extensive array of empirical experiments meticulously conducted on the prototype CNC machine, with synchronous real-time acquisition of vibrational data. This empirical journey starts by generating two distinct datasets, each meticulously designed to encompass an assemblage of seven distinct rotational speeds, spanning the spectrum from 18000 to 30000 RPM, thereby facilitating enhanced diversity within the dataset. In parallel, a secondary dataset is meticulously derived from the CNC machine operating in the absence of the cutting tool, thereby encapsulating an exhaustive range of 20 discrete RPM values. The extraction of pivotal features aimed at discerning between the vibrational signals arising from distinct conditions (i.e., those emanating from situations involving the presence or absence of the cutting tool) and the associated variance in CNC machine speeds is facilitated through an innovative framework grounded in co-occurrence matrices. The culmination of this methodological framework is the identification of discernible co-occurrence matrices, thereby facilitating the subsequent computation of Heralick features. The classification effort was performed systematically using 10-fold cross-validation analysis, covering a number of different machine learning models. The outcomes emanating from this intricate sequence of systematic methodologies underscore remarkable achievements. Specifically, the classification of vibrational signals corresponding to varying CNC machine speeds, contingent upon the presence or absence of the cutting tool, yields commendable accuracy rates of 94.27% and 94.16%, respectively. Notably, an exemplary accuracy rate of 100% is attained when classifying differing conditions (i.e., situations involving the presence or absence of the cutting tool) across specific RPM settings, prominently at 22000  24000  26000  28000  and 30000 RPM.  |
| first_indexed | 2024-04-24T16:29:09Z |
| format | Article |
| id | doaj.art-5648e7658d824cf2bc601d8f4b51dd18 |
| institution | Directory Open Access Journal |
| issn | 0948-6968 |
| language | English |
| last_indexed | 2024-04-24T16:29:09Z |
| publishDate | 2024-03-01 |
| publisher | Graz University of Technology |
| record_format | Article |
| series | Journal of Universal Computer Science |
| spelling | doaj.art-5648e7658d824cf2bc601d8f4b51dd182024-03-30T07:33:11ZengGraz University of TechnologyJournal of Universal Computer Science0948-69682024-03-0130336338210.3897/jucs.106543106543Classification of CNC Vibration Speeds by Heralick FeaturesMelih Kuncan0Kaplan Kaplan1Yılmaz Kaya2Mehmet Recep Minaz3H. Metin Ertunç4Siirt UniversityKocaeli UniversityBatman UniversitySiirt UniversityKocaeli UniversityIn the contemporary landscape of industrial manufacturing, the concept of computer numerical control (CNC) has emerged due to the optimization of conventional machinery, distinguished by its remarkable precision and expeditious processing capabilities. These inherent advantages have seamlessly paved the way for the pervasive integration of CNC machines across a myriad of industrial manufacturing sectors. The present study embarks upon a comprehensive inquiry, delving into the intricate analysis of a specialized prototype CNC molding machine, encompassing a meticulous assessment of its structural rigidity, robustness, and propensity for vibrational occurrences. Moreover, an insightful exploration is undertaken to discern the intricate interplay between vibrational signals and intricate machining processes, particularly under diverse conditions such as the presence or absence of the cutting tool, and at varying rotational speeds denoted in revolutions per minute (RPM). The trajectory of this research voyage encompasses an extensive array of empirical experiments meticulously conducted on the prototype CNC machine, with synchronous real-time acquisition of vibrational data. This empirical journey starts by generating two distinct datasets, each meticulously designed to encompass an assemblage of seven distinct rotational speeds, spanning the spectrum from 18000 to 30000 RPM, thereby facilitating enhanced diversity within the dataset. In parallel, a secondary dataset is meticulously derived from the CNC machine operating in the absence of the cutting tool, thereby encapsulating an exhaustive range of 20 discrete RPM values. The extraction of pivotal features aimed at discerning between the vibrational signals arising from distinct conditions (i.e., those emanating from situations involving the presence or absence of the cutting tool) and the associated variance in CNC machine speeds is facilitated through an innovative framework grounded in co-occurrence matrices. The culmination of this methodological framework is the identification of discernible co-occurrence matrices, thereby facilitating the subsequent computation of Heralick features. The classification effort was performed systematically using 10-fold cross-validation analysis, covering a number of different machine learning models. The outcomes emanating from this intricate sequence of systematic methodologies underscore remarkable achievements. Specifically, the classification of vibrational signals corresponding to varying CNC machine speeds, contingent upon the presence or absence of the cutting tool, yields commendable accuracy rates of 94.27% and 94.16%, respectively. Notably, an exemplary accuracy rate of 100% is attained when classifying differing conditions (i.e., situations involving the presence or absence of the cutting tool) across specific RPM settings, prominently at 22000  24000  26000  28000  and 30000 RPM. https://lib.jucs.org/article/106543/download/pdf/CNCclassificationHeralick featuresmachine le |
| spellingShingle | Melih Kuncan Kaplan Kaplan Yılmaz Kaya Mehmet Recep Minaz H. Metin Ertunç Classification of CNC Vibration Speeds by Heralick Features Journal of Universal Computer Science CNC classification Heralick features machine le |
| title | Classification of CNC Vibration Speeds by Heralick Features |
| title_full | Classification of CNC Vibration Speeds by Heralick Features |
| title_fullStr | Classification of CNC Vibration Speeds by Heralick Features |
| title_full_unstemmed | Classification of CNC Vibration Speeds by Heralick Features |
| title_short | Classification of CNC Vibration Speeds by Heralick Features |
| title_sort | classification of cnc vibration speeds by heralick features |
| topic | CNC classification Heralick features machine le |
| url | https://lib.jucs.org/article/106543/download/pdf/ |
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