On a Simulation-based Chatter Prediction System by Integrating Relative Entropy and Dynamic Cutting Force

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This paper presents a simulation-based system using relative entropy to predict chatter in NC programs by comparing dynamic and static cutting forces, enabling program modification for stable machining.

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This paper develops a simulation-based CNC chatter prediction system that uses relative entropy (Kullback-Leibler divergence) to quantify differences between dynamic cutting force and static cutting forces, with the goal of identifying chatter in an NC program and modifying it to be non-chatter. The method relies on generating a stability lobe diagram using cutting force coefficient values from cutting experiments and frequency response functions from tapping tests, which are stored in a database and used to support the simulation and KLD-based prediction. It was verified via on-site machining and reported to show promising performance, with major limitation/caveat implied by its dependence on experimentally obtained cutting force coefficients and FRFs and by being presented as a preprint without peer review at the time of posting. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

This paper aims to develop a simulation-based chatter prediction system using relative entropy - Kullback-Leibler Divergence (KLD), and the NC program can be modified to become non-chatter. Chatter is one of the major concerns when machining mechanical components on a CNC machine. In general, the majority of the previous research methods achieved non-chatter stable machining by assigning the appropriate machining parameters: (1) spindle speed, (2) feed rate, and (3) depth of cut based on the generated SLD (Stability Lobe Diagram). Non-chatter stable machining can also be accomplished by manually adjusting the spindle override percentage on the operation panel or the values in the CNC controller via networking once chatter is detected during the machining processes. The creation of SLD must consider two essential parameters: cutting force coefficient (CFC) and frequency response function (FRF). The CFC can be obtained from cutting experiment data related to a paired tool and workpiece, and the FRF can be calculated from the tapping test experiment. Then, the CFC and FRF are stored in the database of the developed system. The simulation-based chatter prediction calculates the KLD value based on the relativity of the dynamic cutting force and the static cutting forces so as to predict whether there is chatter in the NC program or not. The NC program can be adjusted to become non-chatter if there is chatter predicted. The proposed method has been successfully verified through on-site machining, showing very promising achievement.
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On a Simulation-based Chatter Prediction System by Integrating Relative Entropy and Dynamic Cutting Force | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article On a Simulation-based Chatter Prediction System by Integrating Relative Entropy and Dynamic Cutting Force trung kien vi, Bo-Cheng Luo, Hsiang-Chiu Wu, Meng-Jie Wu, Yung Chou Kao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3653974/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Feb, 2024 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted 5 You are reading this latest preprint version Abstract This paper aims to develop a simulation-based chatter prediction system using relative entropy - Kullback-Leibler Divergence (KLD), and the NC program can be modified to become non-chatter. Chatter is one of the major concerns when machining mechanical components on a CNC machine. In general, the majority of the previous research methods achieved non-chatter stable machining by assigning the appropriate machining parameters: (1) spindle speed, (2) feed rate, and (3) depth of cut based on the generated SLD (Stability Lobe Diagram). Non-chatter stable machining can also be accomplished by manually adjusting the spindle override percentage on the operation panel or the values in the CNC controller via networking once chatter is detected during the machining processes. The creation of SLD must consider two essential parameters: cutting force coefficient (CFC) and frequency response function (FRF). The CFC can be obtained from cutting experiment data related to a paired tool and workpiece, and the FRF can be calculated from the tapping test experiment. Then, the CFC and FRF are stored in the database of the developed system. The simulation-based chatter prediction calculates the KLD value based on the relativity of the dynamic cutting force and the static cutting forces so as to predict whether there is chatter in the NC program or not. The NC program can be adjusted to become non-chatter if there is chatter predicted. The proposed method has been successfully verified through on-site machining, showing very promising achievement. Chatter Prediction Dynamic Cutting Force Stability Lobe Diagram Relative Entropy Full Text Cite Share Download PDF Status: Published Journal Publication published 27 Feb, 2024 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted Editorial decision: Major Revisions Needed 18 Dec, 2023 Reviewers agreed at journal 29 Nov, 2023 Reviewers invited by journal 28 Nov, 2023 Editor assigned by journal 27 Nov, 2023 First submitted to journal 24 Nov, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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