Results 11 to 20 of about 1,031 (236)
Automatic chatter detection in grinding [PDF]
International Journal of Machine Tools and Manufacture, 2003 Two methods for automatic chatter detection in outer diameter plunge feed grinding are proposed. The methods employ entropy and coarse-grained information rate (CIR) as indicators of chatter. Entropy is calculated from a power spectrum, while CIR is calculated directly from fluctuations of a recorded signal.
Janez Gradišek +4 more
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GA-PE-VMD and MSE Methods for Milling Chatter Feature Extraction of Thin-walled Parts
Journal of Harbin University of Science and Technology, 2023 In the high-speed milling of aviation parts, due to the low stiffness of thin-walled structure, it is easy to produce chatter. Chatter leads to poor surface quality, dimensional error and reducing the service life of tools and machines.Therefore, a ...
WANG Hanbin +4 more
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In-Process Chatter Detection in Milling: Comparison of the Robustness of Selected Entropy Methods
Journal of Manufacturing and Materials Processing, 2022 This article deals with the issue of online chatter detection during milling. The aim is to achieve a verification of the reliability and robustness of selected methods for the detection of chatter that can be evaluated on the machine tool in real time ...
Barbora Hauptfleischová +4 more
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Topological feature vectors for chatter detection in turning processes [PDF]
The International Journal of Advanced Manufacturing Technology, 2022 Machining processes are most accurately described using complex dynamical systems that include nonlinearities, time delays, and stochastic effects. Due to the nature of these models as well as the practical challenges which include time-varying parameters, the transition from numerical/analytical modeling of machining to the analysis of real cutting ...
Melih C. Yesilli +2 more
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Ensemble-Based Semi-Supervised Learning for Milling Chatter Detection
Machines, 2022 Chatter is one of the most deleterious phenomena during the machining process, and leads to a low quality of workpiece surface, a noisy workplace, and decreases in tool and machine life.
Weichao Liu, Pengyu Wang, Youpeng You
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Transfer learning for autonomous chatter detection in machining
Journal of Manufacturing Processes, 2022 Large-amplitude chatter vibrations are one of the most important phenomena in machining processes. It is often detrimental in cutting operations causing a poor surface finish and decreased tool life. Therefore, chatter detection using machine learning has been an active research area over the last decade.
Yesilli, Melih C. +2 more
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Optimization of Milling Processes: Chatter Detection via a Sensor-Integrated Vice
Machines, 2023 The future of the milling process is the fully autonomous operation of the machine tools. Developments in terms of automation and machine tool design are now enabling fully autonomous operation.
Panagiotis Stavropoulos +4 more
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In-Process Chatter Detection Using Signal Analysis in Frequency and Time-Frequency Domain
Machines, 2021 All machining processes involve vibrations generated by structural sources such as a machine’s moving parts or by the interaction between cutting tools and work-pieces.
Michele Perrelli +3 more
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Chatter detection algorithm based on machine vision [PDF]
The International Journal of Advanced Manufacturing Technology, 2011 Production of precise high-value mechanical elements requires a hundred percent on-site control. Chatter may occur due to random events. Although an unaided human eye can also easily identify the presence of chatter marks, it is economically ineffective. Therefore, an algorithm based on machine vision signals was proposed for surface inspection.
Szydłowski, Michał, Powałka, Bartosz
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On-Line Energy-Based Milling Chatter Detection
Journal of Manufacturing Science and Engineering, 2018 Milling exhibits forced vibrations at tooth passing frequency and its harmonics, as well as chatter vibrations close to one of the natural modes. In addition, there are sidebands, which are spread at the multiples of tooth passing frequency above and below the chatter frequency, and make the robust chatter detection difficult.
Caliskan, Hakan +2 more
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