Results 11 to 20 of about 1,067 (222)
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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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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Chatter Detection in Robotic Milling Using Entropy Features
Applied Sciences, 2022 Chatter detection in robotic milling is a difficult issue due to the complex dynamic behavior of robots. In this paper, a novel approach to detecting chatter in the robotic milling process is proposed.
Bin Yang, Kai Guo, Jie Sun
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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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Exploring the Potential of Transfer Learning for Chatter Detection
Procedia Computer Science, 2022 Chatter detection and avoidance are indispensable for many industries that rely on the machining process. The physics-based analytical models and recently successful machine learning methods can provide solutions using data from a unique setting. When the primary conditions of machining alter, new data needs to be collected, and analysis/training ...
Hakki Özgür Ünver, Batihan Sener
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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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Deep learning for the detection of machining vibration chatter
Advances in Engineering Software, 2023 Most of the work on chatter detection is based on laboratory machining tests, thus without the constraints of noise, the variety of situations to be managed in the industry, and the uncertainties on the parameters (sensor position, tool engagement, and sometimes even spindle rotation frequency).
Kounta, Cheick Abdoul Kadir A. +3 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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Sensors, 2022 Real-time chatter detection is crucial for the milling process to maintain the workpiece surface quality and minimize the generation of defective parts. In this study, we propose a new methodology based on the measurement of machine head stock structural
Kwanghun Jeong +4 more
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