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A Meta-Invariant Feature Space Method for Accurate Tool Wear Prediction Under Cross Conditions
IEEE Transactions on Industrial Informatics, 2022Cross conditions prediction is a prevalent problem in manufacturing area, where tool wear prediction is a typical one. Existing data-driven methods for tool wear prediction mainly focus on cutting conditions with small variations, which encounters much ...
Changqing Liu +3 more
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Prediction of tool wear based on GA-BP neural network
Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture, 2022The anisotropy and nonuniformity of wood-plastic composites (WPCs) affect the milling tool, which rapidly wears during high-speed milling of WPCs. Thus, the evolution mechanism of tool failure becomes complicated, and the prediction of tool wear cannot ...
Weihua Wei +5 more
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A U-Net-Based Approach for Tool Wear Area Detection and Identification
IEEE Transactions on Instrumentation and Measurement, 2021The tool wear condition monitoring is key to ensuring product quality. This article develops a direct technique dealing with cutting tool images to automate the tool wear detection and identification.
Huihui Miao +4 more
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Tool wear estimation using a CNN-transformer model with semi-supervised learning
Measurement science and technology, 2021In the machining industry, tool wear has a great influence on machining efficiency, product quality, and production costs. To achieve accurate tool wear estimation, a novel CNN-transformer neural network (CTNN) model is proposed in this paper.
Hui Liu +5 more
semanticscholar +1 more source
DIAGNOSIS OF TOOL WEAR WITH A MICROCONTROLLER
IFAC Proceedings Volumes, 2006Tool wear monitoring is very important for economical reasons. In this paper a very economical solution is presented. The idea is to use easily available microcontroller based hardware, which is very cheap due to mass production. The cheap hardware is combined together with sophisticated software. The use of regression analysis techniques together with
Jantunen Erkki, Vaajoensuu Eero
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Physics-Informed Deep Learning for Tool Wear Monitoring
IEEE Transactions on Industrial InformaticsTool condition monitoring is essential to maintain the final product quality and machining efficiency of the manufacturing process. However, traditional physics-based and data-driven approaches have limitations either on prediction efficiency or ...
K. Zhu, Hao Guo, Sipei Li, Xin Lin
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Wear mechanism of ceramic tools
Wear, 1993Abstract Cutting tests were performed using ceramic cutting tools under continuous cutting conditions. The tests were carried out on AISI 1040 steel, with cutting speeds ranging from 5 to 11 m s −1 . The wear mechanism was investigated for both crater and flank.
CASTO SL +4 more
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Tool wear analysis in turning inconel-657 using various tool materials
Materials and Manufacturing ProcessesInconel 657, also known as 50Cr-50Ni, is a high-temp, corrosion-resistant Ni-Cr alloy with excellent fuel-ash corrosion resistance against sulfur and vanadium.
Yunhe Zou +3 more
semanticscholar +1 more source
Wear, 1973
Abstract Thermoelectric tool wear was measured by the thermocurrent generated in Machine-Tool-Workpiece-Machine (MTWM) circuit. The relationship between thermocurrent and the cutting parameters in the machining of EN 24 steel with a carbide tool and the significance of the influencing parameters are assessed statistically.
H. Bagchi, S.K. Basu
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Abstract Thermoelectric tool wear was measured by the thermocurrent generated in Machine-Tool-Workpiece-Machine (MTWM) circuit. The relationship between thermocurrent and the cutting parameters in the machining of EN 24 steel with a carbide tool and the significance of the influencing parameters are assessed statistically.
H. Bagchi, S.K. Basu
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1975
There are a group of problems which on face value appear to be associated with tool-wear mechanisms, but which, after a careful examination are either design based or metallurgical in their nature.
R. A. Etheridge, A. J. A. Scott
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There are a group of problems which on face value appear to be associated with tool-wear mechanisms, but which, after a careful examination are either design based or metallurgical in their nature.
R. A. Etheridge, A. J. A. Scott
openaire +1 more source

