Online Tool Condition Monitoring Based on Parsimonious Ensemble+
نویسندگان
چکیده
منابع مشابه
Online Tool Condition Monitoring Based on Parsimonious Ensemble+
Accurate diagnosis of tool wear in metal turning process remains an open challenge for both scientists and industrial practitioners because of inhomogeneities in workpiece material, nonstationary machining settings to suit production requirements, and nonlinear relations between measured variables and tool wear. Common methodologies for tool condition monitoring still rely on batch approaches w...
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As manufacturing processes become increasingly automated, so should tool condition monitoring (TCM) as it is impractical to have human workers monitor the state of the tools continuously. Tool condition is crucial to ensure the good quality of products: Worn tools affect not only the surface quality but also the dimensional accuracy, which means higher reject rate of the products. Therefore, th...
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Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the...
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Monitoring the state of mechanical machine tool components is of growing importance for increasing machine tool availability and reducing inspection efforts and costs. Open Numeric Controls offer a new opportunity for getting access to signals of drives as well as of the control itself and to integrate end-user’s individual applications. Because the actual drive signals contain information on t...
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ژورنال
عنوان ژورنال: IEEE Transactions on Cybernetics
سال: 2020
ISSN: 2168-2267,2168-2275
DOI: 10.1109/tcyb.2018.2871120