Superior surface finish remains a fundamental criterion in precision machining operations,and tool-tip vibration is an important factor that significantly influences the quality of the machined surface.Physics-based m...Superior surface finish remains a fundamental criterion in precision machining operations,and tool-tip vibration is an important factor that significantly influences the quality of the machined surface.Physics-based models heavily rely on assumptions for model simplification when applied to complex high-end systems.However,these assumptions may come at the cost of compromising the model's accuracy.In contrast,data-driven techniques have emerged as an attractive alternative for tasks such as prediction and complex system analysis.To exploit the advantages of data-driven models,this study introduces a novel convolutional enhanced transformer model for tool-tip vibration prediction,referred to as CeT-TV.The effectiveness of this model is demonstrated through its successful application in ultra-precision fly-cutting(UPFC)operations.Two distinct variants of the model,namely,guided and nonguided CeT-TV,were developed and rigorously tested on a data set custom-tailored for UPFC applications.The results reveal that the guided CeT-TV model exhibits outstanding performance,characterized by the lowest mean absolute error and root mean square error values.Additionally,the model demonstrates excellent agreement between the predicted values and the actual measurements,thus underlining its efficiency and potential for predicting the tool-tip vibration in the context of UPFC.展开更多
There have been various theoretical attempts by researchers worldwide to link up different scales of plasticity studies from the nano-, micro- and macro-scale of observation, based on molecular dynamics, crystal plast...There have been various theoretical attempts by researchers worldwide to link up different scales of plasticity studies from the nano-, micro- and macro-scale of observation, based on molecular dynamics, crystal plasticity and continuum mechanics. Very few attempts, however, have been reported in ultra-precision machining studies. A mesoplasticity approach advocated by Lee and Yang is adopted by the authors and is successfully applied to studies of the micro-cutting mechanisms in ultra-precision machining. Traditionally, the shear angle in metal cutting, as well as the cutting force variation, can only be determined from cutting tests. In the pioneering work of the authors, the use of mesoplasticity theory enables prediction of the fluctuation of the shear angle and micro-cutting force, shear band formation, chip morphology in diamond turning and size effect in nano-indentation. These findings are verified by experiments. The mesoplasticity formulation opens up a new direction of studies to enable how the plastic behaviour of materials and their constitutive representations in deformation processing, such as machining can be predicted, assessed and deduced from the basic properties of the materials measurable at the microscale.展开更多
基金supported by the Science Challenge Project(No.JDZZ2016006-0102).
文摘Superior surface finish remains a fundamental criterion in precision machining operations,and tool-tip vibration is an important factor that significantly influences the quality of the machined surface.Physics-based models heavily rely on assumptions for model simplification when applied to complex high-end systems.However,these assumptions may come at the cost of compromising the model's accuracy.In contrast,data-driven techniques have emerged as an attractive alternative for tasks such as prediction and complex system analysis.To exploit the advantages of data-driven models,this study introduces a novel convolutional enhanced transformer model for tool-tip vibration prediction,referred to as CeT-TV.The effectiveness of this model is demonstrated through its successful application in ultra-precision fly-cutting(UPFC)operations.Two distinct variants of the model,namely,guided and nonguided CeT-TV,were developed and rigorously tested on a data set custom-tailored for UPFC applications.The results reveal that the guided CeT-TV model exhibits outstanding performance,characterized by the lowest mean absolute error and root mean square error values.Additionally,the model demonstrates excellent agreement between the predicted values and the actual measurements,thus underlining its efficiency and potential for predicting the tool-tip vibration in the context of UPFC.
基金the Research Committee of The Hong Kong Polytechnic University and the Innovation Technology Commission of The Hong Kong SAR Government for their financial support of the Hong Kong Partner State Key Laboratory of Ultra-Precision Machining Technology
文摘There have been various theoretical attempts by researchers worldwide to link up different scales of plasticity studies from the nano-, micro- and macro-scale of observation, based on molecular dynamics, crystal plasticity and continuum mechanics. Very few attempts, however, have been reported in ultra-precision machining studies. A mesoplasticity approach advocated by Lee and Yang is adopted by the authors and is successfully applied to studies of the micro-cutting mechanisms in ultra-precision machining. Traditionally, the shear angle in metal cutting, as well as the cutting force variation, can only be determined from cutting tests. In the pioneering work of the authors, the use of mesoplasticity theory enables prediction of the fluctuation of the shear angle and micro-cutting force, shear band formation, chip morphology in diamond turning and size effect in nano-indentation. These findings are verified by experiments. The mesoplasticity formulation opens up a new direction of studies to enable how the plastic behaviour of materials and their constitutive representations in deformation processing, such as machining can be predicted, assessed and deduced from the basic properties of the materials measurable at the microscale.
