☆ 4.6 Article

The prediction model and experimental research of grinding surface roughness based on AE signal

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2022)

Experimental evaluation of surface generation and force time-varying characteristics of curvilinear grooved micro end mills fabricated by EDM

Yao Sun et al.

Summary: In this study, curvilinear grooved micro textures were created on the rear surface of double helical micro end mills with a diameter of about 800μm by EDM method to lower specific milling energy and forces in dry micro milling experiments on aluminum alloy material. The results showed a significant reduction in specific cutting energy and forces when using micro end mills with curvilinear grooved micro textures compared to ordinary micro end mills.

JOURNAL OF MANUFACTURING PROCESSES (2022)

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Article Engineering, Manufacturing

Influence of the dynamic disc grinding wheel displacement on surface generation

Cong Sun et al.

Summary: This study investigates the surface generation mechanism of disc grinding by establishing an element deformation model on dynamic-static characteristic and a three-dimensional abrasive trajectory equation. The influence regulation of the system dynamic-static characteristic on machining surface waviness and surface roughness is explored, with findings indicating that static characteristic plays a key role in influencing disc grinding surface waviness, while disc grinding surface roughness is controlled by the system dynamic-static characteristic.

JOURNAL OF MANUFACTURING PROCESSES (2022)

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Article Computer Science, Artificial Intelligence

Activation functions selection for BP neural network model of ground surface roughness

Yuhang Pan et al.

JOURNAL OF INTELLIGENT MANUFACTURING (2020)

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Article Computer Science, Information Systems

Automatic sedimentary microfacies identification from logging curves based on deep process neural network

Hui Liu et al.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2019)

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Article Engineering, Manufacturing

In-process tool condition monitoring in compliant abrasive belt grinding process using support vector machine and genetic algorithm

Vigneashwara Pandiyan et al.

JOURNAL OF MANUFACTURING PROCESSES (2018)

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Article Engineering, Environmental

Prediction of impact sensitivity of nitro energetic compounds by neural network based on electrotopological-state indices

Rui Wang et al.

JOURNAL OF HAZARDOUS MATERIALS (2009)

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The prediction model and experimental research of grinding surface roughness based on AE signal

相关参考文献

Experimental evaluation of surface generation and force time-varying characteristics of curvilinear grooved micro end mills fabricated by EDM

Influence of the dynamic disc grinding wheel displacement on surface generation

Activation functions selection for BP neural network model of ground surface roughness

Automatic sedimentary microfacies identification from logging curves based on deep process neural network

In-process tool condition monitoring in compliant abrasive belt grinding process using support vector machine and genetic algorithm

Prediction of impact sensitivity of nitro energetic compounds by neural network based on electrotopological-state indices

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