| 李东方， 杨海波， 黄林波， 林玉珍， 巫少龙， 徐文俊.基于神经网络与DEFORM的薄壁齿套高速车削工艺参数优化[J].轻工机械,2019,37(2):24-28 |
| 基于神经网络与DEFORM的薄壁齿套高速车削工艺参数优化 |
| Optimization of High Speed Turning Machining Parameters of Thin Walled Synchronous Gear Sleeve Based on Neural Network and DEFORM |
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| DOI：10.3969/j.issn.1005 2895.2019.02.005 |
| 中文关键词: 金属切削 薄壁齿套 车削力 DEFORM 3D软件 正交实验 神经网络模型 |
| 英文关键词:metal cutting thin walled synchronous gear sleeve turning force DEFORM 3D orthogonal test neural network model |
| 基金项目:浙江省衢州市科技局计划项目（2017G13）；国家重大科学仪器设备开发专项基金(2011YQ14014505)。 |
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| 中文摘要: |
| 为提高薄壁齿套的加工精度，对某型齿套的高速车削进行理论分析和切削力预测。利用DEFORM 3D软件建立齿套的高速
车削的数值分析模型，得到了正交试验车削工艺参数条件下的切削力；建立了神经网络模型，对切削力进行预测。结果表明，使用神经网络模型可精确预测高速
车削力大小，为新型专用夹具设计和优化加工工艺参数提供数据支持。 |
| 英文摘要: |
| In order to improve the machining accuracy of thin walled synchronous gear sleeve, theoretical analysis and cutting force forecasting of
high speed turning with a certain type of synchronizer were carried out. The numerical analysis model of high speed turning of synchronizer was established by DEFORM 3D software
to obtain the cutting force under the orthogonal test with different turning process parameters and the neural network model was established to forecast the cutting force. The results show
that the high speed turning force can be forecasted accurately by the neural network model, which provides data support for new special fixture design and process parameter
optimization. |
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