| 摘要: |
| 通过采用人工神经网络方法对TC4钛合金电子束焊缝熔凝区形状尺寸进行预测研究.在大量工艺试验的基础上,采集网络训练样本,并对训练样本和测试样本进行标准化,通过确定合适的人工神经网络模型、网络结构、网络算法以及网络训练次数,建立了从聚焦电流、电子束流和焊接速度到焊缝熔深、熔宽、正面焊缝宽度、深宽比、焊缝余高、钉头半角的BP网络映射模型.结果表明,网络的最大输出相对误差不超过5%,说明该网络具有较强的映射能力,能满足预测要求。 |
| 关键词: 电子束焊接 熔凝区形状 人工神经网络 |
| DOI： |
| 分类号: |
| 基金项目:国防"973"基础研究项目(61362) |
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| ANN model to predict geometry shape of fusion-solidification zone in electron beam welding |
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LU Zhijun1, WANG Yajun1,2
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1.National Key Laboratory of High Energy Density Beam Processing Technology, Beijing Aeronautical Manufacturing Technology Research Institute, Beijing 100024, China;2.School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
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| Abstract: |
| The geometry shape of fusion-solidification zone in electron beam welding of TC4 titanium alloy was predicted based on artificial neural network.Based on adaptive network model, network structure, and training algorithm and times, a BP neural network mapping model from focused current, beam current and welding speed to fusion penetration, fusion width, top weld width, depth-to-width ratio, weld reinforcement, nailhead half-angle was established.Training samples were obtained from abundant process experiments and normalized for reducing prediction error.The predicted results indicate that maximum relative error is less than 5%, and the prediction requirement can be satisfied. |
| Key words: electron beam welding geometry shape of fusion-solidification zone ANN |
