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摘要：
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在弯曲成形智能化控制过程的4个要素中,材料性能参数的实时识别占有极其重要的地位。为提高实时识别的精度和效率,根据宽板V型自由弯曲成形的特点,建立了宽板V型自由弯曲成形智能化控制过程材料性能参数实时识别的LM神经网络模型。训练结果表明,与改进的BP网络模型比较,LM网络模型的收敛精度和收敛速度均有明显的提高,为实现弯曲成形过程的智能化控制奠定了基础。
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In the four basic factors on the intellectualization of sheet metal forming,the real-time identification of the material performance parameter has a very important position.To improve accuracy and efficiency of the real-time identification,during the process of the intelligence control of wide V-shaped free bending,the real-time identification of the material performance parameter neural network model based on LM algorithm has been used based on the characteristic of V-shaped wide free bending.The training result proves that the converge accuracy and speed of the neutral network have been evidently boosted,compared with the improved neural network based on BP algorithm,it paves the way for the intelligent control of sheet metal forming.
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基金项目：
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河北省自然科学基金资助项目(501215)
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作者简介：
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参考文献：
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