锻压技术

BP神经网络口罩齿模参数优化

英文标题：Optimization on parameter of mask tooth mold by BP neural network

作者：王钧李玮许静王周梅王泰恒

单位：西南林业大学

分类号：TQ330.4+1

出版年,卷(期):页码：2023,48(4):218-228

摘要：

针对齿模在旋压时由于结构复杂和切削刃口优化不够导致的落料或拉深不顺利的问题展开研究。对齿模切削刃口进行多组正态分布参数的超声波剪切有限元分析，模拟出不同切削刃口参数下的切断位移和剪切强度变化，并且对结果进行齐性检验和极差分析，以确保数据的可靠性，并分析了各数据对结果的影响程度。通过Matlab软件，对不同切削刃口参数和不同剪切强度、切断位移的关系构建BP神经网络，并进行拟合训练，通过神经网络反向模拟，推算出切削刃口的最佳参数，再将得到的参数值应用到实际的切削加工实验中，利用实验结果来验证预测的齿模切削刃口最佳参数的正确性和可靠性。研究成果为此类新型模具的设计提供了一种优化方案，为抗疫物资的生产提供了最优的加工数据。

The problems of blanking or deep drawing unsmoothly caused by the complex structure and insufficient cutting edge optimization of tooth mold during spinning were studied, and through the ultrasonic shear finite element analysis of multiple sets of normal distribution parameters on the cutting edge of tooth mold, the cutting displacement and shear strength changes under different cutting edge parameters were simulated. Then, the homogeneity test and range analysis on the results were carried out to ensure the reliability of the data, and the influence degree of each data on the results was analyzed. Furthermore, through Matlab software, the BP neural network was constructed for the relationship between different cutting edge parameters and shear strengths, cutting displacements, and the fitting training was carried out. Through neural network reverse simulation, the optimal cutting edge parameters were deduced, and the obtained parameter values were applied to the actual cutting experiment. The experimental results were used to verify the correctness and reliability of the predicted optimal parameters for the cutting edge of tooth mold. Thus, the study result provides an optimization scheme for the design of such new molds, and provides optimal processing data for the production of anti-epidemic materials.

基金项目：

云南省教育厅基金资助项目（2022Y569）

作者简介：王钧（1996-），男，硕士研究生 E-mail：270254127@qq.com 通信作者：李玮（1967-），女，博士，教授 E-mail：772074913@qq.com

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