数控滚齿机工作台热-力变形分析及预测建模

doi:10.13229/j.cnki.jdxbgxb.20211350

摘要/Abstract

摘要：

为了减小滚齿机工作台变形对加工精度的影响，对工作台热、力变形进行了研究，提出一种基于子种群自适应思维进化算法优化反向传播（SAMEA-BP）神经网络的滚齿机工作台热-力变形预测方法。通过SAMEA对BP神经网络的初始值、权重和阈值等参量进行调整，有效提升了基于神经网络的热-力变形预测准确度。结合K均值聚类策略和灰色关联分析（GRA）对影响热误差的温度测点进行耦合性和关联度分析，将热误差输入变量从8个测点减少到3个；针对滚齿加工中切削力导致的工作台变形，利用机床主轴电流表征切削力，并作为预测模型的输入变量。试验结果表明：本文模型平均预测精度为95.1%，与其他模型进行的对比分析验证了本文SAMEA-BP模型的有效性和泛化性。

关键词: 热致误差, 力致误差, SAMEA?BP神经网络, 均值聚类算法, 灰色关联分析

Abstract:

In order to reduce the influence of hobbing workbench deformation on machining accuracy， the thermal and mechanical deformation of the workbench were studied.A Subpopulation Adaptive Mind Evolution Algorithm-Back Propagation Neural Network was proposed for thermal-mechanical deformation prediction of hobbing workbench. The initial value， weight and threshold of BP Neural Network were adjusted by SAMEA， which effectively improved the prediction accuracy. Combining K-means clustering and grey correlation analysis （GRA）， the thermal error input variables were reduced from eight to three. Aiming at the table deformation caused by cutting force in gear hobbing， the cutting force was represented by the current of machine tool spindle and used as the input variable of the prediction model. Experimental results show that the average prediction accuracy of the proposed SAMEA-BP model is 95.1%， and comparison with other models verifies the validity and generalization of the model.

Key words: thermal error, force error, SAMEA-BP neural network, mean clustering algorithm, grey relation analysis

中图分类号:

TH161

王四宝,郭忠政,马驰,王时龙. 数控滚齿机工作台热-力变形分析及预测建模[J]. 吉林大学学报(工学版), 2023, 53(10): 2761-2772.

Si-bao WANG,Zhong-zheng GUO,Chi MA,Shi-long WANG. Thermal-force deformation analysis and prediction modeling of CNC gear hobbing machine workbench[J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(10): 2761-2772.

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参数	取值	参数	取值
种群大小	40	子群体数	6
优胜子种群数	6	迭代次数	70
临时子种群数	6

滚刀参数	数值	齿轮参数	数值
头数	2	法向模数/mm	5.08
旋向	左旋	法向压力角/（°）	20
外径/mm	110	齿数	34
螺旋角	5°34′30″	齿顶圆直径/mm	192
容屑槽数	10	螺旋角/（°）	13
容屑槽类型	直槽	齿宽/mm	30

传感器	安装/检测位置	传感器	安装/检测位置
T1	小立柱外侧	T6	刀架侧面
T2	Z轴拖板丝杠套	T7	床身上表面
T3	Z轴拖板上部	T8	环境温度
T4	立柱Z轴静压导轨	S1	工作台X方向
T5	电主轴轴承侧面	S2	工作台Y方向

t/min	n/（r·min^-1）	f/（mm·min^-1）	a_p/mm
0~40	120	12	6
40~80	160	14	7
80~120	200	16	8

分组序号	K均值聚类分组结果			灰色关联度大小
1	T1	T2	T3	0.721	0.939	0.735
2	T4		T7	0.688		0.693
3	T5	T6	T8	0.705	0.694	0.687