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融合机床加工特性的主轴回转误差预测
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江苏省前瞻性产学研联合创新资金项目(BY201502401)


Spindle Rotation Error Prediction Based on Fusion of Machining Characteristics
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    摘要:

    针对机械制造装备主轴精度补偿问题,研究一种融合机床精度和加工参数的主轴回转精度预测方法。为获取主轴回转精度指标,研究基于多点测量的主轴实际回转位置测量方法,利用最小二乘法求解主轴端面跳动的最大圆、最小圆和最优圆,进一步得到端面圆度的极大误差和极小误差。建立BP神经网络模型,融合机床精度因素、加工精度因素获得输入指标,将极大误差、极小误差和其余实测指标作为输出指标,训练神经网络,获得网络权值。验证机床主轴回转预测精度,实验结果表明:已训练的网络预测偏差为05%。考虑机床本体精度和加工参数的误差预测结果可指导工程技术人员进行机床选型,根据不同加工要求选择最优加工方式,提高加工质量。

    Abstract:

    Aiming at the problem of spindle accuracy compensation for mechanical manufacturing equipment, a spindle rotation accuracy prediction method combined the accuracy of machine tools and machining parameters was studied.In order to obtain the index of spindle rotation precision, the method of measuring the actual rotation position of the spindle based on multipoint measurement was studied.The least squares method was used to solve the maximum circle, the minimum circle, and the optimal circle of the spindle face runout, and the maximum error and minimum error of the end surface roundness were further obtained.A BP neural network model was established to integrate the machine tool accuracy factors and machining accuracy factors to obtain input indicators. The maximum error, minimum error and other measured indicators were used as output indicators to train neural networks and to obtain network weights.The accuracy of the spindle revolution of the machine tool was verified.The experimental result shows that the prediction deviation of the training network is 05%.The error prediction results considering machine tool body accuracy and machining parameters can be used to instruct machine tool selection,engineering technicians can select the optimal machining method according to different machining requirements, to improve the machining quality.

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陆兴华,张忠海.融合机床加工特性的主轴回转误差预测[J].机床与液压,2019,47(20):33-37.
. Spindle Rotation Error Prediction Based on Fusion of Machining Characteristics[J]. Machine Tool & Hydraulics,2019,47(20):33-37

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  • 在线发布日期: 2020-03-12
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