伺服加载系统的摩擦预测模型研究

Research on Friction Prediction Model of Servo Loading System

摘要: 针对伺服加载系统中摩擦力矩对测量精度的影响，提出了一种考虑速度与压力双变量影响的摩擦力矩预测建模方法。首先，通过实验平台采集了主轴在不同速度与加载压力条件下的扭矩响应数据，基于传统Stribeck摩擦模型，提出了带压力影响项的改进模型，并结合遗传算法进行参数辨识，最后采用最小二乘法进行精确逼近。实验结果表明，该模型在中、高速区间都具有较好的拟合精度，模型预测值与实测数据的最大相对误差在3.5%以内，能有效描述实际摩擦力矩变化趋势，并在实际工程应用中具有较高的建模精度。

Abstract: Aiming at the influence of friction torque on measurement accuracy in servo loading systems, a friction torque prediction modeling method considering both velocity and pressure effects is proposed. Firstly, torque response data of the spindle under different velocity and loading pressure conditions were collected through an experimental platform. Based on the traditional Stribeck friction model, an improved model with pressure influence terms was established, and the parameters were identified using a genetic algorithm. Finally, the least squares method was applied for accurate approximation. Experimental results show that the proposed model achieves good fitting accuracy in both medium- and high-speed ranges, with the maximum relative error between the predicted and measured values within 3.5%. The model can effectively describe the actual variation trend of friction torque and has high modeling accuracy in engineering applications.