Adaptive model estimation of machine-tool thermal errors based on recursive dynamic modeling strategy
Adaptive model estimation of machine-tool thermal errors based on recursive dynamic modeling strategy
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DOI：
10.1016/j.ijmachtools.2004.06.023
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发表时间：
2005
影响因子：
14
通讯作者：
Hong Yang;J. Ni
中科院分区：
文献类型：
--
作者：
Hong Yang;J. Ni
一个系统的模型自适应方法的开发，以不断更新的热误差模型在不同的制造条件下。过程间歇探测和自适应系统识别技术被集成到监测和估计机床的热误差和递归地修改模型系数作为制造过程的进行。递归模型自适应，这是基于卡尔曼滤波器参数估计技术和多重采样范围，最大限度地减少对生产的干扰，同时保持良好的模型自适应能力。实验结果表明，该方法具有良好的模型精度和鲁棒性频繁变化的工作条件。
A systematic model adaptation methodology is developed in order to continuously update the thermal-error model under varying manufacturing conditions. Process-intermittent probing and adaptive system identification techniques are integrated to monitor and estimate machine-tool thermal errors and recursively modify model coefficients as manufacturing process proceeds. The recursive model adaptation, which is based on the Kalman filter parameter estimation technique and multiple-sampling horizons, minimizes intrusion to production while maintaining good model adaptation capability. The experimental results proved that the proposed methodology has good model accuracy and robustness to frequently changing working conditions.