西安交通大学机械工程学院,西安,710049
网络首发:2013-05-10,
纸质出版:2013
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赵飞 1, 梅雪松 1, 姜歌东 1, 等. 数控机床进给系统模态参数的自激振辨识方法[J]. 西安交通大学学报, 2013,47(5):88-92.
Research on the Self-Excitation and Identification Method of Modal Parameter of Feed System of Numerical Control Machine Tool[J]. 2013, 47(5): 88-92.
赵飞 1, 梅雪松 1, 姜歌东 1, 等. 数控机床进给系统模态参数的自激振辨识方法[J]. 西安交通大学学报, 2013,47(5):88-92. DOI: 10.7652/xjtuxb201305016.
Research on the Self-Excitation and Identification Method of Modal Parameter of Feed System of Numerical Control Machine Tool[J]. 2013, 47(5): 88-92. DOI: 10.7652/xjtuxb201305016.
为实现数控机床模态参数的现场辨识
提出了数控机床进给系统模态参数的快速自激辨识方法。利用G代码小线段编程方法
实现了数控机床进给系统振动的激励
并通过内置传感器信号(光栅、编码器、电流)采集了进给系统的振动信息。采用ARMA模型的响应信号模态参数辨识方法分析内置传感器信息
得到了进给系统轴向和扭转振动的模态参数。试验表明
所提出的模态参数辨识方法可使激振过程更为方便
采用的内置传感器信号减少了对传感器布置的限制
从而提高了现场试验模态的效率
可以比较准确地辨识出进给系统的一阶固有频率。
To implement the modal test conveniently in industry scene
a self-excitation and identification method is proposed following built-in sensor signal test technology and autoregressive moving average model(ARMA)parameter identification. The vibration of feed system is evoked by the planning the trajectory of motion using small step G code programming method
the response information is contained in the built in signal
and ARMA serves to identify parameter based on the response signal. The experiment results show that the proposed method simplifies the experiment process
reduces the sensor layout restrictions
and identifies the first modal frequency accurately.
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