基于模态区间的数控机床切削状态监测
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华东交通大学机电与车辆工程学院南昌330013

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TH133TH391

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国家自然科学基金(51565015)项目资助


Cutting state monitoring of NC machine tool based on modal interval
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School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China

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    摘要:

    随着高速高精数控加工技术的发展,对数控机床切削加工状态的稳定性提出了更高的要求,传统的切削加工状态监测方法中对不确定性处理存在不足。提出了一个基于模态区间的切削状态监测不确定性处理方法,利用模态区间的宽度对传统监测方法中的不确定性加以表述,以解决监测中的不确定性问题。为了验证提出方法的有效性,搭建了切削加工实验平台,通过加速度传感器获取数控机床切削加工信息,由时频分析方法将切削状态划分成稳定、过渡及颤振3个加工阶段,利用基于模态区间的小波包能量百分比方法,提取不同加工阶段的区间特征量,通过Lloyd 算法进行编码后作为基于模态区间的广义隐马尔科夫模型的输入特征向量,最后利用广义隐马尔科夫状态辨识方法,对数据机床切削状态进行了识别。实验结果表明,基于模态区间的广义隐马尔科夫模型辨识方法优于传统的隐马尔科夫模型辨识方法。

    Abstract:

    With the development of high speed and high precision NC machining technology, high cutting stability of NC machine tool is required. The uncertainty processing is insufficient in the traditional cutting state monitoring. In this paper, an uncertainty processing method for cutting state monitoring is proposed based on modal interval theory. The uncertainty in traditional monitoring methods is described by using the width of modal interval to solve the monitoring uncertainty problem. In order to verify effectiveness of the proposed method, a cutting experimental platform is built. The cutting information of the NC machining is obtained by acceleration sensor. The cutting states are divided into three processing stages: stable, transition and chatter state by using timefrequency analysis. The interval feature of the different stages is extracted by using the wavelet packet energy percentage based on modal interval. The interval feature is encoded by Lloyd algorithm, and regarded as the input vectors of generalized hidden Markov model. Finally, the cutting stats of NC machine are identified by generalized hidden Markov model state recognition method. The experimental results show that the proposed generalized hidden Markov model recognition method based on modal interval is superior to the traditional hidden Markov model recognition method.

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谢锋云,陈红年,江炜文,谢三毛,李勇.基于模态区间的数控机床切削状态监测[J].仪器仪表学报,2017,38(12):2900-2907

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  • 在线发布日期: 2018-01-17
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