基于振动信号的深孔钻削涡振在线检测方法研究*
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中图分类号TG806TH165+.4 文献标识码A国家标准学科分类代码: 46050

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*基金项目:基金项目国家自然科学基金(51905421)、中国博士后科学基金(2019M653880XB)、陕西省教育厅自然科学专项(19JK0586)资助


An online whirl detection method in deep hole drilling based on vibration signal
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    摘要:

    摘要:摘要涡振是深孔钻削中极易出现的刀具异常振动形式之一。深孔钻削中刀具系统的涡振将导致深孔圆度超差,甚至损坏刀具和孔壁。因此,实时监测深孔钻削状态、辨识刀具系统涡振,对及时抑制刀具系统涡振、提高深孔加工质量具有重要意义。提出一种基于主轴振动信号的深孔钻削中涡振在线检测方法。首先,对实时采集的主轴振动信号进行经验小波变换分解,提取主轴转频的高倍频信号;其次,计算所提取高倍频信号的能量比,作为监测指标;最后,依据监测指标实时辨识刀具系统涡振。实验结果表明,所提检测方法可有效识别深孔加工中导致孔圆度误差大于035mm的刀具系统涡振缺陷。

    Abstract:

    Abstract:Whirling is one kind of abnormal vibration in deep hole drilling. During the drilling process, it may enlarge the roundness error, and even damage the tool and hole wall. Thus, it is important to monitor the drilling condition and identify the whirling timely. To be specific, the whirling shouldbe suppressedtimelyand thequality ofdeep hole machining should be improved. In thisstudy, anonlinewhirlingdetectionmethodin deep holedrillingisproposedbased onvibrationsignal.Firstly,thevibration signal isdecomposedby empirical wavelet transform, and the high multiple frequency components of spindle rotation are extracted. Secondly, the energy ratio between the extracted component and the original signal is calculated. Finally, the energy ratio is viewed as the detection index to identify the tool condition. The proposed method is evaluated with BTA deephole drilling tests. Experimental results show that the proposed method can effectively identify the whirling which lead to the roundness error that is larger than 0035 mm during the deep hole drilling.

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思悦,孔令飞,李旭阳,郑建明,李淑娟.基于振动信号的深孔钻削涡振在线检测方法研究*[J].仪器仪表学报,2020,41(6):250-256

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  • 在线发布日期: 2022-03-01
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