提出了一种基于HHT的刀具状态实时监测新方法

Q3 Engineering

International Journal of Abrasive Technology Pub Date : 2019-01-01 DOI:10.1504/ijat.2019.10028319

Qizheng Liu, Guoqiang Guo, Zichao Lin, Bin Shen

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引用次数: 1

摘要

机床是信息物理系统(CPS)的主要执行单元，通过动态监测和实时感知其磨损状态来提高产品质量。为了实现对刀具磨损状态的在线信号采集和监测，实现了主轴功率信号采集系统。用切削力信号进行对比分析。引入HHT方法和小波变换方法构造刀具磨损系数，并与刀具磨损状态相对应。与小波变换相比较，证明Hilbert-Huang变换能有效抑制噪声信号，提高监测精度。最后，将新型刀具磨损监测方法应用于45#钢和钛合金TC4的钻孔中，捕捉刀具磨损状态，并利用功率信号进行全面的刀具状态在线监测。该方法在钻井试验中具有较好的准确性和实用性，具有较好的应用前景。

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A new method of real-time monitoring of cutting tool status bases on HHT

The machine tool is the main execution unit in the cyber-physical system (CPS system), which can improve the product quality by dynamic monitoring and real-time perception of its wear status. In order to realise the online signal acquisition and monitoring of tool wear status, the spindle power signal acquisition system was implemented. The cutting force signal is used as contrast analysis. The HHT method and wavelet transform method are introduced to construct the tool wear coefficients, which are corresponding to the tool wear status. Compared with the wavelet transform, it is proved that Hilbert-Huang transform can restrain the noise signal effectively and improve the accuracy of the monitoring. Finally, the new tool wear monitoring method is applied to drilling 45# steel and titanium alloy TC4 to catch the tool wear state, and the power signal is used to carry out comprehensive online tool state monitoring. It is accurate and practical in the drilling test, which shows prospective usage in the near future.

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来源期刊

International Journal of Abrasive Technology Engineering-Industrial and Manufacturing Engineering

CiteScore

0.90

自引率

0.00%

发文量