基于时频分析的脉冲特征提取方法在铣刀磨损定量评价中的应用

IF 5.7 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Structural Health Monitoring-An International Journal Pub Date : 2023-09-07 DOI:10.1177/14759217231192003
MingAng Guo, Xiaotong Tu, Saqlain Abbas, Shuangmu Zhuo, Xiaolu Li
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引用次数: 0

摘要

机械系统状态监测是现代工业中的一个重要环节,它不仅降低了维护成本,而且确保了设备的安全运行。目前,基于信号处理的监测方法是最常见、最有效的故障诊断方法之一。本文利用广义水平同步压缩变换得到的时频分布(TFD)来提取刀具非平稳振动信号的脉冲特征。通过使用TFD结果,二维(2D)傅立叶变换可以进一步检测周期性脉冲。其次,提出了周期频率点的能量比例因子来评价不同刀具磨损程度。数值模拟和实验数据分析证明了所提出方法的有效性以及状态监测的潜力。
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Time-frequency analysis-based impulse feature extraction method for quantitative evaluation of milling tool wear
Mechanical system condition monitoring is an important procedure in modern industry, which not only reduces maintenance costs but also ensures safe equipment operation. At present, the monitoring method based on signal processing is one of the most common and effective fault diagnosis methods. In this work, the time-frequency distribution (TFD) obtained by generalized horizontal synchrosqueezing transform is used to extract the impulse feature of the non-stationary vibration signal of the tool. By using the TFD result, the two-dimensional (2D) Fourier transform can further detect the periodic pulses. Next, the energy proportion factor of periodic frequency point is proposed to evaluate the different tool wear degrees. Numerical simulations and experimental data analysis demonstrate the effectiveness of the proposed method as well as the potential for condition monitoring.
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来源期刊
CiteScore
12.80
自引率
12.10%
发文量
181
审稿时长
4.8 months
期刊介绍: Structural Health Monitoring is an international peer reviewed journal that publishes the highest quality original research that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.
期刊最新文献
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