MingAng Guo, Xiaotong Tu, Saqlain Abbas, Shuangmu Zhuo, Xiaolu Li
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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.
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.