Open AccessSpindle vibration signal extraction method based on improved all phase Fast Fourier Transform
Author(s) -
Z Wang,
Sy Du,
LC Roşca
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/789/1/012066
Subject(s) - vibration , machining , signal (programming language) , fourier transform , rotor (electric) , computer science , machine tool , dynamic balance , signal processing , fast fourier transform , acoustics , control theory (sociology) , engineering , digital signal processing , artificial intelligence , mechanical engineering , algorithm , mathematics , physics , computer hardware , control (management) , programming language , mathematical analysis
In the modern processing technology, the machine tool plays an irreplaceable role as the main processing tool, and its machining accuracy directly affects the processing quality of the part. Because the spindle vibration caused by the rotor mass imbalance will seriously affect the machining accuracy of the machine tool, it is necessary to dynamically balance the spindle. The key step of dynamic balancing is to accurately extract the characteristics of the vibration signal, the phase of the vibration signal of the spindle was extracted by the all phase fast Fourier transform, the amplitude of vibration signal was extracted by cross correlation analysis, the results are applied to the influence coefficient method to realize the dynamic balance of spindle vibration The results show that the vibration signal feature extraction method combined with the results of the two extraction methods has high precision and stability.