Wavelet transform of vibration signal of CNC machine tool based on python

Sihan Guo; Mu Li; Xinwei Wang

doi:10.1117/12.3005949

10 October 2023 Wavelet transform of vibration signal of CNC machine tool based on python

Sihan Guo, Mu Li, Xinwei Wang

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127992F (2023) https://doi.org/10.1117/12.3005949
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

In this paper,wavelet transform of vibration signal of CNC machine tool is performed based on Python programming language.wavelet transform function in PyWavelets library,the signal is decomposed into sub-signals of different frequencies.The experimental results show that the vibration signal of CNC machine tool has multiple frequency components,and the noise reduction effect is obvious after wavelet transform of the By implementing wavelet analysis method,EMD[1],and EEMD through Python programming,the three feature extraction methods are compared,and it is concluded that wavelet transform can be more convenient for signal processing and analysis,and the analysis method and parameters Therefore,the wavelet analysis method of vibration signal of CNC machine tool based Therefore,the wavelet analysis method of vibration signal of CNC machine tool based on Python has high practicality and scalability,which can provide important support for the optimization design and machining accuracy improvement of machine tools.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Sihan Guo, Mu Li, and Xinwei Wang "Wavelet transform of vibration signal of CNC machine tool based on python", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127992F (10 October 2023); https://doi.org/10.1117/12.3005949

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available