Open AccessResearch on Gear Signal Fault Diagnosis Based on Wavelet Transform Denoising
Author(s) -
Yuan Li,
Zhuojian Wang,
Zhe Li,
Hao Li
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1971/1/012074
Subject(s) - wavelet , fault (geology) , signal (programming language) , wavelet transform , noise reduction , computer science , time–frequency analysis , vibration , time domain , signal processing , frequency domain , engineering , pattern recognition (psychology) , electronic engineering , artificial intelligence , acoustics , filter (signal processing) , computer vision , digital signal processing , physics , seismology , programming language , geology
As an important part of modern machinery, gears are safe and reliable directly related to the normal operation of the mechanical system, and when the gears are abnormal, it is very important to carry out fault diagnosis in time and effectively. Wavelet transform is effective in signal time-frequency analysis and fault diagnosis. Based on the wavelet analysis method, this paper first filters and de-noises the vibration signal data of a certain type of gear, and then performs fault analysis. Time-frequency analysis of time-domain signals has a better effect on gear fault diagnosis.