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Gear fault monitoring method based on electrostatic signal and short-time Fourier transform
Published:2023-11-27 author:WANG Kexian, LIU Ruochen, SUN Jianzhong. Browse: 267 Check PDF documents
Gear fault monitoring method based on electrostatic signal and 
short-time Fourier transform


WANG Kexian1, LIU Ruochen1, SUN Jianzhong2

(1.School of Automobile and Traffic Engineering, Jiangsu University of Technology, Changzhou 213001, China; 

2.College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)


Abstract:  Traditional vibration monitoring requires attachment to the tested object, which leads to an increase in vibration interference source excitation, causing the fault characteristics of gear vibration signals under variable operating conditions to be obscured by interference signals. In order to solve this problem, taking the meshing gear set as the research object, the advantages of electrostatic monitoring signal were analyzed, the theory of signal time-frequency analysis was deduced, and a gear fault monitoring method based on electrostatic signal and short time Fourier transform (STFT) was proposed. First of all, the mechanism of electrostatic monitoring technology was studied and a band-stop filter was designed to remove industrial frequency interference to achieve signal pre-processing work. And then, the principle of short-time Fourier plus window transformation was derived, and the time-frequency domain signal characteristics were analyzed by combining the gear vibration and electrostatic experimental data. Finally, a gear fault monitoring platform was set up and electrostatic monitoring experiments in the wear region were carried out by varying the gear revolutions and additional loads to verify the universality of electrostatic signal extraction for gear fault characteristics. The results of the experimental study show that the characteristic frequency of the gear extracted from the electrostatic signal is 309.6Hz, which is consistent with the actual meshing frequency, and the three-dimensional power spectrum density is positively correlated with the gear speed and load. Compared with the vibration signal of gears, the electrostatic signal not only contains less interference frequency bands, but also highlight different fault information by using the time-frequency power spectrum. The results show that the electrostatic signal can better obtain the status information of gears under the variable working conditions, which overcomes the shortage of traditional vibration monitoring,and the gear fault monitoring method has certain application value.

Key words: gear failures; electrostatic monitoring technology; short time Fourier transform (STFT); electrostatic sensor; variable working conditions experiment;timefrequency domain analysis; three-dimensional power spectra


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