A detection method of gear micro-cracks based on tuned resonance

被引:8
|
作者
Li, Rui [1 ]
Cui, Xiaoling [1 ]
Zhao, Yang [2 ]
Feng, Xu [2 ]
Dong, Jikun [1 ]
机构
[1] Beijing Univ Technol, Beijing Engn Res Ctr Precis Measurement Technol &, Beijing, Peoples R China
[2] Acad Space Technol, Beijing Inst Spacecraft Syst Engn, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Feature extraction; Empirical mode decomposition; Tuning resonance; Modal frequency; Gear defect detection; ARTIFICIAL NEURAL-NETWORK; WAVELET TRANSFORM; FAULT;
D O I
10.1016/j.measurement.2021.110112
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Detection of micro-cracks before assembling has always been a challenge in gear defect detection. A mature detection method of micro-cracks is not available. Due to the complex detection environment and large production of gears, it's urgent to develop a rapid and accurate detection method of gear micro-cracks. It's the key to separate and extract weak vibration signals accurately under complex disturbances in gear defect detection. In this study, vibration characteristics of gear defects under resonance conditions were firstly explored and a detection method of gear micro-cracks was proposed based on tuned resonance. Based on the amplification effect of tuned resonance on the peak frequency spectrum of gear vibration, meshing frequency and sideband frequency characteristics of the gear defect signal spectrum were experimentally investigated. The amplitudes of gear meshing frequency and its harmonic meshing frequency in the signal frequency domain diagram were higher and the surrounding sideband frequency components were clearer.
引用
收藏
页数:10
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