TY - GEN
T1 - Fault diagnosis of rolling bearing based on time and frequency domain analysis and EMD
AU - Zhu, Liandie
AU - Dai, Wei
AU - Luo, Guixiu
AU - Du, Rui
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Prognostic and health management (PHM) technology is the use of a large amount of condition monitoring data and information, with the help of all kinds of fault model and artificial intelligence algorithms monitoring, diagnosis, prediction and management of the health status of the equipment technology, by predicting the problems and reliable working life, improving the safety of equipment, minimizing the fault effect, this article in rolling bearing, using Labview software construction time domain analysis program, the analysis of three kinds of condition from different perspective (35Hz12KN/37.5Hz11KN/40HZ10KN)under the rolling bearing, Finally, Matlab software was used for frequency domain analysis and empirical mode decomposition (EMD), and the inherent modal function and vibration signal spectrum were extracted to find out the fault characteristic frequency band, which provided a basis for bearing fault diagnosis under different loads.
AB - Prognostic and health management (PHM) technology is the use of a large amount of condition monitoring data and information, with the help of all kinds of fault model and artificial intelligence algorithms monitoring, diagnosis, prediction and management of the health status of the equipment technology, by predicting the problems and reliable working life, improving the safety of equipment, minimizing the fault effect, this article in rolling bearing, using Labview software construction time domain analysis program, the analysis of three kinds of condition from different perspective (35Hz12KN/37.5Hz11KN/40HZ10KN)under the rolling bearing, Finally, Matlab software was used for frequency domain analysis and empirical mode decomposition (EMD), and the inherent modal function and vibration signal spectrum were extracted to find out the fault characteristic frequency band, which provided a basis for bearing fault diagnosis under different loads.
KW - Empirical Mode Decomposition
KW - Frequency domain analysis
KW - PHM
KW - Time domain analysis
KW - component
KW - feature extraction(key words)
UR - https://www.scopus.com/pages/publications/85078029346
U2 - 10.1109/PHM-Qingdao46334.2019.8942926
DO - 10.1109/PHM-Qingdao46334.2019.8942926
M3 - 会议稿件
AN - SCOPUS:85078029346
T3 - 2019 Prognostics and System Health Management Conference, PHM-Qingdao 2019
BT - 2019 Prognostics and System Health Management Conference, PHAI-Qingdao 2019
A2 - Guo, Wei
A2 - Li, Steven
A2 - Miao, Qiang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th Prognostics and System Health Management Conference, PHM-Qingdao 2019
Y2 - 25 October 2019 through 27 October 2019
ER -