TY - GEN
T1 - Fault diagnosis of wind turbine using local mean decomposition and synchrosqueezing transforms
AU - Guo, Yanjie
AU - Chen, Xuefeng
AU - Wang, Shibin
AU - Li, Xiang
AU - Liu, Ruonan
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/22
Y1 - 2016/7/22
N2 - Wind turbine is driven by natural wind, thus the vibration signal of gearbox is influenced and performs with nature of non-stationary and noisy. In order to analyze the variable speed signal, time-frequency representation is introduced as a powerful tool. The synchrosqueezing transform is a useful time-frequency representation method in many situation but can not restrain noise in high noise background. And local mean decomposition can decompose noise from the signal and remain the character of signals. In this paper, we proposed a new method for fault diagnosis of wind turbine with help of synchrosqueezing transform and local mean decomposition, which can denoise and represent the frequency of signals changing with time. This method is validated by simulated signals and experimental field test. The results showed the proposed method can restrain the noise and decrease the inaccuracy of time-frequency representation.
AB - Wind turbine is driven by natural wind, thus the vibration signal of gearbox is influenced and performs with nature of non-stationary and noisy. In order to analyze the variable speed signal, time-frequency representation is introduced as a powerful tool. The synchrosqueezing transform is a useful time-frequency representation method in many situation but can not restrain noise in high noise background. And local mean decomposition can decompose noise from the signal and remain the character of signals. In this paper, we proposed a new method for fault diagnosis of wind turbine with help of synchrosqueezing transform and local mean decomposition, which can denoise and represent the frequency of signals changing with time. This method is validated by simulated signals and experimental field test. The results showed the proposed method can restrain the noise and decrease the inaccuracy of time-frequency representation.
KW - SNR
KW - local mean decomposition
KW - synchrosqueezing transform
KW - varibale speed signal
KW - wind turbine gearbox vibration
UR - https://www.scopus.com/pages/publications/84980325755
U2 - 10.1109/I2MTC.2016.7520584
DO - 10.1109/I2MTC.2016.7520584
M3 - 会议稿件
AN - SCOPUS:84980325755
T3 - Conference Record - IEEE Instrumentation and Measurement Technology Conference
BT - I2MTC 2016 - 2016 IEEE International Instrumentation and Measurement Technology Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2016
Y2 - 23 May 2016 through 26 May 2016
ER -