TY - GEN
T1 - Modeling and analyzing low frequency noise of offshore wind turbines with acoustics vector sensors
AU - Zhu, Jiannan
AU - Comesana, Daniel Fernandez
AU - Yang, Yixin
AU - Yang, Long
AU - Feng, Miao
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/28
Y1 - 2016/11/28
N2 - Low frequency noise is the main noise sources of wind turbine, causing annoyance for daily life. This paper proposes a simplified model for wind turbine low frequency noise sources through three elements: noise sources, propagation paths and perceived signals of acoustic vector sensors(AVS) array. AVS array is utilized for far field source localization, offering a key advantage with respect to conventional acoustic pressure solutions due to their vector nature. Due to doppler effects, time-dependent Green functions are hereby used to extract information about the physical characteristic of different elements. Two time domain beamforming methods (de-dopplerized and conventional method) are utilized for locating the model noise rotational sources with AVS array, along with several simulations and their performance analysis in different situations. The results show that de-dopplerized method outperform than the conventional method.
AB - Low frequency noise is the main noise sources of wind turbine, causing annoyance for daily life. This paper proposes a simplified model for wind turbine low frequency noise sources through three elements: noise sources, propagation paths and perceived signals of acoustic vector sensors(AVS) array. AVS array is utilized for far field source localization, offering a key advantage with respect to conventional acoustic pressure solutions due to their vector nature. Due to doppler effects, time-dependent Green functions are hereby used to extract information about the physical characteristic of different elements. Two time domain beamforming methods (de-dopplerized and conventional method) are utilized for locating the model noise rotational sources with AVS array, along with several simulations and their performance analysis in different situations. The results show that de-dopplerized method outperform than the conventional method.
KW - Acoustic Vector Sensor(AVS)
KW - Green function
KW - Low frequency
KW - Noise sources
KW - Time domain beamforming
KW - Wind turbine
UR - https://www.scopus.com/pages/publications/85006847221
U2 - 10.1109/OCEANS.2016.7761301
DO - 10.1109/OCEANS.2016.7761301
M3 - 会议稿件
AN - SCOPUS:85006847221
T3 - OCEANS 2016 MTS/IEEE Monterey, OCE 2016
BT - OCEANS 2016 MTS/IEEE Monterey, OCE 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 OCEANS MTS/IEEE Monterey, OCE 2016
Y2 - 19 September 2016 through 23 September 2016
ER -