TY - GEN
T1 - Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine
AU - Muñoz-Ferreras, José María
AU - Peng, Zhengyu
AU - Tang, Yao
AU - Gómez-García, Roberto
AU - Li, Changzhi
N1 - Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/3/14
Y1 - 2017/3/14
N2 - Non-contact radar-based monitoring of large mechanical constructions is currently gaining much attention from the RF/microwave community. In particular, Doppler radars can be coherently exploited to extract spectrograms - i.e., time-Doppler maps - of industrial-type wind turbines. This work conducts short-range experiments corresponding to a 50-m-height Vestas wind turbine illuminated by two custom-designed quadrature radar prototypes operating at 5.8 and 24 GHz, respectively. It is observed that the obtained experimental radar signatures - that are shaped by flashes and quasi-sinusoidal halos - exhibit distinct characteristics depending on the acquisition geometry and the operation frequency of the radar sensor. These features might lead in the future to a radar-based non-contact monitoring solution of the structural health of industrial-type wind turbines.
AB - Non-contact radar-based monitoring of large mechanical constructions is currently gaining much attention from the RF/microwave community. In particular, Doppler radars can be coherently exploited to extract spectrograms - i.e., time-Doppler maps - of industrial-type wind turbines. This work conducts short-range experiments corresponding to a 50-m-height Vestas wind turbine illuminated by two custom-designed quadrature radar prototypes operating at 5.8 and 24 GHz, respectively. It is observed that the obtained experimental radar signatures - that are shaped by flashes and quasi-sinusoidal halos - exhibit distinct characteristics depending on the acquisition geometry and the operation frequency of the radar sensor. These features might lead in the future to a radar-based non-contact monitoring solution of the structural health of industrial-type wind turbines.
KW - Doppler radars
KW - Structural health monitoring (SHM)
KW - Wind turbines
KW - Wireless sensors
UR - http://www.scopus.com/inward/record.url?scp=85017329078&partnerID=8YFLogxK
U2 - 10.1109/WISNET.2017.7878741
DO - 10.1109/WISNET.2017.7878741
M3 - Conference contribution
AN - SCOPUS:85017329078
T3 - Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017
SP - 5
EP - 7
BT - Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 15 January 2017 through 18 January 2017
ER -