Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine

José María Muñoz-Ferreras; Zhengyu Peng; Yao Tang; Roberto Gómez-García; Changzhi Li

doi:10.1109/WISNET.2017.7878741

Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine

José María Muñoz-Ferreras, Zhengyu Peng, Yao Tang, Roberto Gómez-García, Changzhi Li

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5-7
Number of pages	3
ISBN (Electronic)	9781509034604
DOIs	https://doi.org/10.1109/WISNET.2017.7878741
State	Published - Mar 14 2017
Event	2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017 - Phoenix, United States Duration: Jan 15 2017 → Jan 18 2017

Publication series

Name	Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017

Conference

Conference	2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017
Country/Territory	United States
City	Phoenix
Period	01/15/17 → 01/18/17

Keywords

Doppler radars
Structural health monitoring (SHM)
Wind turbines
Wireless sensors

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10.1109/WISNET.2017.7878741

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Muñoz-Ferreras, J. M., Peng, Z., Tang, Y., Gómez-García, R., & Li, C. (2017). Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine. In Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017 (pp. 5-7). [7878741] (Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WISNET.2017.7878741

Muñoz-Ferreras, José María ; Peng, Zhengyu ; Tang, Yao et al. / Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine. Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 5-7 (Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017).

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title = "Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine",

abstract = "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.",

keywords = "Doppler radars, Structural health monitoring (SHM), Wind turbines, Wireless sensors",

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Muñoz-Ferreras, JM, Peng, Z, Tang, Y, Gómez-García, R & Li, C 2017, Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine. in Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017., 7878741, Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017, Institute of Electrical and Electronics Engineers Inc., pp. 5-7, 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017, Phoenix, United States, 01/15/17. https://doi.org/10.1109/WISNET.2017.7878741

Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine. / Muñoz-Ferreras, José María; Peng, Zhengyu; Tang, Yao et al.

Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 5-7 7878741 (Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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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

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.

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KW - Structural health monitoring (SHM)

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KW - Wireless sensors

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M3 - Conference contribution

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T3 - Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017

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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

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Muñoz-Ferreras JM, Peng Z, Tang Y, Gómez-García R, Li C. Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine. In Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 5-7. 7878741. (Proceedings - 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNet 2017). doi: 10.1109/WISNET.2017.7878741

Doppler-radar-based short-range acquisitions of time-frequency signatures from an industrial-type wind turbine

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