Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria
Abstract
:1. Introduction
2. Method
2.1. Time-Frequency Location Analysis
2.2. Accurate Arrival-Time Determination of Echo Signal Based on BIC
3. Experiments and Results
3.1. Experimental Platform
3.2. Performance under Different Signal-To-Noise Ratios
3.3. Stability and Accuracy Tests of Wind Speed in Wind Tunnel
3.4. Discussion of Results of Wind-Speed Tests
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Wind Speed in Wind Tunnel (m/s) | Mean Measured Value (m/s) | Standard Deviation (m/s) |
---|---|---|
0 | 0.07 | 0.03 |
10 | 10.15 | 0.09 |
15 | 15.06 | 0.16 |
20 | 20.16 | 0.19 |
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Zhang, W.; Li, Z.; Gao, X.; Li, Y.; Shi, Y. Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria. Sensors 2020, 20, 269. https://doi.org/10.3390/s20010269
Zhang W, Li Z, Gao X, Li Y, Shi Y. Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria. Sensors. 2020; 20(1):269. https://doi.org/10.3390/s20010269
Chicago/Turabian StyleZhang, Wei, Zhipeng Li, Xuyang Gao, Yanjun Li, and Yibing Shi. 2020. "Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria" Sensors 20, no. 1: 269. https://doi.org/10.3390/s20010269