# Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria

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## 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

_{measured}and standard time T

_{standard}denoted by Δt = T

_{standard}− T

_{measured}, which is obtained from the proposed, the Kurz, and the TKEO methods, as well as the high-order statistics method under experimental conditions of 10, 5, and 0 dB, respectively. The abscissa denotes t Δt, and the ordinate denotes the number of each Δt in Figure 7, Figure 8 and Figure 9.

#### 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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**Figure 2.**Influence of noise on an echo signal: (

**a**) an echo signal with noise; (

**b**) the signal frequency spectrum.

**Figure 6.**Hardware comprising experimental platform: (

**a**) anemometer in wind tunnel; (

**b**) sensor positions; (

**c**) overall structure of experimental anemometer.

**Figure 7.**Distribution of deviation in the environment of 10 dB: (

**a**) proposed, (

**b**) Kurz, (

**c**) TKEO, and (

**d**) high-order statistics methods.

**Figure 8.**Distribution of deviation in the environment of 5 dB: (

**a**) proposed, (

**b**) Kurz, (

**c**) TKEO, and (

**d**) high-order statistics methods.

**Figure 9.**Distribution of deviation in the environment of 0 dB: (

**a**) proposed, (

**b**) Kurz, (

**c**) TKEO, and (

**d**) high-order statistics methods.

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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**MDPI and ACS Style**

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

**AMA Style**

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 Style**

Zhang, 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