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

Abstract

The time-difference method is a common one for measuring wind speed ultrasonically, and its core is the precise arrival-time determination of the ultrasonic echo signal. However, because of background noise and different types of ultrasonic sensors, it is difficult to measure the arrival time of the echo signal accurately in practice. In this paper, a method based on the wavelet transform (WT) and Bayesian information criteria (BIC) is proposed for determining the arrival time of the echo signal. First, the time-frequency distribution of the echo signal is obtained by using the determined WT and rough arrival time. After setting up a time window around the rough arrival time point, the BIC function is calculated in the time window, and the arrival time is determined by using the BIC function. The proposed method is tested in a wind tunnel with an ultrasonic anemometer. The experimental results show that, even in the low-signal-to-noise-ratio area, the deviation between mostly measured values and preset standard values is mostly within 5 μs, and the standard deviation of measured wind speed is within 0.2 m/s.

A New Wearable System for Sensing Outdoor Environmental Conditions for Monitoring Hyper-Microclimate

“…MEMS are significantly smaller than traditional hygrometers and have integrated amplification and analogue-to-digital convertor (ADC) circuitry [62]. The wind speed is frequently measured with ultrasonic anemometers, which have the advantages of no mechanical structure, no start-up wind speed limitation, and a wide measurement range regarding mechanical and pitot-tube anemometers [63].…”

Reversible Information of Encrypted Image Based on Feature Difference Detection and Wavelet Transform

“…Zhang designed the image encryption technology based on row and column transformation, formed the row and column transformation engine by iterative Logistic mapping, and built the corresponding encryption mechanism to complete the encryption of the input image. Experimental results show that the algorithm has ideal encryption speed and security [ 6 ]. Nasrallah N. Min Ming designed the image encryption technology based on the wavelet transmission and chaotic system.…”

A Study on Determining Time-Of-Flight Difference of Overlapping Ultrasonic Signal: Wave-Transform Network

“…In terms of the single ultrasonic echo signal, research on TOF has been carried out by researchers around the world who have created plenty of methods to tackle the issue. All existing methods can be roughly divided into two categories corresponding to the mathematical model including model-based estimation of ultrasonic echoes [ 16 ]; Kalman filtering for TOF Estimation [ 17 ]; echo signal envelope [ 18 ], etc., and to energy distribution including peak-value; information criteria [ 19 , 20 ]; higher-order statistics method [ 21 ]; Teager–Kaiser energy operator (TKEO) [ 22 ], etc.…”

“…In terms of the single ultrasonic echo signal, research on TOF has been carried out by researchers around the world who have created plenty of methods to tackle the issue. All existing methods can be roughly divided into two categories corresponding to the mathematical model including model-based estimation of ultrasonic echoes [16]; Kalman filtering for TOF Estimation [17]; echo signal envelope [18], etc., and to energy distribution including peak-value; information criteria [19,20]; higher-order statistics method [21]; Teager-Kaiser energy operator (TKEO) [22], etc. With the recent surge in developments of deep learning, audio signal processing has adopted this method to extensively tackle problems that were difficult to solve in the past, such as source separation, audio enhancement, and generative models for speech, sound, and music synthesis [23].…”