Abstract
In laser Doppler velocimeter (LDV), calculation precision of Doppler shift is affected by noise contained in Doppler signal. In order to restrain the noise interference and improve the precision of signal processing, wavelet packet threshold denoising methods are proposed. Based on the analysis of Doppler signal, appropriate threshold function and decomposition layer number are selected. Heursure, sqtwolog, rigrsure, and minimaxi rules are adopted to get the thresholds. Processing results indicate that signal-to-noise ratio (SNR) and root mean square error (RMSE) of simulated signals with original SNR of 0 dB, 5 dB, and 10 dB in both low- and high-frequency ranges are significantly improved by wavelet packet threshold denoising. A double-beam and double-scattering LDV system is built in our laboratory. For measured signals obtained from the experimental system, the minimum relative error of denoised signal is only 0.079% (using minimaxi rule). The denoised waveforms of simulated and experimental signals are much more smooth and clear than that of original signals. Generally speaking, denoising effects of minimaxi and saqtwolog rules are better than those of heursure and rigrsure rules. As shown in the processing and analysis of simulated and experimental signals, denoising methods based on wavelet packet threshold have ability to depress the noise in laser Doppler signal and improve the precision of signal processing. Owing to its effectiveness and practicability, wavelet packet threshold denoising is a practical method for LDV signal processing.
Highlights
As having advantages as high sensitivity, high precision, wide measuring range, and noncontact measurement, the laser Doppler velocimeter (LDV) has widespread applications in industry and scientific research [1,2,3,4,5,6]
For commercial applications such as high-speed mill and fluid velocity measurement, the cost of signal processing system is limited. erefore, a complex denoising method is not applicable for LDV. e aim of our research is to find a practical, stable, reliable, and lesscomplicated noise reduction method for the laser Doppler velocimeter
The optimal parameters are determined. e main novelty of the proposed work can be summarized as follows: (1) the study of the applicability of wavelet packet denoising method to LDV signal; (2) the construction of double-beam and double-scattering experiment system; (3) the optimization of the parameters of wavelet packet threshold denoising method applied in LDV signal. e study provides a practical and reliable method for LDV signal denoising in application
Summary
As having advantages as high sensitivity, high precision, wide measuring range, and noncontact measurement, the laser Doppler velocimeter (LDV) has widespread applications in industry and scientific research [1,2,3,4,5,6]. Double-beam and double-scattering optical structure adopted in our research is mainly used for the contactless velocity measurement of solid and fluid. E aim of our research is to find a practical, stable, reliable, and lesscomplicated noise reduction method for the laser Doppler velocimeter. E time-frequency analysis method is more applicable for LDV signal denoising. The selection of parameters, such as the basis function, the number of decomposition layers, and the threshold determination method, which directly a ect the noise reduction e ect, is studied in detail through the analysis of experimental signal and the comparison of SNR and RMSE. E main novelty of the proposed work can be summarized as follows: (1) the study of the applicability of wavelet packet denoising method to LDV signal; (2) the construction of double-beam and double-scattering experiment system; (3) the optimization of the parameters of wavelet packet threshold denoising method applied in LDV signal. The optimal parameters are determined. e main novelty of the proposed work can be summarized as follows: (1) the study of the applicability of wavelet packet denoising method to LDV signal; (2) the construction of double-beam and double-scattering experiment system; (3) the optimization of the parameters of wavelet packet threshold denoising method applied in LDV signal. e study provides a practical and reliable method for LDV signal denoising in application
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