小波
稳健性(进化)
小波包分解
算法
时域
计算机科学
小波变换
数学
人工智能
计算机视觉
生物化学
基因
化学
作者
Matthias Bächle,Daniel Schwär,Fernando Puente León
出处
期刊:Tm-technisches Messen
[R. Oldenbourg Verlag]
日期:2019-09-26
卷期号:87 (1): 45-54
被引量:2
标识
DOI:10.1515/teme-2019-0093
摘要
Abstract A key element in robust transit-time ultrasonic flow measurement is the accurate estimation of the transit-time difference. Conventional methods, such as cross-correlation or the estimation in the phase domain, are limited in their robustness against signal distortions, interfering signals or noise. In this work, we present a novel method to estimate the transit-time difference through the fusion of selected analytic wavelet packet coefficients. The combination of the complex coefficients, which represent a projection of the signal on analytic wavelets, with a configurable time-frequency resolution allows a sub-sample estimation at the frequency of interest. After giving an introduction into the fundamentals of analytic wavelet packets based on multi-scale filtering, we introduce two features that correlate strongly with the transit-time difference. The selection and fusion of these features is done by using correlation coefficients with a calibration set and principal component analysis. Finally, using a clamp-on flow measurement system, the robustness against temperature variation and measurement noise is shown and compared with conventional methods.
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