Estimation of Flow Turbulence Metrics With a Lateral Line Probe and Regression

被引:17
作者
Chen, Ke [1 ]
Tuhtan, Jeffrey A. [2 ,3 ]
Fuentes-Perez, Juan Fran [2 ]
Toming, Gert [2 ]
Musall, Mark [4 ]
Strokina, Nataliya [1 ]
Kamarianen, Joni-Kristian [1 ]
Kruusmaa, Maarja [2 ]
机构
[1] Tampere Univ Technol, Dept Signal Proc, Tampere 33720, Finland
[2] Tallinn Univ Technol, Ctr Biorobot, EE-12616 Tallinn, Estonia
[3] SJE Ecohydraul Engn GmbH, D-70569 Stuttgart, Germany
[4] Karlsruhe Inst Technol, Inst Water & River Basin Management, D-76131 Karlsruhe, Germany
基金
芬兰科学院;
关键词
Artificial lateral line; bioinspired flow sensing; regression analysis; turbulence; turbulence intensity; DOPPLER VELOCIMETRY; VELOCITY; AGE;
D O I
10.1109/TIM.2017.2658278
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The time-averaged velocity of water flow is the most commonly measured metric for both laboratory and field applications. Its employment in scientific and engineering studies often leads to an oversimplification of the underlying flow physics. In reality, complex flows are ubiquitous, and commonly arise from fluid-body interactions with man-made structures, such as bridges as well as from natural flows along rocky river beds. Studying flows outside of laboratory conditions requires more detailed information in addition to time-averaged flow properties. The choice of in situ measuring device capable of delivering turbulence metrics is determined based on site accessibility, the required measuring period, and overall flow complexity. Current devices are suitable for measuring turbulence under controlled laboratory conditions, and thus there remains a technology gap for turbulence measurement in the field. In this paper, we show how a bioinspired fish-shaped probe outfitted with an artificial lateral line can be utilized to measure turbulence metrics under challenging conditions. The device and proposed signal processing methods are experimentally validated in a scale vertical slot fishway, which represents an extreme turbulent environment, such as those commonly encountered in the field. Optimal performance is achieved after 10 s of sampling using a standard deviation feature.
引用
收藏
页码:651 / 660
页数:10
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