2020
DOI: 10.1080/00221686.2020.1844810
|View full text |Cite
|
Sign up to set email alerts
|

Turbulent free-surface monitoring with an RGB-D sensor: the hydraulic jump case

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
9
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
8

Relationship

2
6

Authors

Journals

citations
Cited by 18 publications
(9 citation statements)
references
References 30 publications
0
9
0
Order By: Relevance
“…According to Bung et al (2021), an Intel® RealSense™ D435 depth camera was used to survey the downstream bed topography at equilibrium (±1.0 mm accuracy operated within 0.6 m and 0.8 m range). This camera includes active stereoscopy via two infrared cameras and an RGB camera.…”
Section: Methodsmentioning
confidence: 99%
“…According to Bung et al (2021), an Intel® RealSense™ D435 depth camera was used to survey the downstream bed topography at equilibrium (±1.0 mm accuracy operated within 0.6 m and 0.8 m range). This camera includes active stereoscopy via two infrared cameras and an RGB camera.…”
Section: Methodsmentioning
confidence: 99%
“…Hydraulic structure design more often than not involves highly turbulent and aerated flows where seeding particles cannot be implemented and thus requires the development of methods that rely on naturally occurring visual features such as bubbles and droplets. A recent study by Bung et al [ 77 ] employed an RGB-D camera for monitoring and characterizing a highly aerated hydraulic jump using two different methods to calibrate depth estimations (both leading to similar results). The method was able to measure 3D surfaces with high temporal and spatial resolution, although the result evaluation of measurement accuracy was somewhat limited as it was only performed using two-dimensional flow edge position data at channel walls.…”
Section: Methods For Measuring Free Water Surfacementioning
confidence: 99%
“…To determine equilibrium morphology, the substrate was scanned with an Intel® Re-alSense TM D435 depth camera (accuracy of ±1 mm) (Intel, Santa Clara, CA, USA) [30,39,40] processed with a Utah State University (USU) custom MATLAB (vR2020) script. The camera data was cross-checked with point measurements taken on a grid layout with a point gage assembly (accuracy of ±1 mm).…”
Section: Methodsmentioning
confidence: 99%