Sgarabotto, A.; Manzella, I.; Raby, A.
Smart sensor data from tracking a single wooden dowel travelling along a flume in laboratory experiments
https://doi.org/10.5285/11b69869-90db-4deb-8ec2-a78f6bb0ea24
Cite this dataset as:
Sgarabotto, A.; Manzella, I.; Raby, A. (2023). Smart sensor data from tracking a single wooden dowel travelling along a flume in laboratory experiments. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/11b69869-90db-4deb-8ec2-a78f6bb0ea24
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This dataset is available under the terms of the Open Government Licence
This dataset contains measurements from smart sensors and cameras monitoring the movement of a single wooden dowel moving downstream in a flume. The following values in the x, y, and z directions are provided: velocity, linear acceleration, angular velocity, and filtered angular velocity. The quaternion components are also included. Four uniform flow conditions were tested, and the experiments were repeated about 50 times.
Publication date: 2023-11-14
View numbers valid from 14 November 2023 Download numbers valid from 20 June 2024 (information prior to this was not collected)
Format
Comma-separated values (CSV)
Provenance & quality
The wooden dowel was hollow, and a sensor equipped with an accelerometer, a gyroscope, and a magnetometer was installed within the longitudinal borehole of the wooden dowel. The experiments were recorded above by two cameras (GoPro HERO4 Silver) with a 2.7K resolution and a frame rate of 30 fps. The accelerometer and gyroscope had an acquisition frequency set at 14.9 Hz, whereas the magnetometer recorded at 5 Hz.
The data were processed and saved in CSV files, one for each flow condition and each experiment. First, the cameras were calibrated and the images were rectified. Then, each sensor was calibrated and the orientation angles were computed. The gravity effects were compensated for to compute the linear acceleration. Lastly, a linear Kalman filter was used to computer more reliable linear acceleration, velocity and position values. More details are available in the ReadMe.docx.
The data were processed and saved in CSV files, one for each flow condition and each experiment. First, the cameras were calibrated and the images were rectified. Then, each sensor was calibrated and the orientation angles were computed. The gravity effects were compensated for to compute the linear acceleration. Lastly, a linear Kalman filter was used to computer more reliable linear acceleration, velocity and position values. More details are available in the ReadMe.docx.
Licensing and constraints
This dataset is available under the terms of the Open Government Licence
Cite this dataset as:
Sgarabotto, A.; Manzella, I.; Raby, A. (2023). Smart sensor data from tracking a single wooden dowel travelling along a flume in laboratory experiments. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/11b69869-90db-4deb-8ec2-a78f6bb0ea24
Related
This dataset is included in the following collections
Correspondence/contact details
Sgarabotto, A.
University of Plymouth
Plymouth
Devon
PL4 8AA
UNITED KINGDOM
alessandro.sgarabotto@plymouth.ac.uk
Devon
PL4 8AA
UNITED KINGDOM
Authors
Other contacts
Rights holders
University of Plymouth, University of Exeter, University of East Anglia
Custodian
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Publisher
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk

https://orcid.org/0000-0002-4740-784X