Smartstones: A small 9-axis sensor implanted in stones to track their movements

The movement of stones is important in a variety of disciplines such as geomorphology or hydraulic engineering. Plenty of different sensors, visual, active or passive tracers exist to capture movements in various ways. However, none of them is sufficiently small to be implanted in pebbles with a lon...

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Veröffentlicht in:Catena (Giessen) 2016-07, Vol.142, p.245-251
Hauptverfasser: Gronz, Oliver, Hiller, Priska H., Wirtz, Stefan, Becker, Kerstin, Iserloh, Thomas, Seeger, Manuel, Brings, Christine, Aberle, Jochen, Casper, Markus C., Ries, Johannes B.
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Sprache:eng
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Zusammenfassung:The movement of stones is important in a variety of disciplines such as geomorphology or hydraulic engineering. Plenty of different sensors, visual, active or passive tracers exist to capture movements in various ways. However, none of them is sufficiently small to be implanted in pebbles with a longest axis of approx. 60mm. In this article, a sufficiently small probe is introduced: the Smartstone probe. It consists of a metal cylinder (diameter 8mm, length 55mm) with a flexible antenna and contains a Bosch BMX055 sensor composed of a triaxial accelerometer, magnetometer and gyroscope, respectively. Additional components inside the probe are memory to store data, active RFID (Radio-frequency identification) technique to transmit data and two button cells as power supply. Mounted into a pebble, the applicability of this probe was tested in laboratory flume experiments by determining the pebble movement using the Smartstone measurements and comparing them to the movement pattern captured by a high-speed camera. The derived orientations and positions in these test experiments resulted in deviations of 32.4% compared to the visual footage. The different reasons for deviations are noise, quantization error, integration error, orientation error and clipping. The error sources were divided with supplementary experiments resulting in mean absolute deviation (MAE) of 3.3% due to noise, quantization, and integration errors; orientation errors result in an increased MAE of 13.7% in natural environment and 21.7% in laboratory. The MAE of all experiments containing clipping was 63.2%. These deviations will be reduced in future by application of methods like Kalman filtering or Markov models, which are established in other disciplines like computer science, robotics or (pedestrian) navigation. [Display omitted] •Small probe dimensions: cylindrical, 8mm diameter, 55mm length•Contains 9-axis sensor: 3-axis magnetometer, 3-axis accelerometer, 3-axis gyroscope•Samples up to every 12ms•Additional features: memory, battery, wireless data transmission via active RFID•Allows for derivation of orientation, approximate position and impact magnitude
ISSN:0341-8162
1872-6887
DOI:10.1016/j.catena.2016.03.030