Soil type characterization for moisture estimation using machine learning and UWB-Time of Flight measurements

Measurement ◽  
2019 ◽  
Vol 146 ◽  
pp. 537-543 ◽  
Author(s):  
Marko Malajner ◽  
Dusan Gleich ◽  
Peter Planinsic
Keyword(s):  
Machine Learning ◽  
Soil Type ◽  
Time Of Flight ◽  
Moisture Estimation ◽  
Flight Measurements

scholarly journals Machine Learning Based Preprocessing to Ensure Validity of Cross-Correlated Ultrasound Signals for Time-of-Flight Measurements

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Simon Herter ◽  
Sargon Youssef ◽  
Michael M. Becker ◽  
Sarah C. L. Fischer
Keyword(s):  
Machine Learning ◽  
High Precision ◽  
Cross Correlation ◽  
Complex Structure ◽  
Time Of Flight ◽  
Industrial Applications ◽  
Ultrasonic Signals ◽  
Ultrasonic Time ◽  
Flight Measurement ◽  
Flight Measurements

AbstractHigh precision ultrasonic time-of-flight measurement is a well known part of non-destructive evaluation used in many scientific and industrial applications, for example stress evaluation or defect detection. Although ultrasonic time-of-flight measurements are widely used there are some limitations where high noise and distorted ultrasonic signals are conflicting with the demand for high precision measurements. Cross-correlation based time-of-flight measurement is one strategy to increase reliability but also exhibits some ambiguous correlation states yielding to wrong time-of-flight results. To improve the reliability of these measurements a new machine learning based approach is presented based on experimental data collected on tightened bolts. Due to the complex structure of the bolts the ultrasonic signal is influenced by boundary conditions of the geometry which lead to high number of the ambiguous cross-correlation results in practice. In this particular application, bolts are in practice evaluated discontinuously and without knowledge of the time-of-flight in the unloaded condition which prevents the use of all other available comparative preprocessing techniques to detect time-of-flight shifts. Three different preprocessing strategies were investigated based on variations in the bolting configurations to ensure a machine learning based model capable of predicting the state of the cross-correlation function for different bolting parameters. With this approach, we achieve up to 100% classification accuracy for both longitudinal and transversal ultrasonic signals under laboratory conditions. In the future the method should be extended to become more robust and be applicable in real-time for industrial applications.

High precision time-of-flight measurements of neutron resonance energies in carbon and oxygen between 3 and 30 MeV

1980 ◽  
Vol 169 (1) ◽  
pp. 185-198 ◽  
Author(s):  
S. Cierjacks ◽  
F. Hinterberger ◽  
G. Schmalz ◽  
D. Erbe ◽  
P.v. Rossen ◽  
...  
Keyword(s):  
High Precision ◽  
Time Of Flight ◽  
Neutron Resonance ◽  
Resonance Energies ◽  
Precision Time ◽  
Flight Measurements

Electronic hardware for high resolution time-of-flight measurements

1979 ◽  
Vol 30 (1) ◽  
pp. 57-62 ◽  
Author(s):  
M. Armenante ◽  
V. Santoro ◽  
N. Spinelli ◽  
F. Vanoli
Keyword(s):  
High Resolution ◽  
Time Of Flight ◽  
Resolution Time ◽  
Electronic Hardware ◽  
Flight Measurements

Time-of-flight measurements of heavy ions using Si PIN diodes

2016 ◽  
Vol 79 (9-10) ◽  
pp. 1386-1390
Author(s):  
A. O. Strekalovsky ◽  
D. V. Kamanin ◽  
Yu. V. Pyatkov ◽  
N. A. Kondratyev ◽  
V. E. Zhuchko ◽  
...  
Keyword(s):  
Heavy Ions ◽  
Time Of Flight ◽  
Pin Diodes ◽  
Flight Measurements

scholarly journals Time-of-flight measurements of charge carrier diffusion in InxGa1−xN/GaN quantum wells

2011 ◽  
Vol 84 (3) ◽  
Author(s):  
J. Danhof ◽  
U. T. Schwarz ◽  
A. Kaneta ◽  
Y. Kawakami
Keyword(s):  
Charge Carrier ◽  
Quantum Wells ◽  
Time Of Flight ◽  
Carrier Diffusion ◽  
Charge Carrier Diffusion ◽  
Flight Measurements

Time-of-flight measurements of the kinetic energies of the O2(a1Δg) fragment from the photolysis of ozone between 287 and 331 nm

1995 ◽  
Vol 245 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Stephen M. Ball ◽  
Gus Hancock ◽  
John C. Pinot de Moira ◽  
Chester M. Sadowski ◽  
Fiona Winterbottom
Keyword(s):  
Time Of Flight ◽  
Flight Measurements

Properties of waves guided by a plasma column as determined by time-of-flight measurements

1974 ◽  
Vol 16 (4) ◽  
pp. 407-412 ◽  
Author(s):  
D L Landt ◽  
H C S Hsuan ◽  
K E Lonngren
Keyword(s):  
Plasma Column ◽  
Time Of Flight ◽  
Flight Measurements

Electron time-of-flight measurements in quantum well lasers

1998 ◽  
Author(s):  
S.A. Wood ◽  
D.J. Somerford ◽  
P.M. Smowton ◽  
C.C. Button ◽  
P. Blood
Keyword(s):  
Quantum Well ◽  
Time Of Flight ◽  
Quantum Well Lasers ◽  
Flight Measurements
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