Temperature and Consolidation Sensing Near Drinking Water Wells Using Fiber Bragg Grating Sensors
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Site and Sensor Installation
- FBG sensors: consolidation and temperature
- reference divers: pressure and temperature
- weather station: atmospheric pressure
- flowmeter: horizontal flowrate in well
- status of 12 wells: on/off
2.2. Pressure Sensing
2.3. Consolidation Models and Temperature Sensing
- —time shifted output values
- —time shifted input values
- —error term
- —model coefficients
- —backward time shift in the output
- —backward time shift in the input
- —number of input samples that occur before the input affects the output, also called the dead time in the system.
- and
- .
3. Results and Discussion
3.1. Pressure (FBG Sensors vs. Divers)
3.2. Consolidation Models
3.3. Temperature (FBG Sensors)
3.4. Temperature (FBG Sensors vs. Divers)
3.5. Temperature (FBG Sensors vs. Well Flowrate)
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Output | Input Well | ||
---|---|---|---|
na | 6 | ||
nb | 8 | 2 | |
nk | 0 | 1 |
Depth (m) | 17.0 | 17.7 | 18.4 | 19.1 | 19.8 | 20.5 | 21.2 | 21.9 | |
A | RMSE training (%) | 88.4 | 94.0 | 94.6 | 92.1 | 73.7 | 89.8 | 90.7 | 94.5 |
RMSE validation (%) | 86.8 | 91.8 | 92.7 | 89.4 | 71.8 | 86.5 | 88.2 | 92.0 | |
B | RMSE training (%) | 92.7 | 91.2 | 96.7 | 96.5 | 90.9 | 91.4 | 91.8 | 35.1 |
RMSE validation (%) | 80.9 | 75.1 | 89.2 | 86.7 | 79.5 | 75.8 | −111.9 | 1.1 | |
Depth (m) | 22.6 | 23.3 | 24.0 | 24.7 | 25.4 | 26.1 | 26.8 | 27.5 | |
A | RMSE training (%) | 94.1 | 94.6 | 89.0 | 92.3 | 92.8 | 95.0 | 94.0 | 88.5 |
RMSE validation (%) | 92.4 | 92.2 | 89.1 | 87.3 | 90.2 | 91.5 | 91.6 | 86.7 | |
B | RMSE training (%) | 89.5 | 89.6 | 86.7 | 93.2 | 96.0 | 35.4 | 69.4 | 85.5 |
RMSE validation (%) | 87.0 | 72.8 | 76.3 | 78.0 | 91.5 | 0.7 | 22.8 | 76.6 | |
Depth (m) | 28.2 | 28.9 | 29.6 | 30.3 | 31.0 | 31.7 | 32.4 | 33.1 | |
A | RMSE training (%) | 95.1 | 96.4 | 94.7 | 89.4 | 92.7 | 87.7 | 92.1 | 89.5 |
RMSE validation (%) | 93.5 | 92.5 | 93.0 | 90.4 | 89.8 | 82.1 | 88.5 | 86.3 | |
B | RMSE training (%) | 96.3 | 96.5 | 95.6 | 94.4 | 90.0 | 94.0 | 90.1 | 87.7 |
RMSE validation (%) | 93.2 | 93.0 | 91.9 | 89.1 | 77.2 | 80.6 | 71.9 | 80.82 |
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Drusová, S.; Wagterveld, R.M.; Keesman, K.J.; Offerhaus, H.L. Temperature and Consolidation Sensing Near Drinking Water Wells Using Fiber Bragg Grating Sensors. Water 2020, 12, 3572. https://doi.org/10.3390/w12123572
Drusová S, Wagterveld RM, Keesman KJ, Offerhaus HL. Temperature and Consolidation Sensing Near Drinking Water Wells Using Fiber Bragg Grating Sensors. Water. 2020; 12(12):3572. https://doi.org/10.3390/w12123572
Chicago/Turabian StyleDrusová, Sandra, R. Martijn Wagterveld, Karel J. Keesman, and Herman L. Offerhaus. 2020. "Temperature and Consolidation Sensing Near Drinking Water Wells Using Fiber Bragg Grating Sensors" Water 12, no. 12: 3572. https://doi.org/10.3390/w12123572