Activities per year
Abstract
In order to generate consistent and comprehensive datasets for the application of
machine learning algorithms to MEMS thermal flow sensors, a measurement set up was created.This system allows automatic data collection of large datasets involving parameters such as the angle of attack, humidity, temperature and flow speed. The electrical output signals in both the time and frequency domain can be measured for both AC and DC actuation. The setup has been able to fully characterize an anemometer by exposing it to flows of 0 to 5 m/s in steps of 0.02 m/s under angles
from -45 to 45° in steps of 5° at a constant temperature of 25 °C and humidity of 30 %RH and complete the measurement in 8 hours.
machine learning algorithms to MEMS thermal flow sensors, a measurement set up was created.This system allows automatic data collection of large datasets involving parameters such as the angle of attack, humidity, temperature and flow speed. The electrical output signals in both the time and frequency domain can be measured for both AC and DC actuation. The setup has been able to fully characterize an anemometer by exposing it to flows of 0 to 5 m/s in steps of 0.02 m/s under angles
from -45 to 45° in steps of 5° at a constant temperature of 25 °C and humidity of 30 %RH and complete the measurement in 8 hours.
| Original language | English |
|---|---|
| Pages | 126-129 |
| Number of pages | 4 |
| Publication status | Published - 22 Feb 2024 |
| Event | 5th Conference on MicroFluidic Handling Systems, MFHS 2024 - Munich, Germany Duration: 21 Feb 2024 → 23 Feb 2024 Conference number: 5 |
Conference
| Conference | 5th Conference on MicroFluidic Handling Systems, MFHS 2024 |
|---|---|
| Abbreviated title | MFHS 2024 |
| Country/Territory | Germany |
| City | Munich |
| Period | 21/02/24 → 23/02/24 |
Keywords
- MEMS
- Machine Learning
- Thermal
- Anemometer
- Microfluidics
- Flow sensor
Fingerprint
Dive into the research topics of 'A Multi-Parameter Measurement System for MEMS Anemoters for Data Collection with Machine Learning Outcomes'. Together they form a unique fingerprint.Activities
- 1 Oral presentation
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A Machine Learning Enhanced MEMS Thermal Anemometer for Detection of Flow, Angle of Attack, and Relative Humidity
Hackett, T. (Speaker), Choi, J. Y. (Contributor), Sanders, R. G. P. (Contributor), van den Berg, T. E. (Contributor), Alveringh, D. (Contributor) & Schmitz, J. (Contributor)
23 Oct 2024Activity: Talk or presentation › Oral presentation
Prizes
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Best Poster Presentation 1st Place
Hackett, T. (Recipient), Sanders, R. G. P. (Contributor), van den Berg, T. E. (Contributor), Alveringh, D. (Contributor) & Schmitz, J. (Contributor), 23 Feb 2024
Prize
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Advances in 2D Anemometry
Hackett, T. L., Sanders, R. G. P., Choi, J. Y., Džemaili, N., Winnen, V., van den Berg, T. E., Alveringh, D. & Schmitz, J., 23 Oct 2024.Research output: Contribution to conference › Poster › Academic
Open AccessFile -
A Machine Learning Enhanced MEMS Thermal Anemometer for Detection of Flow, Angle of Attack, and Relative Humidity
Hackett, T., Sanders, R. G. P., Schmitz, J., Alveringh, D., van den Berg, T. E. & Choi, J. Y., Jul 2024, In: IEEE Sensors Letters. 8, 7, 4 p., 6008304.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile167 Downloads (Pure) -
A Multi-Parameter measurement system for MEMS Anemometers for Data Collection with Machine Learning Outcomes
Hackett, T. L., Sanders, R. G. P., van den Berg, T. E., Alveringh, D. & Schmitz, J., 23 Feb 2024.Research output: Contribution to conference › Poster › Academic
Open AccessFile