MD-0550 Calibration dataset by UT-363 Anemometer Calibrator Sensor for Laminar and Turbulent Airflow
Product Description — MD0550 Airspeed Sensor Calibration Dataset — Wind Tunnel Experiment with UT-363 Reference.
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price: €5.00 EUR
MD0550 Airspeed Sensor Calibration Dataset — Wind Tunnel Experiment with UT-363 Reference
This dataset contains full calibration results for the MD0550 analog airspeed sensor, measured inside a custom-built subsonic wind tunnel.
Data was acquired using a UNI-T UT-363 digital anemometer as the reference instrument.
The experiment was performed under two airflow conditions:
- Laminar flow (with honeycomb flow straightener)
- Non-laminar / turbulent flow (no honeycomb)
- More than 100+ measurement points were collected across both configurations.
What’s Included
You receive a structured Excel dataset containing:
- Un-calibrated MD0550 Output Data
- Raw voltage/counted readings
- Corresponding UT-363 airspeed values
- Separate sheets for Honeycomb (H) and Non-Honeycomb (NH) tunnel states
- Calibrated Data (Post-Regression)
- Linear regression calibration
- Sensor error & deviation analysis
- Corrected MD0550 airspeed output
- Graph-Ready Data
- Clean tables used for plotting
- Values organized for immediate charting or model fitting
- Experiment Notes
- Tunnel configuration
- Sensor mounting
- Airflow generation method
- Observed disturbances
- Data validation notes
Use Cases
Perfect for:
- Airspeed sensor research
- DIY or academic projects
- Mechatronics & instrumentation coursework
- Regression testing / verification models
- Benchmarking low-cost airspeed sensors
- Replicating or improving calibration methods
Experiment Summary All data originates from a university wind-tunnel research project supervised and validated by the Head of the Mechatronics Engineering Department. The calibration was performed in controlled conditions with repeated measurements to improve reliability and remove noise outliers.
File Format
- 2× Excel file (.xlsx)
- 4 detailed sheets: Un-calibrated, Calibrated, Graph, Notes
- Clean, labeled columns
- Ready for MATLAB / Python / Excel / LabVIEW workflows
➡ https://creativedesigns840.gumroad.com/l/odvsbd
Technical Dossier on Gumroad