Bibliographic record
Abstract
This study presents a microphone-based system for wind speed measurement, eliminating the need for traditional mechanical components. The primary objective is to demonstrate the feasibility of using an ultrasonic transducer and acoustic sensors, specifically digital or analog microphones, to detect the change of phase differences due to wind speed. In contrast to conventional anemometers which rely on moving parts, such as cups or vanes, the proposed system uses the change of the phase shift or pulse delay in the microphones as a measure of time-offlight (ToF). The research involves the design, calibration, and testing of a prototype that integrates sound wave analysis, wind velocity estimation, and computational methods. Key factors such as environmental noise, microphone response characteristics, electronic interference, and calibration were considered to optimize measurement accuracy and reliability. The results suggest that the microphone-based anemometer offers an inexpensive, viable solution with advantages including reduced mechanical wear, lower maintenance requirements, and lower manufacturing costs. The findings prove the concept of ultrasonic and microphone wind speed measurement, opening the door for further refinement of the technology. This work contributes to the growing need for acoustic wind speed measurement solutions for both environmental monitoring and industrial applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".