Key technology research on ultrasonic ranging of double center hole of air and underwater cast pile based on adaptive filtering algorithm
Bibliographic record
Abstract
To overcome the obstacle of ranging by using the same type of ultrasonic transducer in two medium such as water and air, whose sound wave transmission characteristics are of significantly different, this paper proposed a dual medium ultrasonic ranging scheme, with the application background of cast-in-place piles' borehole diameter measurement.Based on the analysis of media's influence mechanism on ultrasonic ranging performance, a high-sensitivity weak signals conditioning circuit is constructed, with front-end amplifier, bandpass filter, demodulator, back-end amplifier and lowpass filter, which enables the ultrasonic transducer dedicatedly designed for underwater ranging can work in the air.On this basis, by designing a dual channel signal conditioner and increasing the ultrasonic emission power, the problem of ultrasonic ranging in air and underwater using unique type of transducer is solved, and the media in which ranging is ongoing can be distinguished at the same time.To verify the scheme's effectiveness, an experimental platform is built and ranging experiment is conducted in both air and water.The result proves that the expected ranging range and accuracy can be achieved under both media conditions, which lays theoretical foundation and provides engineering approach for similar scenarios.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".