A Wideband, Low-Noise Accelerometer for Sonar Wave Detection
Bibliographic record
Abstract
This paper presents the development of a highperformance micromachined capacitive accelerometer for detection of sonar waves. The device is intended to replace existing hydrophones in towed array sonar systems, and thus, needs to meet stringent performance requirements on noise, bandwidth, and dynamic range, among others. The in-plane, single-axis accelerometer is designed based on a mode-tuning structural platform. A frame was used instead of a solid plate for the proofmass of the device, allowing us to push undesired vibration modes beyond the operating bandwidth of the device while enabling us to employ a portion of the area for capacitive sensing elements. The designed accelerometer was fabricated on a silicon-on-insulator wafer with 100-μm device layer with capacitive gaps of ~2.2 μm. The sensitivity of the accelerometer is 4 V/g with a noise spectral √ density of better than 350 ng/√Hz. The fundamental resonant frequency of the device is 4.4 kHz. The open-loop dynamic range of the accelerometer, while operating at atmospheric pressure, is better than 135 dB with a cross-axis sensitivity of less than 30 dB.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".