Waveform similarity reveals the relationship among pressure, acceleration and velocity in shallow water: a study based on seismic records from different sensors
Bibliographic record
Abstract
Globally, countries along oceans attach great importance to research involving oceanic observations. In the past 60 years, the United States and Canada, Japan, and the European Community have continued to promote development of ocean Seafloor seismic observations. The first Seafloor seismic station in China was built in Fujian in 2018, the Wuyu Island Seafloor seismic station, has recorded more than 100 earthquakes since it began operations more than a year ago. A far-field spherical wave incidence, which can be approximately considered a plane wave, and the sound pressure and vibration velocity are in phase; In the low frequency range (0.1-10Hz), The theory of "forced oscillation" describes that the change of water pressure is proportional to the vertical component of ground acceleration. We demonstrate the equivalence of the acceleration, velocity in shallow water and water-pressure signals for a set of local earthquakes .The cross spectrum method is used to analyze the similarity characteristics of velocity and acceleration with pressure signals at different frequencies. In addition, The similarity relationship between sound pressure and velocity acceleration in different frequency ranges is visually displayed through similarity probability distribution. The results show that with the decrease of frequency, the influence of hydrostatic pressure on the pressure detector gradually increases, and the pressure detector gradually changes from high-velocity correlation to high-acceleration correlation. Our work is not only to prove the existence of "forced oscillation" frequency, but also to explain the reason for high similarity of different types of waveforms by using formulas. Finally, we analyze the position of conversion frequency points through probability density distribution. This work can put forward a new design idea for the future research and development of hydrophone type Seafloor seismometer.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".