Studying of the noise sources in a pneumatic nail-gun process
Bibliographic record
Abstract
Despite generating high noise levels responsible for hearing loss among workers, nail-guns have been used to connect wood pieces since the 50s. The present study belongs to a broader investigation aiming to reduce noise emissions in nail-guns. This noise reduction objective may be achieved by a nail-gun concept design improvement. This requires a study of the noise sources in time domain. The study uses an advanced measurement setup to identify the existing noise sources and their causes in each time interval. The setup includes nine microphones, two accelerometers, two pressure transducers, and a high-speed camera. Three major noise sources were identified during the nailgun process: the air exhaust, the body of the machine, and the workpiece. The air exhaust noise is radiated from the air exhaust holes mostly before the nail driving operation and during the air exhaust process. The noise radiated from the body of the machine is caused by vibrations of different internal/external parts of the machine and air movements. It persists almost throughout the whole duration of the nailgun process. Finally, the workpiece noise is radiated from the vibrating workpiece starting simultaneously with the nail driving operation and ending before the start of the air exhaust process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".