ПОКАЗНИКИ ПРАЦЕЗДАТНОСТІ КОНХОЇДАЛЬНИХ ЦИЛІНДРИЧНИХ ПРЯМОЗУБИХ ПЕРЕДАЧ З ПІДВИЩЕНОЮ ВАНТАЖОПІДЙОМНІСТЮ. ТЕОРІЯ
Bibliographic record
Abstract
The article is devoted to the actual problem of increasing the performance indicators of machine gear drives. To solve this problem, in the article proposed to use a conchoidal engagement made with a shifting of the reference profile and special contact conditions. A feature of the proposed engagement is that it is less sensitive to manufacturing and assembly errors compared to conventional conchoidal engagement. As a result of theoretical studies, the performance indicators of such an engagement were determined. This made it possible to determine the level of load during further experimental tests of new gears. Contact strength and meshing losses were selected as performance indicators subject to further experimental verification. The ratios of these indicators, calculated for conchoidal spur gears with convex-convex contact, made with a shifting of the reference profile, with similar involute ones, are theoretically determined. Comparative analysis of performance indicators was carried out for gears of involute and conchoidal engagement with the same parameters and shifting of the reference profile. It was found that for experimental conchoidal drives with shifting, the maximum load is 1.2 times higher than that of a similar involute drive with shifting, and the loss in engagement is 21% less. A rational area of application of the new gearing is machine drives for high power transmissions. Keywords: spur gears, conchoidal gearing, profile shift, convex-convex contact, meshing characteristics, teeth surface strength, gearing power loss
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.011 |
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".