Research on Position Identification of Missing Teeth of Crankshaft Based on Optimal Threshold Method
Why this work is in the frame
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Bibliographic record
Abstract
In order to identify the engine TDC position accurately, this paper establishes the probability distribution mathematical model of signal crankshaft flywheel an d realized position identification of missing teeth with optimal threshold metho d. The H2 IC engine experimental data is acquired and analyzed, the varia nce distribution of the normal teeth at different speed is calculated, and the probability distribution of the speed ratio between current and last speed ncurrent/nlast obeys normal distribution. The genera l expression of optimal threshold Tjudge for different signal cranksha ft flywheel is educed, and the correctness is validated by three different sig nal crankshaft flywheels, including 60-2, 60-3 and 30-2. The critical value o f speed fluctuation ratio, when error identifcation of missing teeth occurs, is obtained finally, the increasing missing teeth number is benefit for preventing e rror position identification of missing teeth.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it