A Novel Online Detection System for Wheelset Size in Railway Transportation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The online detection of wheelset size has important implications for ensuring the safety of railway operation and decreasing the maintenance costs. Based on laser displacement sensors (LDS), a novel online detection system of the wheel size is proposed using only six two-dimensional LDS and two one-dimensional LDS. The calculation principles of tread profile and wheel diameter are given, as well as the calibration method. Errors induced by wheel-rail vibration, misalignment, sensor noise, S-shape running, and wheelset differential are also analyzed. After system implementation, field experiments were performed using both standard wheel and several real trains. It turns out that the detection uncertainty of flange width and height is 0.1 mm and wheel diameter 0.3 mm, which can meet the requirements of maintenance.
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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 | 0.000 | 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 | 0.000 | 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 it