Static and Dynamic Weighing of Rolling Stocks by Mean of a Customized FBG-Sensorized-Patch
Bibliographic record
Abstract
The structural health monitoring (SHM) of an infrastructure is of fundamental importance for the structure and people safety. Fiber Bragg Grating (FBG) sensors allow to design for each application, a tailored array of quasi-distributed sensors integrated to the infrastructure. To ensure the structural integrity of the railways is crucial to verify that the infrastructures comply with safety requirements to carry out their task. Railways rolling stock must comply with speed limits, the maximum number of wagons, maximum weight limit distributed on each axis of the wagons and the allowed number of trains on specific routes. The identification of the vertical load acting on each wheel is fundamental for the safety of a rolling-stock moving on a railway line. This paper presents the results of a test campaign on sensitive smart patches for static and dynamic weighing of trains. The system aims to generate a gripping system based on the magnetic force of a plastoferrite patch, taking advantage of the peculiarity that the rails are made of ferritic steel. This solution has the benefit of simplifying and speeding up the installation process and enabling a fast and easy removal or change in the configuration of the sensors array on the rail.
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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 | 0.000 | 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 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".