Fault Detection and Isolation for Brake Rotor Thickness Variation
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

 
 
 Brake rotors are critical parts of the disc braking system for modern vehicles. One common failure for brake rotors is the thickness variation, which may result in unpleasant brake pulsation, vehicle vibration during braking, or eventually lead to the malfunction of the braking system. In order to improve customer satisfaction, vehicle serviceability and availability, it is necessary to develop an onboard fault detection and isolation solution. In our previous work, the vibration features of master cylinder pressure, vehicle longitudinal acceleration and wheel speed were identified as fault signatures. Based on these fault signatures, a vibration- based fault detection and isolation algorithm is developed in this work. The difference of frequency response between the braking period and the normal driving period (non-braking) is employed to improve the algorithm robustness. The experiment results demonstrate the proposed algorithm can robustly diagnose the thickness variation fault and isolate the fault to each vehicle corner.
 
 
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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