A Thrust Model Aided Fault Diagnosis Method for the Altitude Estimation of a Quadrotor
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Bibliographic record
Abstract
In this paper, a new fault diagnosis method is presented for the sensors in the vertical direction of a quadrotor. Different from the existing methods that treat the inertial sensors and the measurement sensors separately, the presented method is capable of dealing with both the z-axis accelerometer and the barometer. The knowledge of the thrust model is used to generate an analytical redundancy based fault diagnosis approach for altitude estimation. The filter design, fault detection, isolation, and recovery problems are addressed. An improved chi-test method is used for fault detection. Real-flight data is used to validate the proposed approaches, showing that the faults of the z-axis accelerometer and the barometer can both be detected and the thrust model of a quadrotor can be used to replace the faulty z-axis accelerometer.
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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