Satellite fault diagnosis using a bank of interacting Kalman filters
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 main objective of this work is development and testing of a detection, isolation, and diagnosis algorithm based on interacting multiple model (IMM) filters for both partial (soft) and total (hard) reaction wheels faults in a spacecraft. This is shown to be accomplished under a number of different faulty mode scenarios for these actuators associated with the attitude control system (ACS) of a satellite. Various operating and faulty conditions due to changes and anomalies in the temperature, the power supply line voltage, and the loss of effectiveness of the torque and the current are considered in each reaction wheel associated with the three axes of the satellite. Once a fault mode is detected and isolated the recovery procedure can subsequently be engaged by invoking appropriate switching control strategies for the ACS. The application of a bank of interacting multiple Kalman filters for detection and diagnosis of anticipated reaction wheel failures in the ACS is described and developed. Compared with other model-based fault detection, diagnosis and isolation(FDDI) strategies developed in the control systems literature, our FDDI strategy is shown, through extensive numerical simulations, to be more accurate and robust with potential for extension to a number of other application areas.
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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