Fault Diagnosis and Prognosis for Satellite Formation Flying: A Survey
Bibliographic record
Abstract
Fault diagnostics and prognosis are vital functions of engineering systems, mainly fault prognosis, which is a relatively novel area and requires further development. By applying these methods, the system can be enriched with the ability to detect and isolate faults before they result in failures; in addition, fault propagation can be predicted, and maintenance can be considered to reduce the risk of severe failure. This paper focuses on the problem of satellite formation fault diagnosis and prognosis in the literature. Multi-satellite networks that cooperate as multi-agent systems are primarily used to implement cutting-edge technologies and improve future Earth and space observing missions. Space systems constantly encounter numerous failures due to the hazards and challenges of the space environment that need to be tackled. The current starts with an overview of the main concepts and motivations behind the deployment of small satellites in constellation settings and the detection and prediction of their faults. Next, recent papers on fault diagnosis and prognosis of single and multiple agent(s) or satellite(s), working individually or in collaboration, are reviewed. Comprehensive comparisons and categorization of the reviewed literature are included throughout the paper leading to existing research gaps for future work.
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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".